何兴元
, 任春颖
He Xingyuan, Ren Chunying
中图分类号: F129.9
文献标识码: A
文章编号: 1000-0690（2018）07-0997-15
收稿日期: 2018-06-6
修回日期: 2018-07-19
网络出版日期: 2018-07-20
版权声明: 2018 《地理科学》编辑部 本文是开放获取期刊文献，在以下情况下可以自由使用：学术研究、学术交流、科研教学等，但不允许用于商业目的.
基金资助:
作者简介:
作者简介:何兴元（1962-）,男,辽宁义县人,研究员,博士生导师,主要从事森林生态、城市森林研究。E-mail: hexingyuan@iga.ac.cn
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摘要
森林是陆地生态系统的主体,森林生态系统监测技术是实现森林可持续利用与全球变化研究的重要支撑与信息保障。从4个方面概述了遥感技术在森林生态系统监测中的应用研究进展：森林遥感分类及变化监测、森林植被参数遥感反演、森林蓄积量与生物量遥感估算、森林干扰遥感监测等。结合遥感技术的发展,总结了森林生态系统监测中使用的多源遥感数据和各类模型,提出集成地面调查数据、高分地-空雷达扫描监测技术,以及多源光学遥感建模技术和生态系统过程模型,构建多维度、多尺度、高时间密度的森林生态系统监测平台的研究展望。
关键词：
Abstract
Forest is a main component of the terrestrial ecosystem, and its monitoring is the vital support for sustainable utilization of forest and global change researches. The home and aboard progress of remote sensing techniques application on monitoring forest ecosystems was concluded in this paper from four respects: classification and changes detection, the retrieval of vital ecological parameters of forest ecosystems including tree height, leaf area index, canopy density, etc., the estimation of stand volume and biomass, and disturbance monitoring. After summarized remote sensing data and models used in forest ecosystems monitoring, research prospect of establishment of integrated forest ecosystems monitoring platform with multi-dimension, multi-scale and high time density were put forward, which synthesized filed data, land-to-air high-resolution radar scanning techniques, multi-source optical remote sensing modeling and process models.
Keywords：
森林是陆地上面积最大、分布最广、组成最复杂、资源最丰富的生态系统,在维持生物多样性、涵养水源和碳固持等生态功能,以及提供生物资源等经济功能中发挥着不可替代的作用[1,2,3]。然而,广泛的资源开发及全球变化正在以前所未有的速度和强度改变着森林生态系统,同时,森林面积减少和退化对陆地生物圈及其它地表过程也产生了深刻而重要的影响。2015 年联合国森林论坛第十一届会议指出,森林可持续管理已经提升到事关人类社会文明进程的全球高度,并与生物多样性、荒漠化等问题共同成为陆地生态系统保护目标和诸多国家的基本战略目标[4]。森林经营管理是一个长期过程,需要获取森林分布、组成、结构、干扰随时间变化等动态信息。因此,森林生态系统监测技术是实现森林生态系统保护与可持续利用的重要支撑和信息保障,而且对地区乃至全球环境变化研究意义重大[5,6,7]。
目前森林生态系统监测的内容由森林组分及结构、蓄积量和面积估算,扩展到森林生态系统的各个方面,如森林生物量、森林健康、生物多样性、野生动植物等[8]。由于森林生态系统具有动态性、生产周期长、面积辽阔等特点[9],样方水平上的传统调查方法只能测量一些有限的“点”,存在着工作量大、成本高、周期长、效率低和时效性差等问题[7,10],且在监测有关生物多样性、资源蕴藏量和生态系统结构功能的关键指标（如净初级生产力、土地覆盖、干扰等）时,对大尺度和跨尺度格局与动态的把握存在困难[11,12]。遥感技术具有连续时空领域的观测能力,不仅能够获取森林资源的数量、空间分布和动态变化信息,结合各种模型和样地调查,还可实现森林郁闭度、生物资源蓄积量等参数的定量反演[13],可满足不同尺度森林资源、生态过程监测分析的需求。因此,遥感技术作为一种有效的监测手段已经广泛应用于森林资源清查、经营管理和决策支持等领域。
伴随着遥感技术的飞速发展,遥感数据的时间、空间和光谱分辨率都在不断提高,尤其是无人机遥感和激光雷达技术的日趋成熟,极大地推动了遥感技术在森林生态系统监测领域的应用。本文仅从遥感在森林生态系统监测领域应用较为成熟和广泛的4个方面进行了总结与概述,以期梳理出遥感技术在此领域的研究热点及发展趋势,并为相关研究者提供借鉴与参考。
林分类型和物种多样性表征了森林生态系统的基本组成[14],因此,森林植被类型和树种识别是森林调查中的首要环节。不同树种具有不同的光谱特征,可利用树种的光谱特征信息将不同树种、不同林型从遥感影像中区别开来。
由于森林生态系统特殊的地理环境,使森林植被普遍存在“同物异谱”和“异物同谱”的现象[15]。因此,只使用单一的光谱特征进行森林类型区分较为困难,多数情况下仅能实现林地与非林地类型的精确提取。将光谱信息与纹理、地形、环境等特征结合后,森林类型可以进一步细分为阔叶林、针叶林以及针阔混交林等,如郝泷等利用西藏自治区林芝县Landsat OLI影像,结合地形图、样地调查数据及森林资源二类调查数据,基于纹理信息的CART决策树,进行针叶林、阔叶林、灌木林等森林类型的识别[16]。高时间分辨率影像的出现,使得物候特征成为森林类型识别的重要特征,如张増祥利用MODIS数据同时结合DEM高程数据,采用最大似然分类方法进行针叶林和阔叶林自动分类,然后利用MODIS数据易于获取、重访时间短的特点,计算7~9月生长季和11月至翌年1月落叶季植被的植被指数EVI的差别进行常绿林和落叶林的自动分类,取得较好效果[17];贾明明等利用长时间序列的MODIS数据产品提取得到不同森林类型的物候特征,并与中等分辨率的环境星影像结合,提出了基于面向对象的落叶阔叶林、常绿针叶林、落叶针叶林、针阔混交林和落叶灌木林遥感自动识别方法[1]。20世纪80年代,高光谱遥感的出现突破了光谱分辨率这一瓶颈因子,在光谱空间上大大抑制了其它干扰因素的影响,能够准确地探测到具有细微光谱差异的各种地物类型,极大地提高了森林树种的识别精度[18]。随后发展的激光雷达技术可有效地反演森林的冠层信息,从而为森林类型的识别提供辅助信息。但激光雷达和SAR较多光谱、高光谱及组合传感器识别的树种范围狭窄。因此,近年来,多源数据的融合,尤其是主被动遥感结合如高光谱遥感与LiDAR数据的融合在精细树种遥感识别中应用较多[19]。
传统的森林植被遥感分类方法以像元为基本单元,仅依靠森林植被的光谱信息,错分现象严重且分类结果存在严重的“椒盐现象”[20, 21]。面向对象的森林植被遥感分类方法,通过对影像的分割,使同质像元组成大小不同的对象,利用森林植被的几何形态、结构信息如纹理、形状、结构和空间组合关系等[22],在一定程度上提高了森林植被遥感分类的精度[1, 23]。
近年来,森林植被遥感分类采用的数据源由单时相数据向多传感器、多时相数据发展,分类方法也趋于智能化,分类精度有了显著提高[24, 25]。如基于一定规则集计算隶属度或设置相关阈值进行森林类型遥感识别的模糊聚类与阈值法[26, 27],神经网络、支持向量机等机器学习技术[28, 29],以及基于小波分析、分形理论的分类方法等[25, 30]。森林植被遥感分类受到多种因素的影响,如森林树种混交程度、地理环境复杂程度等,上述分类算法各有利弊,如机器学习存在过度学习的缺点,阈值法所需的专业知识较多且移植性差等,总体而言,这些分类方法在应用中往往具有很大的地理局限性。
森林变化遥感监测就是通过一定的数学运算、变换分析等基础方法来检测影像是否发生变化以及变化的程度[31]。根据是否对图像进行分类,可以将其归纳为图像直接比较法和分类后比较法两大类[32]。图像直接比较法通过直接比较不同时期遥感影像的光谱变化来反映森林植被变化,分类后比较法是对不同时间的遥感数据进行分类后比较各时期森林的分布变化来监测森林生态系统的变化[21]。
常用的森林动态变化遥感监测方法主要包括图像差值、主成分分析、变化矢量分析和分类后比较方法[33, 34]。其中,图像差值与变化矢量分析法是假设地物变化会在不同时相的图像上引起像元灰度值的明显改变,通过选择阈值来确定图像中的变化区域,因此,选择合适的波段和阈值十分关键,同时,辐射校正和几何校正的精度对监测效果有着明显的影响。图像差值法虽简单直观,但不能提供变化类型信息。变化矢量分析法可以理解为图像差值法的扩展,在理论上可以处理多光谱数据,而且能够提供变化类型信息[35]。主成分分析法优点是可以减少数据间的冗余信息,并且变化信息在变换后的新图像上得到增强,便于变化区域的提取和再处理。缺点是它们不能提供详细的变化类别信息,而且需要进行复杂的矩阵运算和阈值确定。主成分分析法在森林的植被变化、森林死亡率和落叶的变化监测中已经得到了应用[36, 37]。
分类后比较法比较容易实现,目前,有关森林生态系统面积、范围以及类型动态变化的遥感监测研究大多数采用分类后比较法,这类方法可以减少大气、传感器差异等外部因素对变化监测的影响,不过该方法需要大量的训练样本来进行监督分类或非监督分类,实际工作中经常运用图像变换、植被指数、高级分类方法或模型、多源数据集成等来提高分类的精度,但是利用它对历史数据进行分类较困难[35, 38]。
随着模式识别、数据挖掘以及机器学习等理论的发展,使得变化检测方法更加综合,尺度更加深入,如面向对象的变化检测方法[39]、基于模型的变化检测方法[40, 41]、以及基于组合的变化检测方法[42]等, 未来的研究趋势将侧重于多源数据的融合和算法的集成与应用,同时结合像元特征、整体影像特征以及较高精度的辅助数据来提高对变化区域的检测和识别能力。
森林植被生态参数（树高、冠幅、叶面积指数、郁闭度、胸径等）是森林生态系统调查不可或缺的测量内容,遥感技术的发展应用为大尺度的重要生态参数获取及其空间变异研究提供了强大的技术支撑[11, 43]。其中,胸径和冠幅主要利用激光雷达数据尤其是激光点云数据基于算法提取,且冠幅与郁闭度有较好的相关关系[44,45,46],故本节仅就树高、叶面积指数及郁闭度进行概述。
树高是反映林地质量及定量估算地上生物量的重要参数,也是获取森林初级生产力和生物多样性的必要信息,是碳循环等多种生态模型建立的基础[47,48,49]。树高遥感估算主要基于如植被指数等波段比值或单波段反射率[44, 50]、DEM等地形遥感因子[50, 51]、激光点云和波形特征值[52,53,54]等建立统计模型。由于光学遥感信号不具有穿透性,难以到达森林冠层以下的地表,利用光学遥感数据进行森林树高的反演在森林垂直结构研究作用较小[55, 56]。而雷达数据可以提供森林垂直结构测量数据[57,58,59],以激光雷达和极化干涉合成孔径雷达较为常用[60, 61]。其中,激光雷达能较精确的测量森林高度,如星载大光斑激光雷达ICESat/GLAS 数据范围覆盖全球,多应用于树高信息的获取[62, 63]。但目前激光雷达尚不能进行大面积的连续覆盖数据获取[64],而极化干涉合成孔径雷达技术可实现基于物理机理的大面积森林高度测量[65, 66]。
无人机遥感以其自动化、智能化、专业化快速获取空间信息,并实时处理、建模和分析的技术优势,在树高提取上得到了较好的应用[67]。无人机技术多利用研究区的数字表面模型或单株树木的立体像对来提取树木高度,抑或利用无人机获取高分辨率正射影像,对研究区进行三维重构,将三维点云分割为树木点云及树下地面点云后进行相关处理得到树木的高度[68]。如Zarco-Tejada 等利用无人机搭载可见光-近红外数码相机采集高分辨率影像,通过三维重构生成林区数字表面模型获取树木高度,且精度较高,与激光雷达相比更为经济[69]。但因其续航时间较短,易受低空天气影响等,目前单独应用于大面积的树高提取研究仍较少,多为中小尺度的树高反演和辅助大面积树高反演及其精度验证。
叶面积指数指单位地表面积上总绿叶面积的一半[70, 71],控制着森林植被冠层的光合、呼吸、蒸腾、碳循环等多种生物物理和生理过程,广泛应用于森林生长及生产力模型、净初级生产力模型、大气模型等[72, 73]。
遥感反演森林植被叶面积指数的方法由基于定位实验的经验模型逐步发展为半经验统计模型和生物物理模型方法[74,75,76,77]。刘振波等基于MODIS BRDF遥感模型参数产品对小兴安岭五营林区森林冠层叶面积指数进行反演,得到基于比值植被指数构建的二次多项式统计模型精度最高[78]。Tang 等利用机载激光雷达全波形数据,基于物理模型方法中的几何光学-辐射传输混合模型估算出了拉塞尔瓦热带雨林的垂直方向叶面积指数连续变化曲线[79]。目前通过统计模型反演叶面积指数应用较广,利用高光谱数据、激光雷达数据及多角度遥感数据反演为热点。统计模型方法参数少、计算效率高 、容易实现,但其基于经验关系,模型随着传感器、植被类型、时间及地理位置的变化而改变,因而建立大范围适用的统计模型非常困难,因此,多应用于小区域的叶面积指数反演中[80, 81]。生物物理模型方法基于森林植被冠层的光子传输理论,模拟冠层中的辐射传输过程建立模型,具有较强的物理基础,但要求输入较多难以获得的参数,且这些参数也易带来误差将导致反演结果的不确定性增加[80, 81]。
郁闭度通常指森林内树冠的垂直投影面积与林地面积的比值,是反映林分密度、评价森林生产力和分解率重要林分因子,也是判定森林状况和进行森林碳储量、蓄积量和生物量估测的重要指标[82, 83]。
基于遥感数据及地面实测样地数据,森林郁闭度遥感估算主要采用统计模型法和物理模型法[84, 85]。如牛战勇等利用TM 影像提取归一化植被指数,结合实测真实叶面积指数和土地利用信息确定的聚集度系数,计算有效叶面积指数,并构建 NDVI 与有效叶面积指数间的回归模型进行较精准的郁闭度估算[86]。Zeng 等以Landsat TM 和 MODIS 影像为数据源,在混合像元分解的基础上,利用几何光学模型定量估算了中国三峡地区森林郁闭度等参数[87]。目前研究以多光谱数据进行郁闭度估测居多,但多光谱数据波段数少、光谱分辨率低导致估测效果不佳,高光谱数据可以从众多的波段信息中筛选植被差异性显著波段进行植被覆盖信息提取,提高郁闭度估测精度。如Pu等基于Hyperion影像采用逐步回归方法选取与森林郁闭度关系紧密的变量进行多元回归建模,估测精度能达到近 85%[88]。但高光谱数据波段数多、冗余大,高光谱数据的降维和特征提取成为高光谱数据处理的关键技术[89]。激光雷达以其极高的角分辨能力、距离分辨能力、抗干扰能力等优点,在林木高度测量与林分垂直结构信息获取方面具有无可比拟的优势[11]。如张瑞英等结合激光雷达数据和Landsat ETM+数据计算得到的8种植被指数作为自变量,使用多元逐步回归、随机森林和Cubist 3种模型得到经验关系估测温带森林郁闭度[90]。随着摄影测量技术和无人机遥感的发展,高分辨率航空影像、立体像对也在森林参数反演中得到了较好的应用,如José等利用多年高分辨率航空数码摄影照片进行了森林郁闭度的反演及分级分类并进行了时空动态分析,精度达到了95%,但其需要人为驾驶、成本较高[91]。王聪等基于几何光学模型,利用无人机遥感数据进行了郁闭度定量反演,并分析了无约束和全约束两种混合像元分解对反演结果的影响[92]。
目前,森林植被重要生态参数研究以三维结构、立体化遥感监测与评价为热点,多源数据及“卫-空-地”结合遥感监测平台得到了较好的应用。无人机等机载平台的激光雷达遥感监测在小尺度高精度的结构参数提取发挥了巨大作用,但相应的海量数据有效挖掘和提取及流程软件的开发仍待进一步研究。统计模型、机理过程模型和卫星遥感数据较适用于大尺度的结构参数反演,但统计模型算法移植性差,机理模型输入参数较多且各参数皆易带入误差。而移植性强的物理模型,其操作性较低,且未见有突破性的物理模型出现,结构参数反演的遥感物理模型多为几何光学模型和辐射传输模型的改良。
传统的森林蓄积量和生物量估测通常以局部人工地面实测方法为主,工作量大、周期长、数据更新慢,且对实物造成一定的破坏,而遥感技术可以通过光学、微波和激光雷达等传感器对森林蓄积量、生物量进行区域尺度实时快速估算,且不具有破坏性,是实现大尺度、长期、连续观测的主要技术手段。
蓄积量指一定森林面积上活立木的总材积,反映森林资源总规模、丰富程度的重要依据,往往与生物多样性高度相关,且基于森林蓄积量的碳储量计算也是森林固碳估计一个重要方法[93, 94]。
森林蓄积量的遥感定量估测研究集中在模型解算方法与蓄积量相关性较好的自变量因子、估测精度影响因素、建模样地抽样等方面。主要基于森林调查实测胸高断面、树高、树种等信息得到实测蓄积量值,利用光学遥感与微波遥感或多源数据相结合,依据光谱信息、纹理信息和环境地形因子,建立描述非线性关系的模型算法与人工神经网络等机器学习模型[95,96,97]。如Giannico等利用激光雷达点云数据得到胸高断面及平均树高,通过多元非线性回归的森林异速生长模型得到较为精准的蓄积量[98]。Schoneberg等结合地面区域森林调查数据和航空激光扫描数据/航空立体影像,通过对比随机森林和K最近邻方法,得到利用航空激光扫描数据得到的精度较高,但其费用也是航空立体影像的1.5倍,且使用随机森林和K最近邻方法的精度相近,从而得到航空立体影像是较适宜于森林蓄积量反演的数据源[99]。因遥感波段间存在一定的多重相关性,线性回归会使估计方差增加,最终导致估计精度降低及模型稳定行差[100, 101]。非线性KNN方法靠邻近样点数据来估算,样点的分布会直接影响估测的结果,且计算量很大[102,103,104]。人工神经网络等机器学习方法的暗箱操作无法表达和分析被预测系统的输入和输出间关系,难于对结果做统计检验[96, 102, 105]。
生物量通常以单位面积或单位时间积累的干物质量或能量来表示,是森林生态系统运行的能量和营养物质来源,是衡量生态系统生产力的重要指标,也是研究森林生态系统碳循环的重要基础[106,107,108]。生物量估测大多基于实测胸径、胸高等调查数据,根据不同树种的异速生长方程计算得到。近年来,多源遥感数据广泛应用于生物量反演。其中,光学影像只能观测到森林冠层信息,不能观测到植被枝、干,采用光学影像估测整个森林生物量,会造成较大误差,而合成孔径雷达的P波段和L波段对植被冠层和树干都有一定的穿透能力,可获得冠层、树干甚至地表表层的土壤信息,但林木结构、含水量、地形、林下背景环境等都会对后向散射系数产生显著影响,且后向散射强度随着生物量增加而增加,达到一定生物量水平后,后向散射趋于饱和[109];而激光雷达成像的不连续性与处理的复杂性,使其在大范围生物量建模应用中受限。
遥感反演森林生态系统生物量主要基于经验模型和遥感机理模型[109,110,111,112,113]。其中,基于光谱响应或后向散射系数与森林结构参数之间的关系,应用多源传感器测定基部面积、郁闭度、树高、胸径和叶面积指数等间接估算森林生物量的经验模型应用较广。Zhao 等基于实测树种胸径数据和异速生长方程计算实测生物量,并利用ALOS PALSAR雷达影像和Landsat TM 多光谱影像提取光谱信息、后向散射系数、纹理特征等,基于逐步回归分析和影像融合技术,分别建立了多光谱生物量模型、雷达生物量模型、结合多光谱与雷达的生物量模型及融合多光谱与雷达的生物量模型,结果表明结合多光谱和雷达的逐步回归模型精度最高[112]。Ni 等利用ALOS/PRISM立体成像的点云数据与美国30 m 分辨率的冠层高度图,基于回归分析,表明利用立体成像得到的冠层高度可以用来估算森林生物量[114]。Wang等利用基于机理改进的MIMICS模型、叶面积指数和树高,结果表明地上生物量联合反演的精度由原来的0.706提高到0.788[115]。此外,据树木的蓄积量推算森林的生物量也是近几年来研究的热点问题[116, 117]。
目前大区域的森林生物量反演大都采用非参数化方法如人工神经网络等[118],需大量地面实测数据进行训练,且在高分辨率的像元或地面测量样方精度难以满足需求,高精度的大区域的森林生态系统生物量遥感反演方法亟待进一步研究[119, 120]。此外,众多研究表明多光谱与雷达数据在森林生物量反演中普遍存在信号饱和现象,但对于不同遥感数据源的信号饱和点精确研究仍较少,不利于森林生物量反演中遥感数据的充分科学利用[111,112]。
干扰是森林生态系统动态变化的主要驱动力,影响林分的生长状态、林分物种组成和林分结构[121]。遥感监测的森林干扰包括自然干扰,如火灾、气象灾害、病虫害等,和人为干扰及由自然和人为因素共同形成的干扰,如林窗干扰等。其中,对于干旱等森林生态系统气象灾害与病虫害遥感监测方法类似,有直接监测水分减少引起的波谱曲线中近红外波段水分吸收峰值的变化,也可间接监测叶片结构、色素或者叶面积指数等重要生态参数变化的植被干旱响应来实现[122]。而人为干扰,如采伐、土地利用变化等主要多建立于森林植被变化结果进行时序变化研究,故本节仅就火灾、病虫害与林窗干扰进行论述。
目前,卫星监测森林火情主要使用的是NOAA,MODIS以及风云等中低空间分辨率、较高时间分辨率的极轨卫星,而航空遥感,尤其是无人机遥感,也被用于灾情的监测与评估,但所观测的区域较窄,也缺少有效提取火情信息的技术方法[123]。
20世纪60年代,国外开始利用航空红外探测技术来监测林火,主要利用燃烧时的辐射和森林在常态下的辐射间的差异,多基于NOAA/AVHRR数据和MODIS 数据,建立火灾与不同敏感波段的关系模型（如Dozier 模型等）[124,125,126]。近些年来,对于森林火灾的研究,不仅限于火灾的监测预警,更多的关注于火灾迹地的遥感识别、灾后火情损失评估与恢复和森林燃烧生物量等环境效应,分析森林火灾的碳排放量对全球碳循环的影响以及发生森林火灾时空特征[127]。如Krylov等利用ETM影像对森林郁闭度和森林覆盖损失进行估算,同时用 MODIS 数据对火烧迹地进行面积估计,从而对俄罗斯 2001~2011 年森林火灾进行更新并统计和分析[128]。Thomas等采用云-气溶胶正交极化激光雷达和中等分辨率分光辐射计监测气溶胶,并结合化学模型,得到了加拿大森林火灾所释放的黑碳浓度,并分析了其对格林兰岛冰盖中的黑碳浓度分布影响[129]。Navarro等利用Sentinel-2A多光谱影像,提取了归一化植被指数、归一化燃烧比率等波谱计算指数来研究马德拉岛森林火灾后植被和土地覆被状态的检测,并指出Sentinel-2A影像是灾后监测的有效工具[130]。
应用遥感技术监测森林病虫害的研究也已探索了几十年。20世纪30年代,研究发现病虫害导致植物光谱反射与辐射特征发生变化,在遥感图像上表现为光谱值的变化,特别是20 世纪80 年代高光谱遥感技术的出现拓宽了植被理化参数遥感定量获取新领域。遥感监测病虫害技术主要利用MODIS数据、Landsat TM影像 、SPOT数据、AVIRIS 高光谱数据和各类高空间分辨率数据,监测森林失叶[131]、林冠动态[132]、营养元素变化[133, 134]、受害森林群落的光谱变化[135,136,137]及病虫爆发与环境因子的关系等[14, 138]。如Stone等利用直升机拍的航空影像结合地面调查数据进行了蚜虫对辐射松冠层破坏的检测[139],Shafri 等利用机载高光谱成像技术对油棕榈植物园的灵芝茎基腐病进行检测,分别用不同植被指数和红边技术来区分病变和健康值株,其分类精度在73%~84% ,并指出航空高光谱成像可以用于规模较大的种植园内病害的检测和管理[140]。无人机遥感技术具有高时效、高分辨率、高机动性等优势和特点,能快速获取森林灾害程度数据,已成为森林病虫害监测的重要手段,但在山高坡陡、人迹罕至的偏远林区,无人机的全覆盖监测任务也面临巨大挑战。因此,基于地面调查获得病虫情等生物学信息,航空遥感及时掌握灾情信息,航天遥感保障监测的“全”覆盖,建立天空地一体化的森林灾害监测体系,对于降低灾害损失、保护森林资源和生态环境意义重大[141]。
林窗由英国生态学家Watt提出,主要指森林群落中老龄树死亡或因各干扰因素（如干旱、台风、火灾等）导致成熟阶段优势树种的死亡,从而在林冠层造成空隙的现象[142,143]。林窗是森林群落中经常发生的重要的小规模干扰,是森林生态系统更新演替的驱动要素,更是森林结构和功能维持的重要因子[144,145,146]。基于地面的林窗测量方法受数据精度差、人力成本高、覆盖范围小等因素限制,很难应用到整个森林群落[147]。传统二维的遥感技术由于光照条件和光谱不可分性,无法达到小尺度范围的群落生态学研究的要求,而激光雷达能进行复杂的森林三维结构信息提取、林窗景观尺度推译及微生境多样性监测等优势,在林窗干扰遥感监测中有较好的应用[148],如Vepakomma等利用小光斑激光雷达数据进行了阔叶冠层的大小从几平方米到几公顷的林窗识别,精度达到了96%,但激光雷达技术仍存在成本较高的缺陷[149]。轻量级无人机兼具及时和低成本的优点,已广泛应用于林冠结构与林窗研究[150],如隋丹丹等利用无人机航拍图像处理技术和样地调查数据,对鼎湖山南亚热带常绿阔叶林的林窗的几何特征和空间分布格局进行了研究,并分析了林窗分布特征及林窗面积与地形因子等环境因子的关系[151]。总体而言,利用遥感数据进行的林窗研究主要包括林窗、面积、形状和边界木高度等特征测量,林窗时空分布推演及林窗生成和闭合动态分析等方面[152,153,154]。如Li等提出了新的点云切片模型,利用地面激光扫描技术较好地反演了叶面积指数进而研究林窗动态[155]。
目前,遥感监测典型干扰仍存在时效性问题,且因病虫害的爆发与气象、地形等周围环境因子复杂相关系,需要利用相关的先验知识[156],火灾遥感监测也需建立完整的传感器网络来检测环境响应[157],林窗干扰研究尺度较小目前遥感监测研究较少仍以实地调查为主,故对于森林干扰的监测与预估的遥感模型方法和平台仍需进一步研究。
森林生态系统监测使用的遥感数据基本涵盖了目前所能用到的包括光学遥感、微波雷达、激光雷达、航空像片等多源数据,如WorldView、IKONOS、Quick-Bird、SPOT 等高分辨率数据、Landsat TM /OLI、CBERS CCD数据等中分辨率数据、MODIS、NOAA/AVHRR等低分辨率数据、Hyperion、AVIRIS高光谱数据、ATSER、MISR等多角度数据、PolInSAR、GLAS等雷达数据和无人机数据等[19, 158]。
其中,传统光学遥感发展较早,如Landsat系列有大范围的长时间序列影像可用于长期的森林生态系统动态研究[55, 159, 160],包括大尺度森林生态系统面积及其变化信息以及水平结构参数的获取。但其穿透性差,且对于浓密植被信息敏感性差、易饱和,较少用于森林生态系统垂直结构监测[119, 161]。高光谱遥感的光谱响应比宽波段的传统多光谱数据更灵敏,广泛应用于冠层生物物理参数和化学参数的估测,但其空间分辨率较低,混合像元问题较为严重,且同物异谱影响明显,在监测区分光谱特征相似的森林生态系统时仍然受限[11, 162, 163]。激光雷达可以获取高精度的三维空间结构信息,在森林结构参数获取方面具有显著的优势,但提供的光谱信息有限且数据获取的成本高,难以在较大尺度上应用[11, 159]。迅猛发展的无人机技术与3D图像重建技术结合,进一步实现了森林结构、林下生物多样性与生物资源的连续监测[164],因此,如何挖掘多源遥感数据信息,解决多源数据融合问题,充分发挥各遥感数据的优势,是实现高精度的森林生态系统分类、参数获取和灾害监测的研究难点和热点。
当前森林生态系统遥感监测方法多基于经验模型、生态系统过程模型、遥感物理模型和混合模型的方法。经验模型利用遥感数据或其指数与实测森林生态系统监测数据之间的相关性建立统计回归（如多元线性/非线性回归等）或非参数化算法（如决策树、K最近邻、人工神经网络和支持向量机等）来进行,因操作简单、参数容易获取而广泛运用于区域性森林生态系统遥感监测,但缺乏物理意义和机理基础,时空可移植性差[2, 80, 119]。生态系统过程模型方法描述森林生长和转换的机理过程以及碳循环在环境和气候变化下的响应特征等,如BEPS模型、MIMES模型、InVEST模型等[165, 166],主要应用于生物量、碳储量等森林参数监测,但对于微观结构参数反演精度较低,且需修订输入参数和模型验证,操作比较复杂。遥感物理模型通常采用数学公式描述,模型中参数具有明确的物理意义,包括辐射传输模型如植被二向性反射的辐射传输模型、几何光学模型、几何光学辐射传输混合模型[119, 167],但由于方程复杂、输入参数多、计算量大,操作中往往为了求解通常对多个非主要因素进行忽略或假定等缺点,导致在森林生态系统监测中实用性较差。混合模型如半经验半物理模型、利用迭代和查找表等方法耦合模型,因结合了各模型的优势,在森林生态系统监测中精度较高[81, 119]。因此,发展遥感物理模型或融合遥感数据与生态系统过程模型进行森林生态系统监测更有潜力。
中国已经建成网络化的森林生态系统监测体系（如CERN、CTERN等）,但以定点监测为主,且在森林生物资源及其开发利用对森林生态系统结构、功能影响方面较少开展工作,而集卫星、航拍、无人机3D图像、地面传感器于一体的立体观测平台刚刚起步,国内目前的工作还局限于一些算法研究,尚未实现实际应用。此外,森林实测数据采集较为困难,成本较大,而森林科研数据共享平台和大众贡献科学数据共享平台也尚未建立,导致重复工作及资源浪费。因此遥感技术在森林生态系统监测领域的应用不能仅仅停留在监测统计数据的发布或个案分析的层面,要全面提升森林生态系统遥感监测的科技转化和数据共享、集成水平,进一步推进基于遥感技术的森林生态系统评价与辅助决策功能研究,实现定量化、精细化和系统化,建成多尺度、高效率、高精度森林生态系统与生物资源监测平台[14]。
综上,集成地面调查的生态系统结构与功能数据（小尺度）,高分地-空雷达扫描监测技术（中尺度）以及多源遥感建模技术和生态系统过程模型（大尺度）,构建多维度、多尺度、高时间密度的服务于森林生态系统的监测集成平台,可显著降低监测模型的不确定性,为森林生态系统有效保护和林区经济可持续发展提供技术保障和平台支持。
The authors have declared that no competing interests exist.
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基于TM影像和样地数据，利用ERDAS处理软件平台，从影像中提取出可能与树高相关的遥感因子，并结合实测数据，通过多元分析中的因子分析及偏相关分析，获得对树高有显著性影响的自变量因子，运用逐步回归法建立树高估测模型。本研究以旺业甸林场为研究区域，其中以针叶林为主要研究对象，利用3倍标准差法进行数据筛选和偏相关分析，可得到该模型的相关系数较高（R=0．808），再利用剩余的18块未参加建模实地调查数据进行检验。结果表明，估测树高的总精度可达到88．55％。具有较好的估测效果。
Trees parameter extraction and tree height estimation based on TM images .https://doi.org/10.3969/j.issn.1673-923X.2013.09.007 URL [本文引用: 1] 摘要
基于TM影像和样地数据，利用ERDAS处理软件平台，从影像中提取出可能与树高相关的遥感因子，并结合实测数据，通过多元分析中的因子分析及偏相关分析，获得对树高有显著性影响的自变量因子，运用逐步回归法建立树高估测模型。本研究以旺业甸林场为研究区域，其中以针叶林为主要研究对象，利用3倍标准差法进行数据筛选和偏相关分析，可得到该模型的相关系数较高（R=0．808），再利用剩余的18块未参加建模实地调查数据进行检验。结果表明，估测树高的总精度可达到88．55％。具有较好的估测效果。
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随机森林算法在机载LiDAR数据林分平均树高估算中的应用研究 [J].https://doi.org/10.3724/SP.J.1047.2016.01133 Magsci [本文引用: 1] 摘要
<p>采用机载LiDAR数据估算森林结构参数是当前林业遥感中的研究热点。本文以福建省长汀县朱溪河流域为示范区,探讨了随机森林算法（RF）在机载LiDAR数据林分平均树高估测中的适用性。首先,通过渐进三角网（TIN）算法进行点云滤波并获取相应林分样地的植被点云子集和高程归一化的植被点云;然后,从归一化后的植被点云提取出高度分位数变量以及点云统计特征值等24个变量参数;最后,根据提取的变量参数和野外实测林分均高数据建立研究区林分平均高随机森林回归估测模型。研究结果表明,模型估测的样地平均树高与实测值具有明显线性相关关系,线性回归系数为0.938,相关系数达到0.968。对样地的估测精度都在86%以上,总体平均精度达到了93.17%。研究认为,基于植被点云变量参数的随机森林模型估测林分平均树高具有较高的可靠性。</p>
Journal of https://doi.org/10.3724/SP.J.1047.2016.01133 Magsci [本文引用: 1] 摘要
<p>采用机载LiDAR数据估算森林结构参数是当前林业遥感中的研究热点。本文以福建省长汀县朱溪河流域为示范区,探讨了随机森林算法（RF）在机载LiDAR数据林分平均树高估测中的适用性。首先,通过渐进三角网（TIN）算法进行点云滤波并获取相应林分样地的植被点云子集和高程归一化的植被点云;然后,从归一化后的植被点云提取出高度分位数变量以及点云统计特征值等24个变量参数;最后,根据提取的变量参数和野外实测林分均高数据建立研究区林分平均高随机森林回归估测模型。研究结果表明,模型估测的样地平均树高与实测值具有明显线性相关关系,线性回归系数为0.938,相关系数达到0.968。对样地的估测精度都在86%以上,总体平均精度达到了93.17%。研究认为,基于植被点云变量参数的随机森林模型估测林分平均树高具有较高的可靠性。</p>
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林区地形复杂、植被分布无序,且森林植被光谱信息相近,因而森林二级类型边界的确定成为土地覆盖遥感分类的难点.选择吉林省东部山区为研究区,以环境星影像(HJ-1 CCD)和中等分辨率成像光谱仪(MODIS)时序数据为基础,采用面向对象的分类方法进行森林植被类型的提取.分类特征参数主要选取了HJ-1 CCD的光谱和纹理特征,以及MODIS时序数据的物候特征.研究区总体分类精度为91.5%,Kappa系数为0.88,森林二级类型的分类精度均较高,其中落叶阔叶林的制图精度达到了97.1%.所用的面向对象分类方法与未加入物候特征的面向对象分类方法相比,森林二级类型的分类精度得到大幅度提高.
Object-oriented forest classification based on combination of HJ-1 CCD and MODIS-NDVI data .https://doi.org/10.5846/stxb201310112438 URL Magsci [本文引用: 3] 摘要
林区地形复杂、植被分布无序,且森林植被光谱信息相近,因而森林二级类型边界的确定成为土地覆盖遥感分类的难点.选择吉林省东部山区为研究区,以环境星影像(HJ-1 CCD)和中等分辨率成像光谱仪(MODIS)时序数据为基础,采用面向对象的分类方法进行森林植被类型的提取.分类特征参数主要选取了HJ-1 CCD的光谱和纹理特征,以及MODIS时序数据的物候特征.研究区总体分类精度为91.5%,Kappa系数为0.88,森林二级类型的分类精度均较高,其中落叶阔叶林的制图精度达到了97.1%.所用的面向对象分类方法与未加入物候特征的面向对象分类方法相比,森林二级类型的分类精度得到大幅度提高.
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树高是森林资源管理领域的重要参数,获取准确、大范围、空间连续的树高信息对于森林资源监测、管理和碳循环研究等都具有重要的意义。利用星载激光雷达ICESatGLAS波形数据,以大兴安岭塔河林业局营林区为研究区,针对不同地形条件选择合适的算法提取出GLAS光斑内的森林平均树高。联合GLAS波形数据与多角度光学遥感MISRBRF数据,应用随机森林机器学习算法获取塔河林场树高图,实现树高信息提取从点到面尺度上的扩展。用实测样地数据进行检验,其结果为:R2=0.72,RMSE=1.83 m,精度为85.22%。激光雷达数据和多角度光学遥感影像协同,弥补了2种数据各自的不足,为森林生物量以及碳储量的估算提供准确的基础数据。
Forest canopy height estimation using LiDAR and optical multi-angler data .https://doi.org/10.13332/j.cnki.jbfu.2014.04.006 URL [本文引用: 2] 摘要
树高是森林资源管理领域的重要参数,获取准确、大范围、空间连续的树高信息对于森林资源监测、管理和碳循环研究等都具有重要的意义。利用星载激光雷达ICESatGLAS波形数据,以大兴安岭塔河林业局营林区为研究区,针对不同地形条件选择合适的算法提取出GLAS光斑内的森林平均树高。联合GLAS波形数据与多角度光学遥感MISRBRF数据,应用随机森林机器学习算法获取塔河林场树高图,实现树高信息提取从点到面尺度上的扩展。用实测样地数据进行检验,其结果为:R2=0.72,RMSE=1.83 m,精度为85.22%。激光雷达数据和多角度光学遥感影像协同,弥补了2种数据各自的不足,为森林生物量以及碳储量的估算提供准确的基础数据。
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Current knowledge of the world carbon budget is reviewed with special emphasis on the question of whether the biota is a source or a sink for CO/sub 2/. The analysis shows through convergent lines of evidence that the biota is not a sink and may be a source of CO/sub 2/ as large or larger than the fossil fuel source. The issue is important because of the potential that changes in the CO/sub 2/ content of air have for changing climate worldwide. Various analyses suggest that human activities in the near future could release large additional amounts of CO/sub 2/ into the atmosphere with results that are substantially unpredictable.
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78 Integration of Landsat MSS and TM/ETM+ for annual time-series analyses. 78 Revised Tasseled Cap coefficients for new MSS post-calibration coefficients. 78 We derived disturbance and recovery metrics from spectral trajectories. 78 Disturbance metrics predicted live biomass better than single-date Landsat data. 78 Disturbance metrics were good predictors of dead woody biomass.
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Forest vertical structure from GLAS: An evaluation using LVIS and SRTM data [J].https://doi.org/10.1016/j.rse.2006.09.036 URL [本文引用: 1] 摘要
The Geoscience Laser Altimeter System (GLAS) on the Ice, Cloud and land Elevation Satellite (ICESat) is the first spaceborne lidar instrument for continuous global observation of the Earth. GLAS records a vertical profile of the returned laser energy from its footprint. To help understand the application of the data for forest spatial structure studies in our regional projects, an evaluation of the GLAS data was conducted using NASA's Laser Vegetation Imaging Sensor (LVIS) data in an area near NASA's Goddard Space Flight Center in Greenbelt, Maryland, USA. The tree height indices from airborne large-footprint lidars such as LVIS have been successfully used for estimation of forest structural parameters in many previous studies and served as truth in this study. The location accuracy of the GLAS footprints was evaluated by matching the elevation profile from GLAS with the Shuttle Radar Topography Mission (SRTM) DEM. The results confirmed the location accuracy of the GLAS geolocation, and showed a high correlation between the height of the scattering phase center from SRTM and the top tree height from GLAS data. The comparisons between LVIS and GLAS data showed that the GLAS waveform is similar to the aggregation of the LVIS waveforms within the GLAS footprint, and the tree height indices derived from the GLAS and LVIS waveforms were highly correlated. The best correlations were found between the 75% waveform energy quartiles of LVIS and GLAS ( r 2 = 0.82 for October 2003 GLAS data, and r 2 = 0.65 for June 2005 GLAS data). The correlations between the 50% waveform energy quartiles of LVIS and GLAS were also high (0.77 and 0.66 respectively). The comparisons of the top tree height and total length of waveform of the GLAS data acquired in fall of 2003 and early summer of 2005 showed a several meter bias. Because the GLAS footprints from these two orbits did not exactly overlap, several other factors may have caused this observed difference, including difference of forest structures, seasonal difference of canopy structures and errors in identifying the ground peak of waveforms.
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Estimation of the amount of carbon stored in forests is a key challenge for understanding the global carbon cycle, one which remote sensing is expected to help address. However, estimation of carbon storage in moderate to high biomass forests is difficult for conventional optical and radar sensors. Lidar (light detection and ranging) instruments measure the vertical structure of forests and thus hold great promise for remotely sensing the quantity and spatial organization of forest biomass. In this study, we compare the relationships between lidar-measured canopy structure and coincident field measurements of above-ground biomass at sites in the temperate deciduous, temperate coniferous, and boreal coniferous biomes. A single regression for all three sites is compared with equations derived for each site individually. The single equation explains 84% of variance in above-ground biomass (P < 0.0001) and shows no statistically significant bias in its predictions for any individual site.
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目前获取森林特征参数的主要方法是外业测量，工作量大、效率低。该文以中国自主研发的轻小型航空遥感系统为数据获取工具，以油松人工林为研究对象，通过对获取森林的激光雷达（light detection and ranging，LIDAR）点云数据去噪，分类，提取等过程获得单木的树高数据，对获取的航空影像数据进行预处理，匹配，拼接，分割及冠幅提取获得单木的冠幅数据，再与外业抽样调查的单木的树高、胸径建立回归模型，同时验证模型精度。试验结果表明：通过LIDAR点云数据提取的树高与实测的树高具有极显著的相关性，所建立的模型预测精度达97.5%，通过影像提取的冠幅与实测的胸径也具有极显著的相关性，预测精度达91.6%，基本上能够满足林业生产的要求。
Model of characteristic parameter for forest plantation with data obtained by light small aerial remote sensing system .https://doi.org/10.3969/j.issn.1002-6819.2013.08.019 URL Magsci [本文引用: 1] 摘要
目前获取森林特征参数的主要方法是外业测量，工作量大、效率低。该文以中国自主研发的轻小型航空遥感系统为数据获取工具，以油松人工林为研究对象，通过对获取森林的激光雷达（light detection and ranging，LIDAR）点云数据去噪，分类，提取等过程获得单木的树高数据，对获取的航空影像数据进行预处理，匹配，拼接，分割及冠幅提取获得单木的冠幅数据，再与外业抽样调查的单木的树高、胸径建立回归模型，同时验证模型精度。试验结果表明：通过LIDAR点云数据提取的树高与实测的树高具有极显著的相关性，所建立的模型预测精度达97.5%，通过影像提取的冠幅与实测的胸径也具有极显著的相关性，预测精度达91.6%，基本上能够满足林业生产的要求。
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Overview of forest resources change detection methods using remote sensing techniques . |
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森林资源监测技术发展趋势 [J]. |
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Trends and progress of forest resources monitoring technique . |
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森林资源动态监测技术综述 [J]. |
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Predicting southeastern forest canopy heights and fire fuel models using GLAS data [J].https://doi.org/10.14358/PERS.76.8.915 URL [本文引用: 1] 摘要
The Geoscience Laser Altimeter System (GLAS) is a waveform lidar system carried on board the Ice, Cloud, and Elevation Satellite (ICESat). This study tested the use of GLAS data, from the L3e and L3g campaigns, to estimate total canopy height. GLAS footprint locations were sampled for reference data. The GLAS-derived and field-derived canopy heights portrayed good correlation (R
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A global forest canopy height map from the moderate resolution imaging spectroradiometer and the geoscience laser altimeter system [J]. |
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Technologies of forest resources dynamic monito ring . |
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基于MODIS影像大尺度森林资源信息提取方法研究 [J].https://doi.org/10.14067/j.cnki.1673-923x.2015.11.005 URL [本文引用: 1] 摘要
森林类型的识别对于掌握森林生态系统和自然环境变化具有重要意义。针对单一时相遥感数据提取森林植被类型信息方法的局限性，以中国东北三省为研究区，探讨了基于多时相MODIS遥感数据，实现主要森林类型识别的方法。将东三省的森林植被划分为非林地、针叶林、阔叶林、针阔混交林、灌木林5种类型，通过分析不同森林类型一年内生长差异，选取多时相NDVI第10期、NDIV第23期、EVI第10期、LAI第20期特征数据，建立了非林地、针叶林、阔叶林、针阔混交林、灌木林的决策树模型，实现了森林类型信息的识别，得出了东三省的森林覆盖率42.39%，植被类型分类总体精度为86.7%，与第八次全国森林资源清查的东三省结果对比，森林覆盖率提取精度高达95.6%。说明应用多时相的MODIS遥感影像可以实现大尺度森林资源信息的快速提取，在大范围的植被类型调查与监测方法具有较大的应用价值。
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基于PolInSAR森林高度反演研究 [J].Forest height inversion based on Polarimetric Interferometry SAR . |
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SAR残余相位误差对森林高度反演影响的全链路模拟与分析 [J].
利用合成孔径雷达(SAR)遥感数据可以有效地估测平均树高、生物量、蓄积量等森林生物学参数。但是遥感数据精度易受SAR系统不确定性因素的影响,造成森林参数反演精度降低甚至异常。遥感系统的全链路模拟可以将遥感过程的各类影响因素解耦,获取大量具有指定参数特征的遥感数据,有利于对不确定性因素单独或联合分析。建立了SAR三维森林场景全链路模拟模型,基于E-SAR样地参数及数据验证了模型的有效性,并以森林高度反演这一典型的林业应用为对象,定量分析了运动补偿残余相位误差这一典型的SAR系统不确定性因素对反演精度的影响程度,得到了残余相位误差与高度反演RMSE测量结果之间的关系曲线。
Simulation and analysis of SAR residual phase error on forest height inversion .
利用合成孔径雷达(SAR)遥感数据可以有效地估测平均树高、生物量、蓄积量等森林生物学参数。但是遥感数据精度易受SAR系统不确定性因素的影响,造成森林参数反演精度降低甚至异常。遥感系统的全链路模拟可以将遥感过程的各类影响因素解耦,获取大量具有指定参数特征的遥感数据,有利于对不确定性因素单独或联合分析。建立了SAR三维森林场景全链路模拟模型,基于E-SAR样地参数及数据验证了模型的有效性,并以森林高度反演这一典型的林业应用为对象,定量分析了运动补偿残余相位误差这一典型的SAR系统不确定性因素对反演精度的影响程度,得到了残余相位误差与高度反演RMSE测量结果之间的关系曲线。
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Based on MODIS image large-scale forest resources information extraction method .https://doi.org/10.14067/j.cnki.1673-923x.2015.11.005 URL [本文引用: 1] 摘要
森林类型的识别对于掌握森林生态系统和自然环境变化具有重要意义。针对单一时相遥感数据提取森林植被类型信息方法的局限性，以中国东北三省为研究区，探讨了基于多时相MODIS遥感数据，实现主要森林类型识别的方法。将东三省的森林植被划分为非林地、针叶林、阔叶林、针阔混交林、灌木林5种类型，通过分析不同森林类型一年内生长差异，选取多时相NDVI第10期、NDIV第23期、EVI第10期、LAI第20期特征数据，建立了非林地、针叶林、阔叶林、针阔混交林、灌木林的决策树模型，实现了森林类型信息的识别，得出了东三省的森林覆盖率42.39%，植被类型分类总体精度为86.7%，与第八次全国森林资源清查的东三省结果对比，森林覆盖率提取精度高达95.6%。说明应用多时相的MODIS遥感影像可以实现大尺度森林资源信息的快速提取，在大范围的植被类型调查与监测方法具有较大的应用价值。
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激光雷达在森林生态系统监测模拟中的应用现状与展望 [J].https://doi.org/10.1360/972013-592 Magsci [本文引用: 5] 摘要
<p>激光雷达是一种新兴的主动遥感技术，能够在多重时空尺度上获取森林生态系统高分辨率的三维地形、植被结构参数. 其对森林生态系统变化的精确、高效监测和模拟在认识这些变化如何影响陆地生态系统碳循环、全球气候变化，并促进生物多样性保护方面将发挥重要作用. 本文拟对激光雷达技术的概念和发展应用简史作一介绍，通过分析其在数字地形产品生成、森林生态参数提取反演应用中的主流算法和优势，继而阐明其推广应用所面临的挑战，最后指出未来激光雷达技术在生态学应用中可能的研究热点. 本文认为，构建集太空、天空、地面多源传感器于一体的数字生态系统是未来生态系统观测网络发展的必然趋势，而激光雷达技术能够在数字生态系统建设过程中搭建可靠的数据支撑体系，最终有助于决策部门调控、优化人与环境关系，实现二者和谐共存.</p>
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On scattering model decomposition with Pol-In SAR data [J].
This paper presents scattering model decomposition technique with Pol-InSAR data sets. The target model decomposition based on the scattering mechanisms corresponding to surface, double, and volume scattering, is one of the powerful tools to analyze and classify the ground surface conditions with fully polarimetric SAR data. However, we sometimes meet difficulty that the power of the decomposed component(s) becomes negative. This is caused by assumptions in the decomposition technique. The number of observables is limited in the fully polarimetric SAR data, therefore some assumptions are necessary. However, when an interferometric pair of fully polarimetric SAR data is available, additional observables can be obtained. These new observables will be available to resolve the difficulty of negative power in the conventional decomposition technique. In this paper, we consider the scattering model decomposition technique with Pol-InSAR data, and propose some modifications for the decomposition.
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Perspectives and prospects of LiDAR in forest ecosystem monitoring and modeling .https://doi.org/10.1360/972013-592 Magsci [本文引用: 5] 摘要
<p>激光雷达是一种新兴的主动遥感技术，能够在多重时空尺度上获取森林生态系统高分辨率的三维地形、植被结构参数. 其对森林生态系统变化的精确、高效监测和模拟在认识这些变化如何影响陆地生态系统碳循环、全球气候变化，并促进生物多样性保护方面将发挥重要作用. 本文拟对激光雷达技术的概念和发展应用简史作一介绍，通过分析其在数字地形产品生成、森林生态参数提取反演应用中的主流算法和优势，继而阐明其推广应用所面临的挑战，最后指出未来激光雷达技术在生态学应用中可能的研究热点. 本文认为，构建集太空、天空、地面多源传感器于一体的数字生态系统是未来生态系统观测网络发展的必然趋势，而激光雷达技术能够在数字生态系统建设过程中搭建可靠的数据支撑体系，最终有助于决策部门调控、优化人与环境关系，实现二者和谐共存.</p>
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Ramet population dynamics and net aerial primary productivity of spartina alterniflora [J].https://doi.org/10.2307/2265677 URL [本文引用: 1] 摘要
Ramet dynamics and net aerial primary productivity (NAPP) were studied in samples of Spartina alterniflora (smooth cordgrass) at Sapelo Island, Georgia. Three populations were compared: tall, short, and short with nitrogen fertilization in spring (short/N). Tall and short S. alterniflora populations had different demographic characteristics. The short population had a shorter leaf longevity (49 vs. 72 d) and a higher leaf turnover than the tall population, which may be due to high salinity and nitrogen limitation in the high marsh. Although the average ramet longevities of tall and short populations were similar (231 and 204 d, respectively), cohorts of the tall population that emerged early in the growing season had a significantly longer average life-span than those of the short population, probably because they had more support from belowground reserves that led to a higher initial survival rate. Leaf number, leaf area, shoot density, and biomass production of the short population were greatly increased by spring nitrogen fertilization, but the longevity of leaves and ramets was little affected. Using the demographic data and phytometric equations (nondestructive method), new growth was found throughout the year in S. alterniflora populations at Sapelo Island. The average dry mass NAPP was estimated to be 1105, 2244, and 1520 g.m-2.yr-1for the short, short/N, and tall populations, respectively. Because of its higher leaf turnover, the short population had a higher leaf to stem production ratio than the tall population. NAPP estimates obtained by nondestructive methods usually lie between overestimates and underestimates from harvest methods, indicating that nondestructive methods give accurate estimates of NAPP for salt marshes. Using the highest spring aerial production rates, the upper limits of annual dry mass total production of S. alterniflora at Sapelo Island were calculated as 2555 g/m2for the short population and 4526 g/m2for the tall population. These limits are lower than many previous estimates of annual total primary production for S. alterniflora.
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Models and methods of extracting forest structure information by Polarimetric SAR interferometry . |
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利用无人机高分辨率影像进行树木高度提取 [J].https://doi.org/10.13332/j.1000--1522.20160428 URL [本文引用: 1] 摘要
无人机遥感技术在树木参数获取中具有重要作用。为探讨利用无人机高分辨率影像提取树高的可行性,本文选择邱集煤矿矿区森林公园为研究区,采用Pix4D软件对无人机采集的高分辨率影像进行处理,生成研究区正射影像和三维点云;利用最大类间方差法将三维点云分割为树木点云及树下地面点云两部分,由此提取树木顶端高度和地面平均高度,并将地面平均高度视为树木根部的高度,得到树木高度。研究表明：最大类间方差法能够准确分割树木点云和地面点云;利用无人机高分辨率影像进行树高提取是可行的,树木高度测量绝对误差小于80cm、相对误差绝对值最大为16.2%、标准误差为36.3 cm;同时,树冠的形状会对树高测量造成影响,阔卵形树冠的法国梧桐和圆锥形树冠的圆柏高度标准误差分别为29.2和50.9 cm,两者树高测量值与真实值决定系数分别为0.992 0和0.889 4,阔卵形树冠的法国梧桐测高精度明显高于圆锥形树冠的圆柏测高精度。
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Consolidating new paradigms in large-scale monitoring and assessment of forest ecosystems [J].https://doi.org/10.1016/j.envres.2015.10.017 URL PMID: 26514075 [本文引用: 1] 摘要
Forests provide a wide range of ecosystem services from which people benefit, and upon which all life depends. However, any rational decision related to the maintenance and enhancement of the multiple functions provided by the forests needs to be based on objective, reliable information. As such, forest monitoring and assessment are rapidly evolving as new information needs arise or new techniques and tools become available. Global change issues and utilities from ecosystem management are distinctively to be considered, so that forest inventory and mapping are broadening their scope towards multipurpose resources surveys. Recent changes in forest management perspective have promoted the consideration of forests as complex adaptive systems, thereby highlighting the need to account that such approaches actually work: forest monitoring and assessment are then expected to address and fully incorporate this perspective at global scale, seeking to support planning and management decisions that are evidence-based. This contribution provides selected considerations on the above mentioned issues, in the form of a commented discussion with examples from the literature produced in the last decade.
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基于遥感技术的森林健康研究综述 [J].https://doi.org/10.5846/stxb201112011838 URL Magsci [本文引用: 3] 摘要
遥感技术可以有效完成复杂时空尺度海量信息的收集处理,其与森林健康研究的交叉、融合大大提高了复杂时空尺度上森林健康研究的表达能力。目前,森林健康遥感研究正处于各学科交叉、融合、调整,由静态向动态、单一向复杂、零散向系统转变的关键发展时期,但缺乏对森林健康问题的全面考量、逻辑安排和系统的顶层设计。在把握森林健康活力、组织结构和恢复力核心理念的基础上,从森林资源调查、森林生态功能评估、森林健康风险控制和森林植被参数提取四个方面构建和丰富基于遥感技术森林健康研究体系,对国内外森林健康遥感研究进行综述。通过对以上研究内容的总结分析,明确基于遥感技术的森林健康研究各领域的研究进展,及其在理论、技术和应用方面的不足。分析认为:(1) 未来应加强森林生态和遥感技术重大基础理论研究,以明确森林结构、过程、功能与遥感数据之间的耦合关系;(2) 发展完善新型遥感技术、遥感数据解译算法与软件工具,提高遥感数据的精确度、利用率和利用效率;(3) 提升森林健康遥感研究成果的科技转化水平,推进快速分析评价与辅助决策功能研究,指导相关森林健康经营活动和科学研究的开展,以及林业政策的制定。
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Tree height extraction using high-resolution imagery acquired from an unmanned aerial vehicle (UAV) .https://doi.org/10.13332/j.1000--1522.20160428 URL [本文引用: 1] 摘要
无人机遥感技术在树木参数获取中具有重要作用。为探讨利用无人机高分辨率影像提取树高的可行性,本文选择邱集煤矿矿区森林公园为研究区,采用Pix4D软件对无人机采集的高分辨率影像进行处理,生成研究区正射影像和三维点云;利用最大类间方差法将三维点云分割为树木点云及树下地面点云两部分,由此提取树木顶端高度和地面平均高度,并将地面平均高度视为树木根部的高度,得到树木高度。研究表明：最大类间方差法能够准确分割树木点云和地面点云;利用无人机高分辨率影像进行树高提取是可行的,树木高度测量绝对误差小于80cm、相对误差绝对值最大为16.2%、标准误差为36.3 cm;同时,树冠的形状会对树高测量造成影响,阔卵形树冠的法国梧桐和圆锥形树冠的圆柏高度标准误差分别为29.2和50.9 cm,两者树高测量值与真实值决定系数分别为0.992 0和0.889 4,阔卵形树冠的法国梧桐测高精度明显高于圆锥形树冠的圆柏测高精度。
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Tree height quantification using very high resolution imagery acquired from an unmanned aerial vehicle (UAV) and automatic 3D photo-reconstruction methods [J].https://doi.org/10.1016/j.eja.2014.01.004 URL [本文引用: 1] |
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Forest health studies based on remote sensing: a review .https://doi.org/10.5846/stxb201112011838 URL Magsci [本文引用: 3] 摘要
遥感技术可以有效完成复杂时空尺度海量信息的收集处理,其与森林健康研究的交叉、融合大大提高了复杂时空尺度上森林健康研究的表达能力。目前,森林健康遥感研究正处于各学科交叉、融合、调整,由静态向动态、单一向复杂、零散向系统转变的关键发展时期,但缺乏对森林健康问题的全面考量、逻辑安排和系统的顶层设计。在把握森林健康活力、组织结构和恢复力核心理念的基础上,从森林资源调查、森林生态功能评估、森林健康风险控制和森林植被参数提取四个方面构建和丰富基于遥感技术森林健康研究体系,对国内外森林健康遥感研究进行综述。通过对以上研究内容的总结分析,明确基于遥感技术的森林健康研究各领域的研究进展,及其在理论、技术和应用方面的不足。分析认为:(1) 未来应加强森林生态和遥感技术重大基础理论研究,以明确森林结构、过程、功能与遥感数据之间的耦合关系;(2) 发展完善新型遥感技术、遥感数据解译算法与软件工具,提高遥感数据的精确度、利用率和利用效率;(3) 提升森林健康遥感研究成果的科技转化水平,推进快速分析评价与辅助决策功能研究,指导相关森林健康经营活动和科学研究的开展,以及林业政策的制定。
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Synergistic use of Landsat TM and SPOT5 imagery for object-based forest classification [J].https://doi.org/10.1117/1.JRS.8.083550 URL [本文引用: 1] 摘要
This study evaluated the synergistic use of Landsat5 TM and SPOT5 images for improving forest classification using an object-based image analysis approach. Three image segmentation schemes were examined: (1) segmentation based on both SPOT5 and Landsat5 TM; (2) segmentation based solely on SPOT5; and (3) segmentation based solely on Landsat5 TM. The optimal scale parameters based on TM/SPOT5 and SPOT5 were determined by measuring the topological similarity between segmented objects and reference objects at 10 different scales. Mean and standard deviation of the pixels within each object in each input layer were the classification metrics. Nearest neighbor classifier was performed for the three segmentation schemes. The results showed that (1) the optimal scales of TM/SPOT5, SPOT5, and TM were 70, 100, and 0.8, respectively and (2) classification results with medium spatial resolution images were not desirable, with overall accuracy of only 72.35%, while synergistic use of Landsat5 TM and SPOT5 greatly improved forest classification accuracy, with overall accuracy of 82.94%.
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Defining leaf area index for non-flat leaves [J].https://doi.org/10.1111/j.1365-3040.1992.tb00992.x URL [本文引用: 1] 摘要
To eliminate the confusion in the definition of leaf area index ( L ) for non-flat leaves, the projection coefficients of several objects including spheres, cylinders, hemicircular cylinders, and triangular and square bars are investigated through mathematical derivation and numerical calculation for a range of ellipsoidal angular distributions. It is shown that the projection coefficient calculated based on half the total intercepting area is close to a constant of 0.5 when the inclination angle of the objects is randomly (spherically) distributed, whereas the calculated results based on the object's largest projected area are strongly dependent on the shape of the objects. Therefore, it is suggested that the leaf area index of non-flat leaves be defined as half the total intercepting area per unit ground surface area and that the definition of L based on the projected leaf area be abandoned.
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| [71] |
中国区域植被叶面积指数时空分布机理模型模拟与遥感反演比较 [J].
叶面积指数是表征植被冠层特征的重要参数，同时也是决定生态系统净初级生产力的重要因子，它对全球变化和生态系统碳循环研究具有重要意义。目前大范围的叶面积指数只能通过遥感反演和机理模型模拟获得，而通过这两种方法获取的叶面积指数都存在一定的不确定性。利用大气-植被相互作用模型（AVIM2）在0.1°×0.1°经纬度网格上模拟产生了中国区域叶面积指数并与两套使用不同遥感反演方法生成的叶面积指数在空间分布和季节变化特征方面进行了比较。通过比较说明中国区域植被叶面积指数分布主要受水分条件限制，整体呈现东南部高西北部低的趋势。中国区域植被生长的季节变化受季风影响显著，与气温及地表太阳辐射的季节变化趋势相一致。中国区域叶面积指数整体呈现夏季高、春秋季次之而冬季低的趋势。
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| [16] |
基于纹理信息CART决策树的林芝县森林植被面向对象分类 [J].https://doi.org/10.11873/j.issn.1004-0323.2017.2.0386 URL [本文引用: 1] 摘要
以西藏自治区林芝县的Landsat-8影像、地形图为信息源,结合样地调查数据及森林资源二类调查数据,研究基于纹理信息的CART决策树的面向对象分类对研究区内的森林地物类别进行提取,分类的总体精度和Kappa系数分别为82.53%和0.768,相较于不利用纹理信息的决策树分类和基于最大似然分类法的研究区地物类别的提取总体精度均高近10%,Kappa系数分别高0.12和0.111.结果表明:基于纹理信息的CART决策树面向对象分类方法对研究区Landsat-8影像进行植被类型提取,分类结果较好,能够满足研究要求.
Object-oriented forest classification of Linzhi County based on CART decision tree with texture information .https://doi.org/10.11873/j.issn.1004-0323.2017.2.0386 URL [本文引用: 1] 摘要
以西藏自治区林芝县的Landsat-8影像、地形图为信息源,结合样地调查数据及森林资源二类调查数据,研究基于纹理信息的CART决策树的面向对象分类对研究区内的森林地物类别进行提取,分类的总体精度和Kappa系数分别为82.53%和0.768,相较于不利用纹理信息的决策树分类和基于最大似然分类法的研究区地物类别的提取总体精度均高近10%,Kappa系数分别高0.12和0.111.结果表明:基于纹理信息的CART决策树面向对象分类方法对研究区Landsat-8影像进行植被类型提取,分类结果较好,能够满足研究要求.
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| [71] |
The spatial-temporal distribution of leaf area index in China: a comparisonbetween ecosystem modeling and remote sensing reversion .
叶面积指数是表征植被冠层特征的重要参数，同时也是决定生态系统净初级生产力的重要因子，它对全球变化和生态系统碳循环研究具有重要意义。目前大范围的叶面积指数只能通过遥感反演和机理模型模拟获得，而通过这两种方法获取的叶面积指数都存在一定的不确定性。利用大气-植被相互作用模型（AVIM2）在0.1°×0.1°经纬度网格上模拟产生了中国区域叶面积指数并与两套使用不同遥感反演方法生成的叶面积指数在空间分布和季节变化特征方面进行了比较。通过比较说明中国区域植被叶面积指数分布主要受水分条件限制，整体呈现东南部高西北部低的趋势。中国区域植被生长的季节变化受季风影响显著，与气温及地表太阳辐射的季节变化趋势相一致。中国区域叶面积指数整体呈现夏季高、春秋季次之而冬季低的趋势。
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Mapping biomass and stress in the Sierra Nevada using lidar and hyperspectral data fusion [J].https://doi.org/10.1016/j.rse.2010.08.027 URL [本文引用: 1] 摘要
78 We combined lidar and hyperspectral data to map aboveground biomass in the Sierra Nevada. 78 Spectral metrics added little value to structural metrics in estimating biomass. 78 Species stratification showed spatial improvements for hardwoods and pines. 78 Lidar is more suited for biomass estimation. 78 Hyperspectral data adds value via species classification and canopy condition. 78 Fusion of the two is powerful for ecological and habitat studies.
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森林冠层地面叶面积指数光学测量方法研究进展 [J].
<p>作为表征植被冠层结构的核心参数之一，叶面积指数（LAI）控制着植被冠层的多种生物物理和生理过程，如光合、呼吸、蒸腾、碳循环、降水截获、能量交换等.本文首先阐述了森林冠层地面LAI光学测量方法的理论基础和数学模型；其后介绍了目前主流光学测量方法的测量原理及其优缺点；归纳了LAI光学测量方法的主要误差来源（聚集效应、非光合作用组分、观测条件和地形效应），并分析总结了聚集效应、非光合作用组分和地形效应的定量评估现状；最后展望了森林冠层地面LAI光学测量方法的未来发展方向.</p>
Optical methods for in situ measuring leaf area index of forest canopy: A review .
<p>作为表征植被冠层结构的核心参数之一，叶面积指数（LAI）控制着植被冠层的多种生物物理和生理过程，如光合、呼吸、蒸腾、碳循环、降水截获、能量交换等.本文首先阐述了森林冠层地面LAI光学测量方法的理论基础和数学模型；其后介绍了目前主流光学测量方法的测量原理及其优缺点；归纳了LAI光学测量方法的主要误差来源（聚集效应、非光合作用组分、观测条件和地形效应），并分析总结了聚集效应、非光合作用组分和地形效应的定量评估现状；最后展望了森林冠层地面LAI光学测量方法的未来发展方向.</p>
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| [18] |
基于高光谱遥感技术的森林树种识别研究进展 [J].Development of hyperspectral remote sensing application in forest species identification . |
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Optical remote sensing of forest leaf area index and biomass [J].https://doi.org/10.1177/0309133312471367 URL [本文引用: 1] 摘要
Forests are the most complex terrestrial ecosystem on Earth's land surface, providing vital goods and services upon which the welfare of humanity depends. The quantification of leaves and biomass in forests is critical for understanding the ecological role of forests in the terrestrial ecosystem. Great effort has been dedicated to the mapping of leaf area and biomass using remotely sensed data. This review focuses on the use of optical remote sensing in mapping leaf area index (LAI) and aboveground biomass for forests. Significant progress has been made in mapping LAI in the past few decades. Mapping of LAI started with location-specific empirical approaches and evolved to semi-empirical and biophysical approaches, which can be applied globally. Although there are some biases in the current LAI products, it can be expected that better-quality LAI products will be delivered in the future. At present, mapping biomass remains predominantly empirical because there is no direct physical relationship between reflected energy in visible, near or mid infrared wavelengths and biomass. Mapping biomass relies on the explicit or implicit mapping of forest structural parameters that are related to biomass allometrically. Although optical images have been successfully used in mapping biomass in low biomass areas, it remains a challenge to map biomass in forested areas with high biomass density due to signal saturation.
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Comparison of Sentinel-2 and Landsat 8 in the estimation of boreal forest canopy cover and leaf area index [J].https://doi.org/10.1016/j.rse.2017.03.021 URL [本文引用: 1] |
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Review of studies on tree species classification from remotely sensed data [J].https://doi.org/10.1016/j.rse.2016.08.013 URL [本文引用: 2] 摘要
61A review of remote-sensing based tree species classification is provided.61Descriptive statistics on publication year, biomes, species numbers & sensor types61Species related traits, classification methods and research gaps are discussed.61We identified a lack of studies working with hypothesis driven questions.61We identified a lack of studies focusing on larger geographic extents.
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面向对象的ALOS高分辨率遥感影像亚热带森林遥感分类研究 [J]. |
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基于随机森林模型的林地叶面积指数遥感估算 [J].Estimation of forest leaf area index based on random forest model and remote sensing data . |
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Object-oriented classification of subtropical forest based on ALOS high resolution remote rensing image . |
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森林覆盖变化遥感监测方法研究进展 [J]. |
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帽儿山地区森林冠层叶面积指数的地面观测与遥感反演 [J].
<p>叶面积指数 (leaf area index, LAI) 是陆地生态系统最重要的结构参数之一，遥感和基于冠层孔隙率模型的光学仪器观测是快速获取LAI的有效方法，但由于植被叶片的聚集效应，这些方法通常只能获取有效叶面积指数 (effective LAI, LAIe).本文以东北林业大学帽儿山实验林场为研究区，利用LAI2000观测森林冠层LAIe，并结合TRAC观测的叶片聚集度系数估算了森林冠层LAI，并通过分析基于Landsat5-TM数据计算的不同植被指数与LAIe之间的关系，建立了该区森林LAI遥感估算模型.结果表明：研究区阔叶林的LAI和LAIe基本相当，而针叶林的LAI比LAIe大27%；减化比值植被指数 (reduced simple ratio，RSR) 与该区LAIe的相关性最好(R<sup>2</sup>=0.763，n=23)，最适合该区LAI的遥感提取.当海拔<400 m时，LAI随海拔高度的上升而快速增大；当海拔在400～750 m时，LAI随海拔高度的上升缓慢增大；当海拔>750 m时，LAI呈下降趋势.研究区森林冠层LAI与森林地上生物量存在显著的正相关关系.</p>
Forest canopy leaf area index in Maoershan Mountain: Ground measurement and remote sensing retrieval .
<p>叶面积指数 (leaf area index, LAI) 是陆地生态系统最重要的结构参数之一，遥感和基于冠层孔隙率模型的光学仪器观测是快速获取LAI的有效方法，但由于植被叶片的聚集效应，这些方法通常只能获取有效叶面积指数 (effective LAI, LAIe).本文以东北林业大学帽儿山实验林场为研究区，利用LAI2000观测森林冠层LAIe，并结合TRAC观测的叶片聚集度系数估算了森林冠层LAI，并通过分析基于Landsat5-TM数据计算的不同植被指数与LAIe之间的关系，建立了该区森林LAI遥感估算模型.结果表明：研究区阔叶林的LAI和LAIe基本相当，而针叶林的LAI比LAIe大27%；减化比值植被指数 (reduced simple ratio，RSR) 与该区LAIe的相关性最好(R<sup>2</sup>=0.763，n=23)，最适合该区LAI的遥感提取.当海拔<400 m时，LAI随海拔高度的上升而快速增大；当海拔在400～750 m时，LAI随海拔高度的上升缓慢增大；当海拔>750 m时，LAI呈下降趋势.研究区森林冠层LAI与森林地上生物量存在显著的正相关关系.</p>
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Progress of study on forest cover change detection by using remote sensing technique . |
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Object based image analysis for remote sensing [J].https://doi.org/10.1016/j.isprsjprs.2009.06.004 URL [本文引用: 1] 摘要
Remote sensing imagery needs to be converted into tangible information which can be utilised in conjunction with other data sets, often within widely used Geographic Information Systems (GIS). As long as pixel sizes remained typically coarser than, or at the best, similar in size to the objects of interest, emphasis was placed on per-pixel analysis, or even sub-pixel analysis for this conversion, but with increasing spatial resolutions alternative paths have been followed, aimed at deriving objects that are made up of several pixels. This paper gives an overview of the development of object based methods, which aim to delineate readily usable objects from imagery while at the same time combining image processing and GIS functionalities in order to utilize spectral and contextual information in an integrative way. The most common approach used for building objects is image segmentation, which dates back to the 1970s. Around the year 2000 GIS and image processing started to grow together rapidly through object based image analysis (OBIA - or GEOBIA for geospatial object based image analysis). In contrast to typical Landsat resolutions, high resolution images support several scales within their images. Through a comprehensive literature review several thousand abstracts have been screened, and more than 820 OBIA-related articles comprising 145 journal papers, 84 book chapters and nearly 600 conference papers, are analysed in detail. It becomes evident that the first years of the OBIA/GEOBIA developments were characterised by the dominance of rey literature, but that the number of peer-reviewed journal articles has increased sharply over the last four to five years. The pixel paradigm is beginning to show cracks and the OBIA methods are making considerable progress towards a spatially explicit information extraction workflow, such as is required for spatial planning as well as for many monitoring programmes.
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森林冠层叶面积指数遥感反演——以小兴安岭五营林区为例 [J].
<p>以中国东北小兴安岭五营林区为研究区，基于MODIS BRDF遥感模型参数产品数据，首先利用4-Scale模型建立查找表计算像元尺度上各组分比例，估算研究区森林乔木冠层反射率，然后利用冠层反射率数据，获取研究区3种常用森林冠层植被指数，最后基于植被指数与实测叶面积指数构建研究区冠层叶面积指数反演模型，并选取最优模型实现研究区森林冠层叶面积指数反演。结果表明：研究区冠层LAI遥感反演模型中，基于比值植被指数SR（simple ratio, SR）构建的二次多项式反演模型精度最高，且反演精度比未考虑背景反射影响的SR反演模型精度有较大幅度提高，模型决定系数由0.38提高至0.54；反演获取的研究区冠层LAI在2.38～12.67，平均值6.52，LAI值在阔叶林区域相对较高。</p>
Retrieving forest canopy LAI from remote sensing data: A case study over Wuying forest in the Lesser Khingan .
<p>以中国东北小兴安岭五营林区为研究区，基于MODIS BRDF遥感模型参数产品数据，首先利用4-Scale模型建立查找表计算像元尺度上各组分比例，估算研究区森林乔木冠层反射率，然后利用冠层反射率数据，获取研究区3种常用森林冠层植被指数，最后基于植被指数与实测叶面积指数构建研究区冠层叶面积指数反演模型，并选取最优模型实现研究区森林冠层叶面积指数反演。结果表明：研究区冠层LAI遥感反演模型中，基于比值植被指数SR（simple ratio, SR）构建的二次多项式反演模型精度最高，且反演精度比未考虑背景反射影响的SR反演模型精度有较大幅度提高，模型决定系数由0.38提高至0.54；反演获取的研究区冠层LAI在2.38～12.67，平均值6.52，LAI值在阔叶林区域相对较高。</p>
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NDVI-based lacunarity texture for improving identification of Torreya using object-oriented method [J].https://doi.org/10.1016/S1671-2927(11)60136-3 URL [本文引用: 1] |
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基于C5.0决策树和时序HJ-1A/B CCD数据的神农架林区植被分类 [J].https://doi.org/10.11870/cjlyzyyhj201607008 Magsci [本文引用: 1] 摘要
我国神农架林区海拔高、气候复杂，森林类型多样，结构破碎，森林遥感分类难度较大。将2013年时间序列HJ-1A/B CCD遥感影像作为数据源，计算出植被指数（NDVI、DVI、RVI）和主成分第一分量（PC1），使用DEM数据生成地形因子（高程、坡度、坡向），构建植被分类时序因子集。运用C5.0决策树分类法将神农架林区植被细分为七类：针叶林；针阔混交林；落叶阔叶林；常绿和落叶阔叶混交林；常绿阔叶林；灌丛和草甸。结果表明：该方法的总体精度为72.7%，Kappa系数为0.67；在6～8月，针叶林、草甸和灌丛的植被指数明显低于常绿阔叶林、常绿和落叶阔叶混交林、落叶阔叶林和针阔混交林，对分类的贡献较大，称为植被分类的“窗口期”。PC1、NDVI和高程因子对神农架林地的区分度较高，而坡度、坡向和RVI因子对分类帮助不大。作为一种智能分类方法，C5.0决策树分类方法应用于30m分辨率的时间序列HJ-1A/B CCD数据，能够将地貌复杂的神农架林区植被分为七类，提高了类别精度，具有更高的应用价值。
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Retrieval of vertical LAI profiles over tropical rain forests using waveform lidar at La Selva, Costa Rica [J].https://doi.org/10.1016/j.rse.2012.05.005 URL [本文引用: 1] |
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基于ETM和图像融合的优势植被冠层叶面积指数和消光系数的遥感反演 [J]. |
| [24] |
Study on vegetation classification in Shennongjia forest district based on C5.0 decision tree and HJ-1 A/B data .https://doi.org/10.11870/cjlyzyyhj201607008 Magsci [本文引用: 1] 摘要
我国神农架林区海拔高、气候复杂，森林类型多样，结构破碎，森林遥感分类难度较大。将2013年时间序列HJ-1A/B CCD遥感影像作为数据源，计算出植被指数（NDVI、DVI、RVI）和主成分第一分量（PC1），使用DEM数据生成地形因子（高程、坡度、坡向），构建植被分类时序因子集。运用C5.0决策树分类法将神农架林区植被细分为七类：针叶林；针阔混交林；落叶阔叶林；常绿和落叶阔叶混交林；常绿阔叶林；灌丛和草甸。结果表明：该方法的总体精度为72.7%，Kappa系数为0.67；在6～8月，针叶林、草甸和灌丛的植被指数明显低于常绿阔叶林、常绿和落叶阔叶混交林、落叶阔叶林和针阔混交林，对分类的贡献较大，称为植被分类的“窗口期”。PC1、NDVI和高程因子对神农架林地的区分度较高，而坡度、坡向和RVI因子对分类帮助不大。作为一种智能分类方法，C5.0决策树分类方法应用于30m分辨率的时间序列HJ-1A/B CCD数据，能够将地貌复杂的神农架林区植被分为七类，提高了类别精度，具有更高的应用价值。
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森林类型遥感分类研究进展 [J].https://doi.org/10.3969/j.issn.2095-1914.2010.06.019 URL [本文引用: 2] 摘要
从光学遥感和微波遥感2方面分析森林类型遥感分类的理论基础,总结国际和国内关于森林类型识别及提取技术,以及森林物理参数估测等方面的相关研究和探讨,归纳目前常用的森林类型遥感分类方法,并介绍其相关研究成果,还从3方面阐述森林类型遥感分类技术的发展趋势。
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Retrieving leaf area index and extinction coefficient of dominated vegetation canopy cover in Meijiang Watershed of China using image-fusion and Landsat ETM data . |
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叶面积指数遥感反演研究进展与展望 [J].https://doi.org/10.3724/SP.J.1047.2013.00734 Magsci [本文引用: 3] 摘要
叶面积指数表征叶片的疏密程度和冠层结构特征,体现植被光合、呼吸和蒸腾作用等生物物理过程的能力,是描述土壤-植被-大气之间物质和能量交换的关键参数。目前多种卫星传感器观测生成了多个区域和全球的叶面积指数标准产品。本文综述了基于光学遥感数据的叶面积指数反演进展:首先,介绍了叶面积指数的定义和在生态系统模拟中的作用;然后,阐述了基于光学遥感反演叶面积指数的基本原理;在此基础上,论述了基于植被指数经验关系和基于物理模型的两种主要遥感反演算法,讨论了2种算法的优点和存在的问题,并总结了现有的主要全球数据产品及其特点,论述了产品检验的方法和需要注意的问题;最后,总结了当前叶面积指数反演中存在的问题,并展望了其发展趋势和研究方向。
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Research advances in forest type classification by remote sensing technology .https://doi.org/10.3969/j.issn.2095-1914.2010.06.019 URL [本文引用: 2] 摘要
从光学遥感和微波遥感2方面分析森林类型遥感分类的理论基础,总结国际和国内关于森林类型识别及提取技术,以及森林物理参数估测等方面的相关研究和探讨,归纳目前常用的森林类型遥感分类方法,并介绍其相关研究成果,还从3方面阐述森林类型遥感分类技术的发展趋势。
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基于阈值法的山区森林常绿、落叶特征遥感自动识别方法——以贡嘎山地区为例 [J].https://doi.org/10.5846/stxb201310112440 URL Magsci [本文引用: 1] 摘要
森林的常绿、落叶特征是土地覆被产品的重要属性.由于山区地形复杂,地表遥感辐射信号地形效应明显,导致山区森林常绿、落叶特征遥感自动识别一直是难点.提出了一种基于阈值法的山区森林常绿、落叶特征遥感自动识别简单实用方法.该方法利用多源、多时相遥感影像,选择归一化植被指数(NDVI)为指标,通过统计参考样本的NDVI在生长季和非生长季的差异,自动找出区分常绿、落叶特征的阈值,基于判别规则识别山区森林常绿、落叶特征.以贡嘎山地区为例,分别以多时相Landsat TM影像(简称TM)、多时相环境减灾卫星影像(简称HJ)为单源数据,多时相的HJ、TM组合影像为多源数据,验证该方法的有效性.实验结果表明,该方法能够有效识别山区森林常绿、落叶特征,总体精度达到93.87%,Kappa系数为0.87.该方法适用于山区大面积森林常绿、落叶特征遥感自动提取,已被成功应用于"生态十年"专项西南地区土地覆被数据的生产.
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Current status and perspectives of leaf area index retrieval from optical remote sensing data .https://doi.org/10.3724/SP.J.1047.2013.00734 Magsci [本文引用: 3] 摘要
叶面积指数表征叶片的疏密程度和冠层结构特征,体现植被光合、呼吸和蒸腾作用等生物物理过程的能力,是描述土壤-植被-大气之间物质和能量交换的关键参数。目前多种卫星传感器观测生成了多个区域和全球的叶面积指数标准产品。本文综述了基于光学遥感数据的叶面积指数反演进展:首先,介绍了叶面积指数的定义和在生态系统模拟中的作用;然后,阐述了基于光学遥感反演叶面积指数的基本原理;在此基础上,论述了基于植被指数经验关系和基于物理模型的两种主要遥感反演算法,讨论了2种算法的优点和存在的问题,并总结了现有的主要全球数据产品及其特点,论述了产品检验的方法和需要注意的问题;最后,总结了当前叶面积指数反演中存在的问题,并展望了其发展趋势和研究方向。
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不同林分郁闭度与遥感数据的相关性 [J].https://doi.org/10.5846/stxb201306101626 Magsci [本文引用: 1] 摘要
林分郁闭度与遥感数据的相关性分析是郁闭度遥感估算的基础,郁闭度遥感是林业遥感的重要方向。以四川省石棉县为例,就不同林分探讨了其郁闭度与陆地资源卫星专题制图仪LANDSAT Thematic Mapper (TM, 包括其波段1至7,分别表示为TM1、TM2、TM3、TM4、TM5、TM6和TM7) 数据之间的相关性及其受地形校正的影响。建立了地形数据库和基于1994年调查数据的森林资源数据库;对1994年6月26日成像的LANDSAT TM数据进行了几何校正,并与森林资源数据库配准;分别利用Lambert Cosine Correction(LCC)模型和Sun Canopy Sensor(SCS)模型对TM数据进行地形校正,生成TM-LCC和TM-SCS数据;将TM、TM-LCC和TM-SCS各波段数据分别与森林资源数据叠加统计,得到各小班TM、TM-LCC和TM-SCS各波段数据的均值和标准差,并将其添入数据库中,选取标准差较小的小班共1194个作为样本。按优势树种将样本层化为8个林分层,分别计算其郁闭度与TM、TM-LCC和TM-SCS各波段数据间的相关系数,并分析其在不同林分不同波段上的差异及其受地形校正的影响。研究表明:铁杉、冷杉和云杉等林分郁闭度与TM部分波段数据的相关性在0.01的水平上均为显著;而桦木、栎类、桤木、软阔类和云南松等林分郁闭度与TM数据的相关性在0.05的水平上均不显著;TM的LCC校正提高了冷杉、铁杉和软阔等林分郁闭度与TM4和TM5的相关性,TM的LCC校正还提高了软阔类林分郁闭度与TM7的相关性,TM的SCS校正提高了冷杉林分郁闭度与TM4和TM5的相关性,且在0.01的水平上均为显著。TM 的LCC和SCS校正未能明显提高桦木、栎类、桤木、云南松和云杉等林分郁闭度与TM数据的相关性。该研究对林分郁闭度遥感具有一定的科学意义和应用价值。
Correlation analysis of canopy density with remote sensing data for different forest stand .https://doi.org/10.5846/stxb201306101626 Magsci [本文引用: 1] 摘要
林分郁闭度与遥感数据的相关性分析是郁闭度遥感估算的基础,郁闭度遥感是林业遥感的重要方向。以四川省石棉县为例,就不同林分探讨了其郁闭度与陆地资源卫星专题制图仪LANDSAT Thematic Mapper (TM, 包括其波段1至7,分别表示为TM1、TM2、TM3、TM4、TM5、TM6和TM7) 数据之间的相关性及其受地形校正的影响。建立了地形数据库和基于1994年调查数据的森林资源数据库;对1994年6月26日成像的LANDSAT TM数据进行了几何校正,并与森林资源数据库配准;分别利用Lambert Cosine Correction(LCC)模型和Sun Canopy Sensor(SCS)模型对TM数据进行地形校正,生成TM-LCC和TM-SCS数据;将TM、TM-LCC和TM-SCS各波段数据分别与森林资源数据叠加统计,得到各小班TM、TM-LCC和TM-SCS各波段数据的均值和标准差,并将其添入数据库中,选取标准差较小的小班共1194个作为样本。按优势树种将样本层化为8个林分层,分别计算其郁闭度与TM、TM-LCC和TM-SCS各波段数据间的相关系数,并分析其在不同林分不同波段上的差异及其受地形校正的影响。研究表明:铁杉、冷杉和云杉等林分郁闭度与TM部分波段数据的相关性在0.01的水平上均为显著;而桦木、栎类、桤木、软阔类和云南松等林分郁闭度与TM数据的相关性在0.05的水平上均不显著;TM的LCC校正提高了冷杉、铁杉和软阔等林分郁闭度与TM4和TM5的相关性,TM的LCC校正还提高了软阔类林分郁闭度与TM7的相关性,TM的SCS校正提高了冷杉林分郁闭度与TM4和TM5的相关性,且在0.01的水平上均为显著。TM 的LCC和SCS校正未能明显提高桦木、栎类、桤木、云南松和云杉等林分郁闭度与TM数据的相关性。该研究对林分郁闭度遥感具有一定的科学意义和应用价值。
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应用全天空照片估计林分透光孔隙度(郁闭度) [J].
Forest structure can not only influence the inhabited and biological factors in stands,but also determine the ecological functions of forest ecosystems.With the help of adjusting stand structure,reasonable forest management can come true.As one of the important indexes of forest structure,stand light transmission porosity or canopy closure can reflect the redistribution of light,water and other environmental factors entered the stand through forest canopy.It also plays a vital role on both forest management and many fine studies on forest ecology.Therefore,it is necessary to find a reasonable and accurate method to measure the light transmission porosity or canopy closure of a stand.This paper gave a detailed introduction on how to use hemispherical photograph to estimate canopy closure on the basis of the former related studies,and discussed in detail the selection of effective area of hemispherical photography,and some problems we have to pay attention to.
Estimation on optical porosity or canopy closure for a forest stand with hemispherical images .
Forest structure can not only influence the inhabited and biological factors in stands,but also determine the ecological functions of forest ecosystems.With the help of adjusting stand structure,reasonable forest management can come true.As one of the important indexes of forest structure,stand light transmission porosity or canopy closure can reflect the redistribution of light,water and other environmental factors entered the stand through forest canopy.It also plays a vital role on both forest management and many fine studies on forest ecology.Therefore,it is necessary to find a reasonable and accurate method to measure the light transmission porosity or canopy closure of a stand.This paper gave a detailed introduction on how to use hemispherical photograph to estimate canopy closure on the basis of the former related studies,and discussed in detail the selection of effective area of hemispherical photography,and some problems we have to pay attention to.
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联合星载ICESat-GLAS波形与多光谱Landsat-TM影像的森林郁闭度估测 [J].
<div style="line-height: 150%">森林郁闭度的空间分布是评价森林生产力和分解率的一个重要指标.本研究以吉林汪清林区为研究区,分别利用星载激光雷达ICESat-GLAS波形数据和多光谱遥感LandsatTM影像对该区的森林郁闭度进行估测,然后采用多元线性回归和BP神经网络两种方法对GLAS数据和TM数据进行联合,共同估测了森林郁闭度.结果表明: 单一遥感数据估测森林郁闭度时,GLAS数据的模型决定系数为0.762,TM数据的模型决定系数为0.598.将GLAS数据和TM数据联合后估测森林郁闭度时,多元线性回归模型的复决定系数为0.841,BP神经网络模型的仿真精度为0.851.表明ICESat-GLAS数据与Landsat-TM影像联合能够发挥多源遥感数据的优势,提高森林郁闭度的估测精度,并为后续的空间区域内森林郁闭度的连续制图提供可靠的方法.
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An practical method for automatically identifying the evergreen and deciduous characteristic of forests at mountainous areas: a case study in Mt.Gongga region .https://doi.org/10.5846/stxb201310112440 URL Magsci [本文引用: 1] 摘要
森林的常绿、落叶特征是土地覆被产品的重要属性.由于山区地形复杂,地表遥感辐射信号地形效应明显,导致山区森林常绿、落叶特征遥感自动识别一直是难点.提出了一种基于阈值法的山区森林常绿、落叶特征遥感自动识别简单实用方法.该方法利用多源、多时相遥感影像,选择归一化植被指数(NDVI)为指标,通过统计参考样本的NDVI在生长季和非生长季的差异,自动找出区分常绿、落叶特征的阈值,基于判别规则识别山区森林常绿、落叶特征.以贡嘎山地区为例,分别以多时相Landsat TM影像(简称TM)、多时相环境减灾卫星影像(简称HJ)为单源数据,多时相的HJ、TM组合影像为多源数据,验证该方法的有效性.实验结果表明,该方法能够有效识别山区森林常绿、落叶特征,总体精度达到93.87%,Kappa系数为0.87.该方法适用于山区大面积森林常绿、落叶特征遥感自动提取,已被成功应用于"生态十年"专项西南地区土地覆被数据的生产.
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Comparison of three different methods to select feature for discriminating forest cover types using SAR imagery [J].https://doi.org/10.1080/01431160050021312 URL [本文引用: 1] |
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Estimating forest canopy cover by combining spaceborne ICESat-GLAS waveforms and multispectral Landsat-TM images .
<div style="line-height: 150%">森林郁闭度的空间分布是评价森林生产力和分解率的一个重要指标.本研究以吉林汪清林区为研究区,分别利用星载激光雷达ICESat-GLAS波形数据和多光谱遥感LandsatTM影像对该区的森林郁闭度进行估测,然后采用多元线性回归和BP神经网络两种方法对GLAS数据和TM数据进行联合,共同估测了森林郁闭度.结果表明: 单一遥感数据估测森林郁闭度时,GLAS数据的模型决定系数为0.762,TM数据的模型决定系数为0.598.将GLAS数据和TM数据联合后估测森林郁闭度时,多元线性回归模型的复决定系数为0.841,BP神经网络模型的仿真精度为0.851.表明ICESat-GLAS数据与Landsat-TM影像联合能够发挥多源遥感数据的优势,提高森林郁闭度的估测精度,并为后续的空间区域内森林郁闭度的连续制图提供可靠的方法.
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基于叶面积指数的森林郁闭度遥感反演研究 [J]. |
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基于元胞自动机和BP神经网络算法的Landsat-TM遥感影像森林类型分类比较 [J].Comparison of Landsat-TM image forest type classification based on cellular automata and BP neural network algorithm . |
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Forest canopy density RS Inversion research based on LAI . |
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Tree species classification using hyperspectral imagery: A comparison of two classifiers [J].https://doi.org/10.3390/rs8060445 URL [本文引用: 1] 摘要
The identification of tree species can provide a useful and efficient tool for forest managers for planning and monitoring purposes. Hyperspectral data provide sufficient spectral information to classify individual tree species. Two non-parametric classifiers, support vector machines (SVM) and random forest (RF), have resulted in high accuracies in previous classification studies. This research takes a comparative classification approach to examine the SVM and RF classifiers in the complex and heterogeneous forests of Muir Woods National Monument and Kent Creek Canyon in Marin County, California. The influence of object- or pixel-based training samples and segmentation size on the object-oriented classification is also explored. To reduce the data dimensionality, a minimum noise fraction transform was applied to the mosaicked hyperspectral image, resulting in the selection of 27 bands for the final classification. Each classifier was also assessed individually to identify any advantage related to an increase in training sample size or an increase in object segmentation size. All classifications resulted in overall accuracies above 90%. No difference was found between classifiers when using object-based training samples. SVM outperformed RF when additional training samples were used. An increase in training samples was also found to improve the individual performance of the SVM classifier.
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Wavelet transform applied to EO-1hyperspectral data for forest LAI and crown closure mapping [J].https://doi.org/10.1016/j.rse.2004.03.006 URL [本文引用: 1] 摘要
A comparison of the performance of three feature extraction methods was made for mapping forest crown closure (CC) and leaf area index (LAI) with EO-1 Hyperion data. The methods are band selection (SB), principal component analysis (PCA) and wavelet transform (WT). Hyperion data were acquired on October 9, 2001. A total of 38 field measurements of CC and LAI were collected on August 10 11, 2001, at Blodgett Forest Research Station, University of California at Berkeley, USA. The analysis method consists of (1) conducting atmospheric correction with High Accuracy Atmospheric Correction for Hyperspectral Data (HATCH) to retrieve surface reflectance, (2) extracting features with the three methods: SB, PCA and WT, (3) establishing multivariate regression prediction models, (4) predicting and mapping pixel-based CC and LAI values, and (5) validating the CC and LAI mapped results with photo-interpreted CC and LAI values. The experimental results indicate that the energy features extracted by the WT method are the most effective for mapping forest CC and LAI (mapped accuracy (MA) for CC=84.90%, LAI MA=75.39%), followed by the PCA method (CC MA=77.42%, LAI MA=52.36%). The SB method performed the worst (CC MA=57.77%, LAI MA=50.87%).
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基于Hyperion 数据的香格里拉森林郁闭度遥感估测研究 [J]. |
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遥感变化检测技术在林业中的应用 [J].https://doi.org/10.13348/j.cnki.sjlyyj.2016.02.005 URL [本文引用: 1] 摘要
森林是人类生存和发展的基础。快速、准确地获取森林的变化信息,对于生态环境可持续发展具有重要意义。文中在总结当前变化检测技术流程及方法最新研究进展的基础上,重点介绍遥感变化检测技术在森林资源监测、森林灾害防控以及林业重点工程监管3个方面的应用情况,展望变化检测技术在林业上的应用前景。
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Estimating methods of forest canopy closure based on hyperion data of Shangri-La . |
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结合机载LiDAR和LANDSAT ETM+数据的温带森林郁闭度估测 [J].https://doi.org/10.17521/cjpe.2014.0366 URL [本文引用: 1] 摘要
森林郁闭度是森林资源调查中的一个重要因子,在森林生态系统管理中具有重要作用。研究如何有效地将激光雷达数据应用于森林郁闭度遥感估测具有重大意义。激光雷达数据的应用能够有效地弥补传统地面调查耗时、费力等不足,不仅可以快速、准确地获取郁闭度遥感估测的模型训练数据和验证数据,还有助于进一步推广应用于大区域的森林郁闭度反演,为林业资源调查提供有力的依据。该研究结合激光雷达数据和LANDSAT ETM＋数据估测温带森林郁闭度。以高密度机载激光雷达（ALS）点云数据估算的郁闭度作为模型训练数据和验证数据,通过LANDSAT ETM＋影像数据计算得到的8种植被指数作为自变量,使用多元逐步回归（MSR）、随机森林（RF）和Cubist 3种模型,对内蒙古大兴安岭根河林区森林郁闭度进行估测。经验证,Cubist模型的效果比较好（决定系数R2=0.722,均方根误差RMSE=0.126,相对均方根误差r RMSE=0.209,估计精度EA=79.883%）。结果表明,结合激光雷达数据和LANDSAT ETM＋影像数据估算温带森林郁闭度非常有潜力。但要将其推广应用于更大区域尺度的森林郁闭度遥感估测,模型的预测能力还有待进一步改进和提高;自变量应尝试加入更多种类遥感数据和其他遥感因子参与建模,例如采用地形因子、高分辨率遥感影像提取纹理特征等,最大可能地减少光学影像、植被指数、地形阴影等带来的影响,提高反演精度;激光雷达数据计算得到的郁闭度的准确性和可靠性还需进一步验证。
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Application of Change Detection Technologies of Remote Sensing to Forestry ,https://doi.org/10.13348/j.cnki.sjlyyj.2016.02.005 URL [本文引用: 1] 摘要
森林是人类生存和发展的基础。快速、准确地获取森林的变化信息,对于生态环境可持续发展具有重要意义。文中在总结当前变化检测技术流程及方法最新研究进展的基础上,重点介绍遥感变化检测技术在森林资源监测、森林灾害防控以及林业重点工程监管3个方面的应用情况,展望变化检测技术在林业上的应用前景。
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Canopy closure estimation in a temperate forest using airborne LiDAR and LANDSAT ETM+ data .https://doi.org/10.17521/cjpe.2014.0366 URL [本文引用: 1] 摘要
森林郁闭度是森林资源调查中的一个重要因子,在森林生态系统管理中具有重要作用。研究如何有效地将激光雷达数据应用于森林郁闭度遥感估测具有重大意义。激光雷达数据的应用能够有效地弥补传统地面调查耗时、费力等不足,不仅可以快速、准确地获取郁闭度遥感估测的模型训练数据和验证数据,还有助于进一步推广应用于大区域的森林郁闭度反演,为林业资源调查提供有力的依据。该研究结合激光雷达数据和LANDSAT ETM＋数据估测温带森林郁闭度。以高密度机载激光雷达（ALS）点云数据估算的郁闭度作为模型训练数据和验证数据,通过LANDSAT ETM＋影像数据计算得到的8种植被指数作为自变量,使用多元逐步回归（MSR）、随机森林（RF）和Cubist 3种模型,对内蒙古大兴安岭根河林区森林郁闭度进行估测。经验证,Cubist模型的效果比较好（决定系数R2=0.722,均方根误差RMSE=0.126,相对均方根误差r RMSE=0.209,估计精度EA=79.883%）。结果表明,结合激光雷达数据和LANDSAT ETM＋影像数据估算温带森林郁闭度非常有潜力。但要将其推广应用于更大区域尺度的森林郁闭度遥感估测,模型的预测能力还有待进一步改进和提高;自变量应尝试加入更多种类遥感数据和其他遥感因子参与建模,例如采用地形因子、高分辨率遥感影像提取纹理特征等,最大可能地减少光学影像、植被指数、地形阴影等带来的影响,提高反演精度;激光雷达数据计算得到的郁闭度的准确性和可靠性还需进一步验证。
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Monitoring changes of forest canopy density in a temperature forest using high-resolution aerial digital photography [J]. |
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高分1号卫星遥感影像监测林地动态变化研究 [J].https://doi.org/10.3969/j.issn.1001-7461.2016.04.37 URL [本文引用: 1] 摘要
应用高分1号和多期国产高分辨率卫星遥感影像对红星林业局林地动态变化进行目视解译与提取识别,检测林木采伐、占地、开垦和森林灾害等因素造成林地和林木的变化情况。结果表明,高分辨率卫星遥感监测林地动态变化解译正判率达95%以上,其可视化分析方法和技术为森林资源动态监测提供一定的科学支撑,为全国林地和林木采伐管理探讨技术方法。
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基于几何光学模型的毛竹林郁闭度无人机遥感定量反演 [J].
<div style="line-height: 150%">基于几何光学模型，探讨无人机遥感数据在毛竹林郁闭度定量反演中的应用，并分析了无约束和全约束两种混合像元分解对反演结果的影响.结果表明：利用无人机遥感数据与几何光学模型在一定程度上能够实现毛竹林郁闭度的估算，但不同混合像元分解方法反演精度差异较大；相对于无约束混合像元分解而言，全约束混合像元分解反演得到的郁闭度精度高，其反演郁闭度与野外实测数据的相关系数达显著水平，决定系数R<sup>2</sup>为 0.63，且均方根误差也很小，为0.04左右，能够较真实地反映毛竹林的实际情况.</div><div style="line-height: 150%"> </div>
Retrieval of crown closure of moso bamboo forest using unmanned aerial vehicle (UAV) remotely sensed imagery based on geometric-optical model .
<div style="line-height: 150%">基于几何光学模型，探讨无人机遥感数据在毛竹林郁闭度定量反演中的应用，并分析了无约束和全约束两种混合像元分解对反演结果的影响.结果表明：利用无人机遥感数据与几何光学模型在一定程度上能够实现毛竹林郁闭度的估算，但不同混合像元分解方法反演精度差异较大；相对于无约束混合像元分解而言，全约束混合像元分解反演得到的郁闭度精度高，其反演郁闭度与野外实测数据的相关系数达显著水平，决定系数R<sup>2</sup>为 0.63，且均方根误差也很小，为0.04左右，能够较真实地反映毛竹林的实际情况.</div><div style="line-height: 150%"> </div>
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Monitoring dynamic changes of forest land by using remote sensing images of GF-1 satellite .https://doi.org/10.3969/j.issn.1001-7461.2016.04.37 URL [本文引用: 1] 摘要
应用高分1号和多期国产高分辨率卫星遥感影像对红星林业局林地动态变化进行目视解译与提取识别,检测林木采伐、占地、开垦和森林灾害等因素造成林地和林木的变化情况。结果表明,高分辨率卫星遥感监测林地动态变化解译正判率达95%以上,其可视化分析方法和技术为森林资源动态监测提供一定的科学支撑,为全国林地和林木采伐管理探讨技术方法。
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Optimal land cover mapping and change analysis in north-eastern oregon using Landsat imagery [J].https://doi.org/10.14358/PERS.81.1.37 URL [本文引用: 1] 摘要
The necessity for the development of repeatable, efficient, and accurate monitoring of land cover change is paramount to successful management of our planet s natural resources. This study evaluated a number of remote sensing methods for classifying land cover and land cover change throughout a two-county area in northeastern Oregon (1986 to 2011). In the past three decades, this region has seen significant changes in forest management that have affected land use and land cover. This study employed an accuracy assessment-based empirical approach to test the optimality of a number of advanced digital image processing techniques that have recently emerged in the field of remote sensing.The accuracies are assessed using traditional error matrices, calculated using reference data obtained in the field. We found that, for single-time land cover classification, Bayes pixel-based classification using samples created with scale and shape segmentation parameters of 8 and 0.3, respectively, resulted in the highest overall accuracy. For land cover change detection, using Landsat-5 TM band 7 with a change threshold of 1.75 standard deviations resulted in the highest accuracy for forest harvesting and regeneration mapping
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黑龙江省大兴安岭森林生物量空间格局及其影响因素 [J].
<div style="line-height: 150%">基于样地实测数据和EVI指数,定量分析了黑龙江省大兴安岭森林生物量空间格局,并利用ArcGIS软件的空间分析与统计工具,分析了气候区、海拔、坡度、坡向和植被类型对森林生物量空间格局的影响.结果表明: 黑龙江省大兴安岭森林生物量为350 Tg,空间上呈聚集分布,生物量有巨大的增长空间.森林生物量密度大小顺序为:寒温带湿润区(64.02 t·hm<sup>-2</sup>)＞中温带湿润区(60.26 t·hm<sup>-2</sup>);各植被类型生物量密度大小顺序为:针阔混交林(65.13 t·hm<sup>-2</sup>)＞云冷杉林(63.92 t·hm<sup>-2</sup>)＞偃松落叶松林(63.79 t·hm<sup>-2</sup>)＞樟子松林(61.97 t·hm<sup>-2</sup>)＞兴安落叶松林(61.40 t·hm<sup>-2</sup>)＞落叶阔叶混交林(58.96 t·hm<sup>-2</sup>).随海拔和坡度的增大,森林生物量密度先减小后增加,并且阴坡大于阳坡.大兴安岭森林生物量空间格局随气候区、植被类型和地形因子的梯度变化表现出差异性,在区域尺度上估算生物量密度时,需要充分考虑这种空间差异性.</div><div style="line-height: 150%"> </div>
Spatial pattern of forest biomass and its influencing factors in the Great Xing’an Mountains, Heilongjiang Province, China .
<div style="line-height: 150%">基于样地实测数据和EVI指数,定量分析了黑龙江省大兴安岭森林生物量空间格局,并利用ArcGIS软件的空间分析与统计工具,分析了气候区、海拔、坡度、坡向和植被类型对森林生物量空间格局的影响.结果表明: 黑龙江省大兴安岭森林生物量为350 Tg,空间上呈聚集分布,生物量有巨大的增长空间.森林生物量密度大小顺序为:寒温带湿润区(64.02 t·hm<sup>-2</sup>)＞中温带湿润区(60.26 t·hm<sup>-2</sup>);各植被类型生物量密度大小顺序为:针阔混交林(65.13 t·hm<sup>-2</sup>)＞云冷杉林(63.92 t·hm<sup>-2</sup>)＞偃松落叶松林(63.79 t·hm<sup>-2</sup>)＞樟子松林(61.97 t·hm<sup>-2</sup>)＞兴安落叶松林(61.40 t·hm<sup>-2</sup>)＞落叶阔叶混交林(58.96 t·hm<sup>-2</sup>).随海拔和坡度的增大,森林生物量密度先减小后增加,并且阴坡大于阳坡.大兴安岭森林生物量空间格局随气候区、植被类型和地形因子的梯度变化表现出差异性,在区域尺度上估算生物量密度时,需要充分考虑这种空间差异性.</div><div style="line-height: 150%"> </div>
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A targeted change-detection procedure by combining change vector analysis and post-classification approach [J].https://doi.org/10.1016/j.isprsjprs.2016.01.018 URL [本文引用: 2] |
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An integrated spectral-textural approach for environmental change monitoring and assessment: analyzing the dynamics of green covers in a highly developing region [J].https://doi.org/10.1007/s10661-016-5206-6 URL [本文引用: 1] |
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森林固碳估计方法综述 [J].https://doi.org/10.3969/j.issn.1001-4241.2005.01.005 URL [本文引用: 1] 摘要
In this paper,several methods to estimate the carbon stored in forests were discussed.They are Biomass Method,Stem Volume Method,Eddy Covariance Method,Relaxed Eddy Accumulation REA method,Enclosures/Chamber Method,etc.Their principles,advantage and weakness were described.
Summary of estimation methods of the carbon stored in forests .https://doi.org/10.3969/j.issn.1001-4241.2005.01.005 URL [本文引用: 1] 摘要
In this paper,several methods to estimate the carbon stored in forests were discussed.They are Biomass Method,Stem Volume Method,Eddy Covariance Method,Relaxed Eddy Accumulation REA method,Enclosures/Chamber Method,etc.Their principles,advantage and weakness were described.
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An assessment of several linear change detection techniques for mapping forest mortality using multitemporal Landsat TM data [J].https://doi.org/10.1016/0034-4257(95)00233-2 URL [本文引用: 1] |
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Mangrove forest decline: consequences for livelihoods and environment in South Sulawesi [J].https://doi.org/10.1007/s10113-016-0989-0 URL [本文引用: 1] 摘要
Mangrove forests in the tropics and subtropics grow in saline sediments in coastal and estuarine environments. Preservation of mangrove forests is important for many reasons, including the prevention of coastal erosion and seawater intrusion; the provision of spawning, nursery, and feeding grounds of diverse marine biota; and for direct use (such as firewood, charcoal, and construction material)—all of which benefit the sustainability of local communities. However, for many mangrove areas of the world, unsustainable resource utilization and the profit orientation of communities have often led to rapid and severe mangrove loss with serious consequences. The mangrove forests of the Takalar District, South Sulawesi, are studied here as a case area that has suffered from degradation and declining spatial extent during recent decades. On the basis of a post-classification comparison of change detection from satellite imagery and a survey of households, we provide an estimate of the mangrove change in the Takalar District during 1979–2011 and the consequences of those changes. Mangrove forest areas were reduced by 66.05 % (3344 hectares) during the 33-year period of analysis, and the biggest annual negative change in dense mangrove forest cover (8.37 %) occurred during the period 2006–2011. The changes were caused mainly by the mangrove clearing and conversion to aquaculture, and consequences have been increasing forest degradation, coastal abrasion, seawater intrusion, a decline in fish capture, a reduction in juvenile shrimp and milkfish, and outbreaks of shrimp disease. On the other hand, the clearing and impoundment of mangrove forests for shrimp and seaweed culture have provided a source of foreign exchange and new opportunities for employment in the study area.
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结合影像光谱与地形因子的森林蓄积量估测模型 [J].https://doi.org/10.6041/j.issn.1000-1298.2014.05.033 URL [本文引用: 1] 摘要
Taking Wang Ye Dian Forestry Farm as the study area, forest volumes of sample plots were obtained as the true value through field investigation. At the same time, the images of satellite ZiYuan 3(ZY-3) were processed, and corresponding band spectra value, combination value of spectra and topographic information of the sample volumes were obtained. Through multiple regression analysis, broad leaved forest and coniferous forest volume estimation models were established. The experimental results show that the correlation coefficient of broad leaved forest volume estimation model was 0.815, and that of coniferous forest was 0.761. There was a strong correlation between the spectra value, combination of spectra, topographic factors of ZY-3 and the forest volume. The model prediction accuracy was verified, and accuracies of broad leaved forest and coniferous forest models were 85.3% and 91.9%, respectively. The study suggests that the use of ZY-3 images for the forest volume estimation has good application prospect.
Forest volume estimation model using spectra and topographic factors of ZY-3 image .https://doi.org/10.6041/j.issn.1000-1298.2014.05.033 URL [本文引用: 1] 摘要
Taking Wang Ye Dian Forestry Farm as the study area, forest volumes of sample plots were obtained as the true value through field investigation. At the same time, the images of satellite ZiYuan 3(ZY-3) were processed, and corresponding band spectra value, combination value of spectra and topographic information of the sample volumes were obtained. Through multiple regression analysis, broad leaved forest and coniferous forest volume estimation models were established. The experimental results show that the correlation coefficient of broad leaved forest volume estimation model was 0.815, and that of coniferous forest was 0.761. There was a strong correlation between the spectra value, combination of spectra, topographic factors of ZY-3 and the forest volume. The model prediction accuracy was verified, and accuracies of broad leaved forest and coniferous forest models were 85.3% and 91.9%, respectively. The study suggests that the use of ZY-3 images for the forest volume estimation has good application prospect.
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结合邻域相关影像与最大相关性最小冗余性特征选择的面向对象变化检测 [J].The object-oriented change detection based on neighborhood correlation images and the minimum-redundancy-maximum-relevance feature selection . |
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A novel partially supervised approach to targeted change detection [J].https://doi.org/10.1109/TGRS.2011.2154336 URL [本文引用: 1] 摘要
In several application domains (e.g., crop conversion subsidies, forestry, natural hazard mapping, and spatial planning), the ultimate operational objective of change-detection analysis is actually limited to the identification of only one (or few) specific land-cover transition(s) of interest (i.e., a "targeted" change detection problem), disregarding all the other potential changes occurring in the area under analysis at the same time. Supervised change-detection techniques generally represent the most accurate methodological solution for mapping land-cover changes while identifying the associated land-cover transitions between two different dates. However, the application of these techniques depends on the availability of exhaustive ground-truth information for all the land-cover classes present in the area of interest at the times under investigation. Such a requirement is seldom satisfied since gathering a reliable ground truth for all the classes characterizing the considered scenes at the two dates under analysis presents several practical drawbacks and limitations (both in terms of time and economic cost) that may render this task almost impossible in most real-life cases. Nevertheless, to solve these specific types of problems, it would be highly beneficial for an operator to rely on a robust automatic technique that may allow an effective detection of the "targeted" land-cover transitions by taking into account only ground-truth information for the few classes of interest at each date (thus, avoiding the burden and cost associated to the collection of a full and exhaustive ground-truth data set at both times). In this paper, we address this challenging issue and propose a novel technique (formulated in terms of a compound decision problem) capable of identifying specific "targeted" land-cover transitions by exploiting the ground truth available only for the classes of interest at the two dates, while providing accuracies comparable to those of traditional fully supervised change-detection methods. The proposed technique relies on a partially supervised approach that jointly exploits the expectation-maximization algorithm and an iterative labeling strategy based on Markov random fields accounting for spatial and temporal correlation between the two images. Moreover, the proposed method is applicable to images acquired by different sensors (or to different sets of features) at the two investigated times. Experimental results on different multitemporal and multisensor data sets confirmed the effectiveness and the reliability of the proposed technique.
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A novel partially supervised approach to targeted change detection [J].https://doi.org/10.1109/TGRS.2011.2154336 URL [本文引用: 1] 摘要
In several application domains (e.g., crop conversion subsidies, forestry, natural hazard mapping, and spatial planning), the ultimate operational objective of change-detection analysis is actually limited to the identification of only one (or few) specific land-cover transition(s) of interest (i.e., a "targeted" change detection problem), disregarding all the other potential changes occurring in the area under analysis at the same time. Supervised change-detection techniques generally represent the most accurate methodological solution for mapping land-cover changes while identifying the associated land-cover transitions between two different dates. However, the application of these techniques depends on the availability of exhaustive ground-truth information for all the land-cover classes present in the area of interest at the times under investigation. Such a requirement is seldom satisfied since gathering a reliable ground truth for all the classes characterizing the considered scenes at the two dates under analysis presents several practical drawbacks and limitations (both in terms of time and economic cost) that may render this task almost impossible in most real-life cases. Nevertheless, to solve these specific types of problems, it would be highly beneficial for an operator to rely on a robust automatic technique that may allow an effective detection of the "targeted" land-cover transitions by taking into account only ground-truth information for the few classes of interest at each date (thus, avoiding the burden and cost associated to the collection of a full and exhaustive ground-truth data set at both times). In this paper, we address this challenging issue and propose a novel technique (formulated in terms of a compound decision problem) capable of identifying specific "targeted" land-cover transitions by exploiting the ground truth available only for the classes of interest at the two dates, while providing accuracies comparable to those of traditional fully supervised change-detection methods. The proposed technique relies on a partially supervised approach that jointly exploits the expectation-maximization algorithm and an iterative labeling strategy based on Markov random fields accounting for spatial and temporal correlation between the two images. Moreover, the proposed method is applicable to images acquired by different sensors (or to different sets of features) at the two investigated times. Experimental results on different multitemporal and multisensor data sets confirmed the effectiveness and the reliability of the proposed technique.
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Estimating timber volume using airborne laser scanning data based on Bayesian methods [D]. In: |
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Estimating stand volume and above-ground biomass of urban forests using LiDAR [J].https://doi.org/10.3390/rs8040339 URL [本文引用: 1] 摘要
2014 by the authors. Assessing forest stand conditions in urban and peri-urban areas is essential to support ecosystem service planning and management, as most of the ecosystem services provided are a consequence of forest stand characteristics. However, collecting data for assessing forest stand conditions is time consuming and labor intensive. A plausible approach for addressing this issue is to establish a relationship between in situ measurements of stand characteristics and data from airborne laser scanning (LiDAR). In this study we assessed forest stand volume and above-ground biomass (AGB) in a broadleaved urban forest, using a combination of LiDAR-derived metrics, which takes the form of a forest allometric model. We tested various methods for extracting proxies of basal area (BA) and mean stand height (H) from the LiDAR point-cloud distribution and evaluated the performance of different models in estimating forest stand volume and AGB. The best predictors for both models were the scale parameters of the Weibull distribution of all returns (except the first) (proxy of BA) and the 95th percentile of the distribution of all first returns (proxy of H). The R 2 were 0.81 (p < 0.01) for the stand volume model and 0.77 (p < 0.01) for the AGB model with a RMSE of 23.66 m 3 ha -1 (23.3%) and 19.59 Mg ha -1 (23.9%), respectively. We found that a combination of two LiDAR-derived variables (i.e., proxy of BA and proxy of H), which take the form of a forest allometric model, can be used to estimate stand volume and above-ground biomass in broadleaved urban forest areas. Our results can be compared to other studies conducted using LiDAR in broadleaved forests with similar methods.
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Improving change detection in forest areas based on stereo panchromatic imagery using kernel MNF [J].https://doi.org/10.1109/TGRS.2014.2308012 URL [本文引用: 1] 摘要
The goal of this paper is to develop an efficient method for forest change detection using multitemporal stereo panchromatic imagery. Due to the lack of spectral information, it is difficult to extract reliable features for forest change monitoring. Moreover, the forest changes often occur together with other unrelated phenomena, e.g., seasonal changes of land covers such as grass and crops. Therefore, we propose an approach that exploits kernel Minimum Noise Fraction (kMNF) to transform simple change features into high-dimensional feature space. Digital surface models (DSMs) generated from stereo imagery are used to provide information on height difference, which is additionally used to separate forest changes from other land-cover changes. With very few training samples, a change mask is generated with iterated canonical discriminant analysis (ICDA). Two examples are presented to illustrate the approach and demonstrate its efficiency. It is shown that with the same amount of training samples, the proposed method can obtain more accurate change masks compared with algorithms based on k-means, one-class support vector machine, and random forests.
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基于机载激光雷达数据的森林结构参数反演 [J].https://doi.org/10.11873/j.issn.1004-0323.2015.5.0917 Magsci [本文引用: 1] 摘要
<p>机载激光雷达(Light Detection And Ranging,LiDAR)技术对植被空间结构和地形的探测能力较强,在植被参数定量测量和反演方面具有显著优势。首先利用野外调查并结合高分辨率Geoeye-1影像数据,对黑河上游天涝池流域植被类型进行分类,提取研究区森林分布,然后结合0.5 m×0.5 m机载激光雷达(LiDAR)数据对森林结构参数(树高、冠幅、胸径和叶面积指数)进行反演,最后利用实际观测数据对反演结果进行验证。结果表明:机载激光雷达数据能够精确地反演森林结构参数,树高、冠幅、胸径和叶面积指数的实测值与估测值决定系数分别为0.98、0.84、0.57和0.73。本研究获得流域森林覆盖区域高精度树冠高度和叶面积指数空间分布图,同时分析了冠层高度和叶面积指数随高度的变化。本研究的结果为该流域分布式生态水文模型提供了重要的输入参数。</p>
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| [99] |
Comparison of stand volume predictions based on airborne laser scanning data versus aerial stereo images [J]. |
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基于偏最小二乘回归的森林蓄积量遥感估测 [J].https://doi.org/10.3969/j.issn.1000-2286.2013.04.023 URL [本文引用: 1] 摘要
森林蓄积量受遥感因子与地形因子的影响,但这些因子间存在多重相 关性,会影响模型稳定性与精度.针对森林蓄积量遥感估测自变量间存在多重共线性问题,采用异于传统最小二乘的偏最小二乘方法建立密云县森林蓄积量遥感估测 模型.先对可能影响蓄积量的因子进行分析,选取既存在相关性又对模型显著性有影响的因子为森林蓄积量估测的自变量.用预留的样本对模型进行检验,预测值与 实测值相比精度达到90.1％.将通过检验的模型对整个密云县进行反演,得到密云县估测森林蓄积量为2 447 695.203 m3.
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| [43] |
Retrieval of the forest structural parameters using airborne LiDAR Data .https://doi.org/10.11873/j.issn.1004-0323.2015.5.0917 Magsci [本文引用: 1] 摘要
<p>机载激光雷达(Light Detection And Ranging,LiDAR)技术对植被空间结构和地形的探测能力较强,在植被参数定量测量和反演方面具有显著优势。首先利用野外调查并结合高分辨率Geoeye-1影像数据,对黑河上游天涝池流域植被类型进行分类,提取研究区森林分布,然后结合0.5 m×0.5 m机载激光雷达(LiDAR)数据对森林结构参数(树高、冠幅、胸径和叶面积指数)进行反演,最后利用实际观测数据对反演结果进行验证。结果表明:机载激光雷达数据能够精确地反演森林结构参数,树高、冠幅、胸径和叶面积指数的实测值与估测值决定系数分别为0.98、0.84、0.57和0.73。本研究获得流域森林覆盖区域高精度树冠高度和叶面积指数空间分布图,同时分析了冠层高度和叶面积指数随高度的变化。本研究的结果为该流域分布式生态水文模型提供了重要的输入参数。</p>
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| [100] |
Estimation of forest stock volume based on partial least squares regression .https://doi.org/10.3969/j.issn.1000-2286.2013.04.023 URL [本文引用: 1] 摘要
森林蓄积量受遥感因子与地形因子的影响,但这些因子间存在多重相 关性,会影响模型稳定性与精度.针对森林蓄积量遥感估测自变量间存在多重共线性问题,采用异于传统最小二乘的偏最小二乘方法建立密云县森林蓄积量遥感估测 模型.先对可能影响蓄积量的因子进行分析,选取既存在相关性又对模型显著性有影响的因子为森林蓄积量估测的自变量.用预留的样本对模型进行检验,预测值与 实测值相比精度达到90.1％.将通过检验的模型对整个密云县进行反演,得到密云县估测森林蓄积量为2 447 695.203 m3.
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| [101] |
利用TM影像和偏最小二乘回归方法估测三峡库区森林蓄积量 [J].
为进一步提高遥感模型预测森林蓄积量的精度和稳定性，分析了遥感特征因子、地形特征因子、郁闭度与森林蓄积量之间的相关关系。在此基础上，利用偏最小二乘回归方法构建了森林蓄积量遥感预测模型，生成了三峡库区森林蓄积量空间等级分布图，并与地面实测值进行比较。结果表明：该模型的最佳主成分数为3，且郁闭度、海拔、坡度、TMl、TM2、TM3、TM4、TM5、TM7、NDVI、RVI、TM7／TM3、TM4×TM3／TM2、亮度和湿度为预测森林蓄积量的人选变量；森林蓄积量预测的调整决定系数为0．524，相对误差为7．33％，均方根误差为1．763m3；利用该模型计算出三峡库区森林总蓄积量约为1．12亿m3，总体预测精度达到89．58％。研究结果为提高森林蓄积量遥感预测的精度提供了一种有效手段，有利于大面积应用和推广。
Predicting forest volume in Three Gorges Reservoir Region using TM images and partial least squares regression .
为进一步提高遥感模型预测森林蓄积量的精度和稳定性，分析了遥感特征因子、地形特征因子、郁闭度与森林蓄积量之间的相关关系。在此基础上，利用偏最小二乘回归方法构建了森林蓄积量遥感预测模型，生成了三峡库区森林蓄积量空间等级分布图，并与地面实测值进行比较。结果表明：该模型的最佳主成分数为3，且郁闭度、海拔、坡度、TMl、TM2、TM3、TM4、TM5、TM7、NDVI、RVI、TM7／TM3、TM4×TM3／TM2、亮度和湿度为预测森林蓄积量的人选变量；森林蓄积量预测的调整决定系数为0．524，相对误差为7．33％，均方根误差为1．763m3；利用该模型计算出三峡库区森林总蓄积量约为1．12亿m3，总体预测精度达到89．58％。研究结果为提高森林蓄积量遥感预测的精度提供了一种有效手段，有利于大面积应用和推广。
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| [102] |
基于遥感、地理信息系统和人工神经网络的呼中林区森林蓄积量估测 [J].
<FONT face=Verdana>利用遥感图像光谱信息良好的综合性和现势性以及地理信息系统(GIS)强大的空间分析功能，结合人工神经网络(ANN)可优化求解非线性复杂系统的功能，对呼中林区森林蓄积量进行了估测.结果表明：中红外波段与森林蓄积量间存在明显的负相关关系，说明中红外波段对估<BR>测森林蓄积量具有一定潜力；可见光波段和光谱变换第一主成分与森林蓄积量间也存在负相<BR>关关系；地形因子中海拔对研究区森林蓄积量的影响最大，坡度和坡向对蓄积量的影响较小<BR>.基于最佳的ANN网络参数、适当的GIS提取信息和遥感波段，呼中林区森林蓄积量的预测值<BR>和实测值的相关系数达0.973，经主成分变换后，数据量被有效降低，而预测精度只有少量<BR>下降(R<SUP>2</SUP>=0.934).<BR></FONT>
Estimation of forest volume in Huzhong forest area based on RS, GIS and ANN .
<FONT face=Verdana>利用遥感图像光谱信息良好的综合性和现势性以及地理信息系统(GIS)强大的空间分析功能，结合人工神经网络(ANN)可优化求解非线性复杂系统的功能，对呼中林区森林蓄积量进行了估测.结果表明：中红外波段与森林蓄积量间存在明显的负相关关系，说明中红外波段对估<BR>测森林蓄积量具有一定潜力；可见光波段和光谱变换第一主成分与森林蓄积量间也存在负相<BR>关关系；地形因子中海拔对研究区森林蓄积量的影响最大，坡度和坡向对蓄积量的影响较小<BR>.基于最佳的ANN网络参数、适当的GIS提取信息和遥感波段，呼中林区森林蓄积量的预测值<BR>和实测值的相关系数达0.973，经主成分变换后，数据量被有效降低，而预测精度只有少量<BR>下降(R<SUP>2</SUP>=0.934).<BR></FONT>
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Comparison of nearest neighbour approaches for small area estimation of tree species-specific forest inventory attributes in central Europe using airborne laser scanner data .https://doi.org/10.1007/s10342-010-0384-1 URL [本文引用: 1] |
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A new method for segmenting individual trees from the lidar point cloud [J].https://doi.org/10.14358/PERS.78.1.75 URL [本文引用: 1] 摘要
Light Detection and Ranging (lidar) has been widely applied to characterize the 3-dimensional (3D) structure of forests as it can generate 3D point data with high spatial resolution and accuracy. Individual tree segmentations, usually derived from the canopy height model, are used to derive individual tree structural attributes such as tree height, crown diameter, canopy-based height, and others. In this study, we develop a new algorithm to segment individual trees from the small footprint discrete return airborne lidar point cloud. We experimentally applied the new algorithm to segment trees in a mixed conifer forest in the Sierra Nevada Mountains in California. The results were evaluated in terms of recall, precision, and F-score, and show that the algorithm detected 86 percent of the trees (“recall”), 94 percent of the segmented trees were correct (“precision”), and the overall F-score is 0.9. Our results indicate that the proposed algorithm has good potential in segmenting individual trees in mixed conifer stands of similar structure using small footprint, discrete return lidar data.
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Simultaneous use of Landsat-TM and IRS-1C WiFS data in estimating large area tree stem volume and aboveground biomass [J].https://doi.org/10.1016/S0034-4257(02)00031-7 URL [本文引用: 1] |
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Predicting individual tree attributes from airborne laser point clouds based on the random forests technique [J].https://doi.org/10.1016/j.isprsjprs.2010.08.003 URL [本文引用: 1] |
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Using lidar data and a height-structured ecosystem model to estimate forest carbon stocks and fluxes over mountainous terrain [J].https://doi.org/10.5589/m08-036 URL [本文引用: 1] |
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Laser remote sensing of canopy habitat heterogeneity as a predictor of bird species richness in an eastern temperate forest, USA [J].https://doi.org/10.1016/j.rse.2006.11.016 URL [本文引用: 1] |
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Estimation of tropical forest structural characteristics using large-footprint lidar [J].https://doi.org/10.1016/S0034-4257(01)00281-4 URL [本文引用: 1] 摘要
Quantification of forest structure is important for developing a better understanding of how forest ecosystems function. Additionally, estimation of forest structural attributes, such as aboveground biomass (AGBM), is an important step in identifying the amount of carbon in terrestrial vegetation pools and is central to global carbon cycle studies. Although current remote sensing techniques recover such tropical forest structure poorly, new large-footprint lidar instruments show great promise. As part of a prelaunch validation plan for the Vegetation Canopy Lidar (VCL) mission, the Laser Vegetation Imaging Sensor (LVIS), a large-footprint airborne scanning lidar, was flown over the La Selva Biological Station, a tropical wet forest site in Costa Rica. The primary objective of this study was to test the ability of large-footprint lidar instruments to recover forest structural characteristics across a spectrum of land cover types from pasture to secondary and primary tropical forests. LVIS metrics were able to predict field-derived quadratic mean stem diameter (QMSD), basal area, and AGBM with R 2 values of up to .93, .72, and .93, respectively. These relationships were significant and nonasymptotic through the entire range of conditions sampled at the La Selva. Our results confirm the ability of large-footprint lidar instruments to estimate important structural attributes, including biomass in dense tropical forests, and when taken along with similar results from studies in temperate forests, strongly validate the VCL mission framework.
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Research on the estimation method of the Chinese fir volume based on BP neural networks . |
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森林生物量估测进展 [J].Progress in forest biomass estimation . |
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Monitoring coniferous forest biomass change using a Landsat trajectory-based approach [J].https://doi.org/10.1016/j.rse.2013.08.010 URL [本文引用: 1] 摘要
Forest biomass is a major store of carbon and thus plays an important role in the regional and global carbon cycle. Accurate forest carbon sequestration assessment requires estimation of both forest biomass and forest biomass dynamics over time. Forest dynamics are characterized by disturbances and recovery, key processes affecting site productivity and the forest carbon cycle. Thus, spatially and temporally explicit knowledge of these processes and their drivers are critical for understanding regional carbon cycles. Here, we present a new method that uses satellite data to estimate changes in forest aboveground biomass associated with forest disturbances and recovery at annual time steps. First yearly maps of aboveground biomass between 1985 and 2010 based on Landsat time series and field data were created. Then, we applied a trajectory-based segmentation and fitting algorithm to the yearly biomass maps to reconstruct the forest disturbance and recovery history over the last 25 years.We tested the method over a coniferous forest region in the Western Carpathian Mountains, which experienced long-term environmental changes. Overall, 55% (similar to 30,700 ha) of the total coniferous forest experienced a loss of biomass over the observation period, while similar to 30% showed severe or complete removal of forest biomass. At the same time, 11.2% of the area was reforested or regenerated on previously damaged forest stands. The total coniferous biomass dropped by 15% between 1985 and 2010, indicating negative balance between the losses and the gains. Disturbance hotspots indicate high insect infestation levels in many areas and reveal strong interactions between biomass loss and climate conditions. Our study demonstrates how spatial and temporal estimates of biomass help to understand regional forest dynamics and derive degradation trends in regard to regional climate change. (C) 2013 Elsevier Inc. All rights reserved.
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| [108] |
Old-growth forests as global carbon sinks [J].https://doi.org/10.1038/nature07276 URL PMID: 18784722 [本文引用: 1] 摘要
Abstract Old-growth forests remove carbon dioxide from the atmosphere at rates that vary with climate and nitrogen deposition. The sequestered carbon dioxide is stored in live woody tissues and slowly decomposing organic matter in litter and soil. Old-growth forests therefore serve as a global carbon dioxide sink, but they are not protected by international treaties, because it is generally thought that ageing forests cease to accumulate carbon. Here we report a search of literature and databases for forest carbon-flux estimates. We find that in forests between 15 and 800 years of age, net ecosystem productivity (the net carbon balance of the forest including soils) is usually positive. Our results demonstrate that old-growth forests can continue to accumulate carbon, contrary to the long-standing view that they are carbon neutral. Over 30 per cent of the global forest area is unmanaged primary forest, and this area contains the remaining old-growth forests. Half of the primary forests (6 x 10(8) hectares) are located in the boreal and temperate regions of the Northern Hemisphere. On the basis of our analysis, these forests alone sequester about 1.3 +/- 0.5 gigatonnes of carbon per year. Thus, our findings suggest that 15 per cent of the global forest area, which is currently not considered when offsetting increasing atmospheric carbon dioxide concentrations, provides at least 10 per cent of the global net ecosystem productivity. Old-growth forests accumulate carbon for centuries and contain large quantities of it. We expect, however, that much of this carbon, even soil carbon, will move back to the atmosphere if these forests are disturbed.
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| [109] |
基于森林群落和光谱曲线特征分异的福建省森林生物量遥感反演 [J].Forest biomass based on the forest communities and image spectral curve characteristics: A remote sensing estimation in Fujian Province . |
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高光谱与高空间分辨率遥感数据的亚热带森林生物量反演 [J].https://doi.org/10.11834/jrs.20165210 URL [本文引用: 1] 摘要
精确估算森林生物量对全球碳平衡以及气候变化的研究有重要意义.以亚热带天然次生林为研究对象,借助地面实测样地数据,通过对机载LiCHy(LiDAR,CCD and Hyperspectral)传感器同时获取的高光谱和高空间分辨率数据进行信息提取和数据融合,建模反演森林生物量.首先通过面向对象分割方法进行单木冠幅提取,然后融合从高光谱数据提取的光谱特征变量和从高空间分辨率数据提取的单木冠幅统计变量,构建多元回归模型估算地上、地下生物量,最后利用地面实测生物量经交叉验证评价模型精度.结果表明,综合模型的精度(R2为0.54-0.62)高于高光谱模型(R2为0.48-0.57);在高光谱模型中地上生物量模型精度(R2为0.57)高于地下生物量模型(R2为0.48);在综合模型中地上生物量模型精度(R2为0.62)同样高于地下生物量模型(R2为0.54).交叉验证结果表明,与仅使用高光谱数据(单一数据源)相比,通过集成高光谱和高空间分辨率数据的生物量反演效果有所提升,可以更加有效地估算亚热带森林生物量.
Subtropical forest biomass estimation based on hyperspectral and high-resolution remotely sensed data .https://doi.org/10.11834/jrs.20165210 URL [本文引用: 1] 摘要
精确估算森林生物量对全球碳平衡以及气候变化的研究有重要意义.以亚热带天然次生林为研究对象,借助地面实测样地数据,通过对机载LiCHy(LiDAR,CCD and Hyperspectral)传感器同时获取的高光谱和高空间分辨率数据进行信息提取和数据融合,建模反演森林生物量.首先通过面向对象分割方法进行单木冠幅提取,然后融合从高光谱数据提取的光谱特征变量和从高空间分辨率数据提取的单木冠幅统计变量,构建多元回归模型估算地上、地下生物量,最后利用地面实测生物量经交叉验证评价模型精度.结果表明,综合模型的精度(R2为0.54-0.62)高于高光谱模型(R2为0.48-0.57);在高光谱模型中地上生物量模型精度(R2为0.57)高于地下生物量模型(R2为0.48);在综合模型中地上生物量模型精度(R2为0.62)同样高于地下生物量模型(R2为0.54).交叉验证结果表明,与仅使用高光谱数据(单一数据源)相比,通过集成高光谱和高空间分辨率数据的生物量反演效果有所提升,可以更加有效地估算亚热带森林生物量.
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| [111] |
A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems .https://doi.org/10.1080/17538947.2014.990526 URL [本文引用: 2] 摘要
Remote sensing-based methods of aboveground biomass (AGB) estimation in forest ecosystems have gained increased attention, and substantial research has been conducted in the past three decades. This paper provides a survey of current biomass estimation methods using remote sensing data and discusses four critical issues collection of field-based biomass reference data, extraction and selection of suitable variables from remote sensing data, identification of proper algorithms to develop biomass estimation models, and uncertainty analysis to refine the estimation procedure. Additionally, we discuss the impacts of scales on biomass estimation performance and describe a general biomass estimation procedure. Although optical sensor and radar data have been primary sources for AGB estimation, data saturation is an important factor resulting in estimation uncertainty. LIght Detection and Ranging (lidar) can remove data saturation, but limited availability of lidar data prevents its extensive application. This literature survey has indicated the limitations of using single-sensor data for biomass estimation and the importance of integrating multi-sensor/scale remote sensing data to produce accurate estimates over large areas. More research is needed to extract a vertical vegetation structure (e.g. canopy height) from interferometry synthetic aperture radar (InSAR) or optical stereo images to incorporate it into horizontal structures (e.g. canopy cover) in biomass estimation modeling.
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Forest aboveground biomass estimation in Zhejiang Province using the integration of Landsat TM and ALOS PALSAR data .https://doi.org/10.1016/j.jag.2016.08.007 URL [本文引用: 3] |
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Retrieval of forest biomass from ALOS PALSAR data using a lookup table method [J].https://doi.org/10.1109/JSTARS.2012.2212701 URL [本文引用: 1] 摘要
Mapping of forest biomass over large area and in higher accuracy becomes more and more important for researches on global carbon cycle and climate change. The feasibility and problems of forest biomass estimations based on lookup table (LUT) methods using ALOS PALSAR data are investigated in this study. Using of the forest structures from a forest growth model as inputs to a three dimensional radar backscattering model, a lookup table is built. Two types of searching methods (Nearest Distance (ND) and Distance Threshold (DT)) are used to find solutions from lookup table. When a simulated dataset is used to test the lookup table, the RMSE of biomass estimation are 39.133 Mg/ha (R-2 = 0.748) from ND and 26.699 Mg/ha (R-2 = 0.886) from DT using dual-polarization data for forest with medium rough soil surface. All results show that DT is superior to ND. Comparisons of biomass from forest inventory data with that inversed from look up table using DT method over eight forest farms shows RMSE of 18.564 Mg/ha and 15.392 Mg/ha from PALSAR data with and without correction of the scattering mechanism, respectively. For the entire Lushuihe forest Bureau, the errors of the biomass estimation are -13.8 Mg/ha (-8.6%) and -5.5 Mg/ha (-3.5%) using PALSAR data with and without correction of scattering mechanisms due to terrain, respectively. The results shows that the radar image corrected data could be directly used for biomass estimation using the lookup table method.
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Features of point clouds synthesized from multi-view ALOS / PRISM data and comparisons with LiDAR data in forested areas [J].https://doi.org/10.1016/j.rse.2014.04.001 URL [本文引用: 1] |
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Biophysical estimation in tropical forests using JERS-1 SAR and VNIR imagery. II. Aboveground woody biomass [J].https://doi.org/10.1080/01431160802270123 URL [本文引用: 1] |
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胡杨单株蓄积量与生物量关系模型研究 [J].https://doi.org/10.13448/j.cnki.jalre.2016.166 URL [本文引用: 1] 摘要
森林的蓄积量与生物量评估是森林监测中的重要内容。我国有关森林蓄积方面的资料较为丰富,但是生物量方面的资料较少,因此森林蓄积量与生物量之间转换模型的研究具有重要意义。文中依据在塔里木河下游所伐倒的40棵胡杨样品,首先利用微积分模拟计算了蓄积量,其次用称重法测得胡杨的生物量,最后利用3个模型将胡杨的蓄积量与生物量的关系进行拟合,并将这3个模型的精确度进行对比分析。得出：B=c Vd模型的模拟效果最好,所建立的模型为：B=291.459V^1.183。
Study on the model of relation between volume and biomass of single Populus euphratica .https://doi.org/10.13448/j.cnki.jalre.2016.166 URL [本文引用: 1] 摘要
森林的蓄积量与生物量评估是森林监测中的重要内容。我国有关森林蓄积方面的资料较为丰富,但是生物量方面的资料较少,因此森林蓄积量与生物量之间转换模型的研究具有重要意义。文中依据在塔里木河下游所伐倒的40棵胡杨样品,首先利用微积分模拟计算了蓄积量,其次用称重法测得胡杨的生物量,最后利用3个模型将胡杨的蓄积量与生物量的关系进行拟合,并将这3个模型的精确度进行对比分析。得出：B=c Vd模型的模拟效果最好,所建立的模型为：B=291.459V^1.183。
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Volume-biomass functions reveal the effect of browsing on three Moroccan dwarf shrubs [J].https://doi.org/10.2989/10220119.2012.687074 URL [本文引用: 1] 摘要
We studied the effects of browsing on the plant architecture and volume-biomass relationships of three dominant dwarf shrubs 090009 Artemisia herba-alba, A. mesatlantica and Teucrium mideltense 090009 in a sagebrush steppe in the Central High Atlas Mountains, southern Morocco. For this purpose, we developed power-law volume-biomass functions based on nonlinear regressions for each of these species, under both browsed and unbrowsed conditions. These functions were then applied to individual-based annual monitoring data from inside and outside a browsing exclosure to calculate standing biomass for each of the years from 2004 to 2009. The biomass of the three species was well predicted by the allometric functions, and different functions for the browsed and unbrowsed conditions reflected changes in plant architecture. Browsing had a significant negative impact on biomass for A. herba-alba but not for A. mesatlantica, whereas its effects on T. mideltense were inconsistent between years. The fact that the latter two species hardly benefited from browsing exclusion might be because of increased competition from the more dominant A. herba-alba. During the study period, the standing biomass increased whether or not there was browsing, which might be because of the recovery of the shrubs after a preceding severe drought. Further studies are needed in order to investigate the generality of the findings.
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Understanding the relationship between aboveground biomass and ALOS PALSAR data in the forests of Guinea-Bissau(West Africa) [J].https://doi.org/10.1016/j.rse.2012.02.012 URL [本文引用: 1] |
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森林地上生物量遥感反演方法综述 [J].Review of forest above ground biomass inversion methods based on remote sensing technology . |
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遥感技术估算森林生物量的研究进展 [J].
从单传感器和多传感器遥感数据集成两个方面介绍和阐述了遥感技术估算森林生物量的发展现状,以此提炼遥感技术估算森林生物量研究面临的问题。
General review on remote sensing-based biomass estimation .
从单传感器和多传感器遥感数据集成两个方面介绍和阐述了遥感技术估算森林生物量的发展现状,以此提炼遥感技术估算森林生物量研究面临的问题。
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基于长时间序列Landsat影像的南方人工林干扰与恢复制图分析 [J].https://doi.org/10.5846/stxb201510142074 URL [本文引用: 1] 摘要
基于1986年到2011年的Landsat影像,以南方人工林分布区域广东省佛冈县为例,运用Landsat生态系统自适应处理系统(LEDAPS)预处理生成标准的地面反射率数据构建Landsat时间序列堆栈(LTSS)用于Land Trendr算法监测人工林森林干扰与恢复的长时间序列变化,分析了连续24a森林干扰的年份变化、干扰量以及干扰持续的时间,验证了算法识别干扰的精度,并探讨了人工林干扰的驱动力。结果表明佛冈县的森林干扰较为剧烈,一般都在1000 hm~2。而1987、2002、2004、2005、2006、2007和2009年的干扰面积均超过2000 hm~2,其中1987、2007年两年的干扰面积达到6000 hm~2以上。相比森林干扰的变化,佛冈县的森林恢复面积随时间的变化相对平稳。通过对佛冈县森林干扰和恢复面积的趋势分析,发现20世纪80年代末到90年代森林干扰和恢复的面积基本少于2000年以后的变化面积,变化趋势比2000年以后的显得平缓;从2000年开始,森林干扰面积逐渐上升,总体面积变化趋势高于森林的恢复,但森林的恢复面积仍有所提升。其中,佛冈县的森林干扰持续1a时间的面积比例约38%,持续2a时间约28%,持续3a时间约25%,持续4a时间约7%,主要为短期急剧的干扰事件。另外,持续时间为4a以上的森林干扰和恢复的面积在佛冈县不超过100hm~2。2000年之前持续干扰和急剧干扰面积相当,变化比较平缓;到2000年之后,急剧干扰的面积远大于持续干扰,最高约达2800 hm~2,但两者都呈现波动上升的变化趋势。在选取的两个4km~2的样方中,基于影像光谱识别以及通过比对干扰资料的可视化验证方法表明算法结果与真实地表的解译信息较吻合,误差约为0.1km~2。利用长时间序列遥感影像进行森林干扰的自动化监测十分必要,导出的定性、定位与定量信息,一方面为可持续的森林经营奠定基础,另一方面为评价森林生产力与森林碳储量提供有效的数据支撑。
Mapping disturbance and recovery of plantation forests in southern China using yearly Landsat time series observations .https://doi.org/10.5846/stxb201510142074 URL [本文引用: 1] 摘要
基于1986年到2011年的Landsat影像,以南方人工林分布区域广东省佛冈县为例,运用Landsat生态系统自适应处理系统(LEDAPS)预处理生成标准的地面反射率数据构建Landsat时间序列堆栈(LTSS)用于Land Trendr算法监测人工林森林干扰与恢复的长时间序列变化,分析了连续24a森林干扰的年份变化、干扰量以及干扰持续的时间,验证了算法识别干扰的精度,并探讨了人工林干扰的驱动力。结果表明佛冈县的森林干扰较为剧烈,一般都在1000 hm~2。而1987、2002、2004、2005、2006、2007和2009年的干扰面积均超过2000 hm~2,其中1987、2007年两年的干扰面积达到6000 hm~2以上。相比森林干扰的变化,佛冈县的森林恢复面积随时间的变化相对平稳。通过对佛冈县森林干扰和恢复面积的趋势分析,发现20世纪80年代末到90年代森林干扰和恢复的面积基本少于2000年以后的变化面积,变化趋势比2000年以后的显得平缓;从2000年开始,森林干扰面积逐渐上升,总体面积变化趋势高于森林的恢复,但森林的恢复面积仍有所提升。其中,佛冈县的森林干扰持续1a时间的面积比例约38%,持续2a时间约28%,持续3a时间约25%,持续4a时间约7%,主要为短期急剧的干扰事件。另外,持续时间为4a以上的森林干扰和恢复的面积在佛冈县不超过100hm~2。2000年之前持续干扰和急剧干扰面积相当,变化比较平缓;到2000年之后,急剧干扰的面积远大于持续干扰,最高约达2800 hm~2,但两者都呈现波动上升的变化趋势。在选取的两个4km~2的样方中,基于影像光谱识别以及通过比对干扰资料的可视化验证方法表明算法结果与真实地表的解译信息较吻合,误差约为0.1km~2。利用长时间序列遥感影像进行森林干扰的自动化监测十分必要,导出的定性、定位与定量信息,一方面为可持续的森林经营奠定基础,另一方面为评价森林生产力与森林碳储量提供有效的数据支撑。
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Monitoring and estimating drought-induced impacts on forest structure, growth, function, and ecosystem services using remote-sensing data: recent progress and future challenges [J].https://doi.org/10.1139/er-2013-0006 URL [本文引用: 1] 摘要
Alongside global warming, droughts are expected to increase in frequency, severity, and extent in the near future, which will likely result in significant impacts on forest growth, production, structure, composition, and ecosystem services. However, due to spatial and temporal characteristics, it is difficult to monitor and assess the potential effects of droughts. Remote sensing can provide an effective way to obtain real-time conditions of forests affected by drought and offer a range of spatial and temporal insights into drought-induced changes to forest ecosystem structure, function, and services. Remote sensing is rapidly developing as more satellites are launched. In situ and remotely sensed data fusion techniques have achieved notable success in assessing drought-induced damage to forests and carbon cycles. Even so, constraints still exist when using satellite data. The objectives of this review are to (1) briefly review existing data sources and methods of remote sensing; (2) synthesize current applications and contributions of remote sensing in monitoring and estimating impacts of droughts on forest ecosystems; and (3) highlight research gaps and future challenges.
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我国森林火灾预警监测技术体系发展思考 [J].Development of forest fire early warning and monitoring technique system in China . |
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Remote sensing approaches for reconstructing fire perimeters and burn severity mosaics in desert spring ecosystems [J].https://doi.org/10.1016/j.rse.2011.05.001 URL [本文引用: 1] |
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Remote sensing estimates of stand-replacement fires in Russia, 2002-2011 [J].https://doi.org/10.1088/1748-9326/9/10/105007 URL [本文引用: 1] 摘要
The presented study quantifies the proportion of stand-replacement fires in Russian forests through the integrated analysis of Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) data products. We employed 30 m Landsat Enhanced Thematic Mapper Plus derived tree canopy cover and decadal (2001–2012) forest cover loss (Hansen et al 2013 High-resolution global maps of 21st-century forest cover change Science 342 850–53) to identify forest extent and disturbance. These data were overlaid with 1 km MODIS active fire (earthdata.nasa.gov/data/near-real-time-data/firms) and 500 m regional burned area data (Loboda et al 2007 Regionally adaptable dNBR-based algorithm for burned area mapping from MODIS data Remote Sens. Environ. 109 429–42 and Loboda et al 2011 Mapping burned area in Alaska using MODIS data: a data limitations-driven modification to the regional burned area algorithm Int. J. Wildl. Fire 20 487–96) to differentiate stand-replacement disturbances due to fire versus other causes. Total stand replacement forest fire area within the Russian Federation from 2002 to 2011 was estimated to be 17.6 million ha (Mha). The smallest stand-replacement fire loss occurred in 2004 (0.4 Mha) and the largest annual loss in 2003 (3.3 Mha). Of total burned area within forests, 33.6% resulted in stand-replacement. Light conifer stands comprised 65% of all non-stand-replacement and 79% of all stand-replacement fire in Russia. Stand-replacement area for the study period is estimated to be two times higher than the reported logging area. Results of this analysis can be used with historical fire regime estimations to develop effective fire management policy, increase accuracy of carbon calculations, and improve fire behavior and climate change modeling efforts. (paper)
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| [129] |
Quantifying black carbon deposition over the Greenland ice sheet from forest fires in Canada [J].https://doi.org/10.1002/2017GL073701 URL [本文引用: 1] 摘要
Black carbon (BC) concentrations has been observed in 22 snowpits sampled in the northwest sector of the Greenland ice sheet in April 2014. The pits contain a strong and widespread BC aerosol deposition event, which accumulated in the pits during two snow storms between 27 July and 2 August 2013. This event comprises a significant portion (57% on average across all pits) of total BC deposition measured in the snowpits (~10 month record). We link this deposition event to forest fires burning in Canada during summer 2013 using modeling and remote sensing tools. Specifically, we use high-resolution regional chemical transport modeling (WRF-Chem) combined with high-resolution fire emissions (FINNv1.5) to study aerosol emissions, transport, and deposition to Greenland snow during this event. The model captures the timing of the BC deposition event and shows that fires in Canada were the main source of deposited BC. The implications for understanding the influence of BC originating from fires on the optical properties of snow is discussed.
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| [130] |
Evaluation of forest fire on Madeira Island using Sentinel-2A MSI imagery [J].https://doi.org/10.1016/j.jag.2017.02.003 URL [本文引用: 1] 摘要
A forest fire started on August 8th, 2016 in several places on Madeira Island causing damage and casualties. As of August 10th the local media had reported the death of three people, over 200 people injured, over 950 habitants evacuated, and 50 houses damaged. This study presents the preliminary results of the assessment of several spectral indices to evaluate the burn severity of Madeira fires during August 2016. These spectral indices were calculated using the new European satellite Sentinel-2A launched in June 2015. The study confirmed the advantages of several spectral indices such as Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Normalized Burn Ratio (NBR) and Normalized Difference Vegetation Index (NDVIreXn) using red-edge spectral bands to assess the post-fire conditions. Results showed high correlation between NDVI, GNDVI, NBR and NDVIre1n spectral indices and the analysis performed by Copernicus Emergency Management Service (EMSR175), considered as the reference truth. Regarding the red-edge spectral indices, the NDVIre1n (using band B5, 705nm) presented better results compared with B6 (740nm) and B7 (783nm) bands. These preliminary results allow us to assume that Sentinel-2 will be a valuable tool for post-fire monitoring. In the future, the two twin Sentinel-2 satellites will offer global coverage of the Madeira Archipelago every five days, therefore allowing the simultaneous study of the evolution of the burnt area and reforestation information with high spatial (up to 10m) and temporal resolution (5days).
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Assessment of MODIS NDVI time series data products for detecting forest defoliation by gypsy moth outbreaks [J].https://doi.org/10.1016/j.rse.2010.09.013 URL [本文引用: 1] |
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Detection of dead or defoliated spruces using digital aerial data [J].https://doi.org/10.1016/S0378-1127(01)00473-X URL [本文引用: 1] 摘要
The purpose of this study was to develop a method for detecting dead and defoliated spruces and defoliated stands in remote-sensing material using a semi-automatic pattern-recognition technique, spectral properties of trees, and different degrees of defoliation. The study material included two mapped defoliation stands in the municipality of Juupajoki (61°50′N, 24°18′E) in southern Finland. The ground truth data were collected during 1996–1997. The aerial color infrared (CIR) photographs, scaled to 1:5000, were taken on 28 June 1995 and on 19 June 1997. The degree of defoliation was visually estimated for every conifer in the defoliation stands. Individual trees in the digital aerial photographs were segmented using a robust segmentation method based on the recognition of tree crown patterns at a sub-pixel accuracy. The images were filtered with a Gaussian N× N smoothing operator, and local maxima above a threshold level were segmented using a directional derivate with some constraints. The segments were placed into defoliation classes using linear Fisher classification models, the parameters of which were estimated by cross-validation. Discriminant analysis was used to find variables for the segment classification. Defoliated tree segments and stands were classified satisfactorily. The accuracy of the pattern-recognition method proved adequate for detecting dead or heavily defoliated trees and heavily defoliated stands. The method described provides an interesting approach to using digital aerial data for automatically detecting severely defoliated spruce stands or individual trees.
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松毛虫灾害的TM影像监测技术 [J].https://doi.org/10.11834/jrs.20040212 Magsci [本文引用: 1] 摘要
中国森林病虫害日趋严重 ,每年都造成巨大损失 ,其主要原因之一就是不能实现森林病虫害的及时准确监测与中长期预测预报 ,以便把灾害控制在萌芽状态 ,虽然目前科学技术和研究水平还不能准确预测森林病虫害的发生发展 ,但可以及时监测早期灾害点 ,尽力把损失降到最低限度。该文主要介绍了利用陆地卫星TM数据开展早期灾害点 (或虫源地 )监测的方法和利用航天遥感数据对“虫源地”实施的有效监测 ,为航天遥感技术用于重大森林病虫害的宏观监测和预警提供了实例
Monitoring technique of pine caterpillars with TM image .https://doi.org/10.11834/jrs.20040212 Magsci [本文引用: 1] 摘要
中国森林病虫害日趋严重 ,每年都造成巨大损失 ,其主要原因之一就是不能实现森林病虫害的及时准确监测与中长期预测预报 ,以便把灾害控制在萌芽状态 ,虽然目前科学技术和研究水平还不能准确预测森林病虫害的发生发展 ,但可以及时监测早期灾害点 ,尽力把损失降到最低限度。该文主要介绍了利用陆地卫星TM数据开展早期灾害点 (或虫源地 )监测的方法和利用航天遥感数据对“虫源地”实施的有效监测 ,为航天遥感技术用于重大森林病虫害的宏观监测和预警提供了实例
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Yellowness index: an application of spectral second derivatives to estimate chlorosis of leaves in stressed vegetation [J].https://doi.org/10.1080/014311699211264 URL [本文引用: 1] |
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基于遥感影像的红树林虫害监测模型 [J].https://doi.org/10.13656/j.cnki.gxkx.20170411.002 URL [本文引用: 1] 摘要
【目的】研究遥感监测对红树林(Mangrove)虫害的适用性。【方法】应用资源一号02C卫星(ZY1-02C)影像和实地调查红树林虫害状况数据,结合影像光谱与纹理特征,采用多元逐步回归分析方法对广西铁山港湾的红树林虫害状况进行估测,并制作研究区红树林虫害状况空间分布图。【结果】估测模型可做为叶片损失情况预测的一种工具。【结论】本研究首次将遥感技术应用于红树林虫害的监测,大大提高红树林虫害的监测效率,项目成果极具推广意义。
Mangrove pests monitoring model based on the remote sesning image .https://doi.org/10.13656/j.cnki.gxkx.20170411.002 URL [本文引用: 1] 摘要
【目的】研究遥感监测对红树林(Mangrove)虫害的适用性。【方法】应用资源一号02C卫星(ZY1-02C)影像和实地调查红树林虫害状况数据,结合影像光谱与纹理特征,采用多元逐步回归分析方法对广西铁山港湾的红树林虫害状况进行估测,并制作研究区红树林虫害状况空间分布图。【结果】估测模型可做为叶片损失情况预测的一种工具。【结论】本研究首次将遥感技术应用于红树林虫害的监测,大大提高红树林虫害的监测效率,项目成果极具推广意义。
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Prediction and assessment of bark beetle-induced mortality of lodgepole pine using estimates of stand vigor derived from remotely sensed data [J].https://doi.org/10.1016/j.rse.2009.01.013 URL [本文引用: 1] |
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遥感技术在森林病虫害监测中的应用研究进展 [J].Application development of remote sensing technology in the assessment of forest pest disaster . |
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我国森林害虫监测预报技术研究进展(综述) [J].https://doi.org/10.3969/j.issn.1000-3924.2003.01.015 URL [本文引用: 1] 摘要
概述了我国森林害虫监测预报技术的最新进展,包括与测报有关的基础研究(种群空间格局、抽样技术),以及应用技术(地面诱捕、雷达监测、数理统计预报、遥感、地理信息系统、全球定位系统)等,对森林害虫监测预报技术的研究和生产应用都具有重要的参考价值.
Research progress on monitoring and forecasting of forest pests in China (a review) .https://doi.org/10.3969/j.issn.1000-3924.2003.01.015 URL [本文引用: 1] 摘要
概述了我国森林害虫监测预报技术的最新进展,包括与测报有关的基础研究(种群空间格局、抽样技术),以及应用技术(地面诱捕、雷达监测、数理统计预报、遥感、地理信息系统、全球定位系统)等,对森林害虫监测预报技术的研究和生产应用都具有重要的参考价值.
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Aerial mapping canopy damage by the aphid Essigella californica in a Pinus radiata plantation in southern New South Wales: what are the challenges? [J]https://doi.org/10.1080/00049158.2013.799055 URL [本文引用: 1] |
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Hyperspectral imagery for mapping disease infection in oil palm plantation using vegetation indices and red edge techniques [J].https://doi.org/10.3844/ajassp.2009.1031.1035 URL [本文引用: 1] |
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森林灾害的高分遥感辅助调查技术体系研究 [J].https://doi.org/10.13466/j.cnki.lyzygl.2014.05.009 URL [本文引用: 1] 摘要
森林灾害的突发性、周期性特点为监测调查带来很大困难,且随着社会经济的快速发展,全面的人工地面调查方法面临严重挑战。今后十几年我国对地观测能力的极速提高,可为森林资源的准实时变化监测提供基础保障。阐述了国产高分遥感数据应用的关键技术方法,展示了其在完善现有地面调查体系中的指导性作用,设计开发了适宜于县或省级应用的原型系统和技术体系,以期为国产高分数据的森林灾害监测应用提供技术示范和支撑。
Study on technical system of forest disaster investigation aided by high spatial resolution remote sensing technology .https://doi.org/10.13466/j.cnki.lyzygl.2014.05.009 URL [本文引用: 1] 摘要
森林灾害的突发性、周期性特点为监测调查带来很大困难,且随着社会经济的快速发展,全面的人工地面调查方法面临严重挑战。今后十几年我国对地观测能力的极速提高,可为森林资源的准实时变化监测提供基础保障。阐述了国产高分遥感数据应用的关键技术方法,展示了其在完善现有地面调查体系中的指导性作用,设计开发了适宜于县或省级应用的原型系统和技术体系,以期为国产高分数据的森林灾害监测应用提供技术示范和支撑。
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针叶林林窗研究进展 [J].Advance in coniferous forest gap . |
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Pattern and process in the plant community [J].https://doi.org/10.2307/2256497 URL [本文引用: 1] 摘要
Alex S. Watt, Pattern and Process in the Plant Community, Journal of Ecology, Vol. 35, No. 1/2 (Dec., 1947), pp. 1-22
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林窗生态学研究进展 .[J]https://doi.org/10.11707/j.1001-7488.20160411 URL Magsci [本文引用: 1] 摘要
林窗是森林生态系统中的一种中小尺度干扰,是促进森林更新、养分循环、功能提高的重要推动力。本文阐述林窗生态学的研究进展与展望,以期为今后的林窗理论研究和森林经营实践提供参考。林窗生态学研究集中于林窗的形成、基本特征以及林窗对森林小气候和植物群落特征等地上结构与过程的影响;近年来,林窗对细根与枯落物分解、土壤碳氮动态及酶活性以及对森林动物和土壤微生物的生理生态学特征影响研究逐渐增多,但研究的时空尺度较小且不够全面、深入。今后应着重研究林窗如何调控林分结构和森林生态服务过程与功能,重点阐明林窗对土壤碳氮分配、循环和固持,细根分解及根际效应等地下生态过程,以及对动植物与微生物生理生态学的影响与影响机制;同时,应进一步拓展研究的时空尺度,并加强地上与地下生态系统、生物与非生物因子、宏观与微观尺度等的整合研究。
Advances in studies of forest gap ecology .https://doi.org/10.11707/j.1001-7488.20160411 URL Magsci [本文引用: 1] 摘要
林窗是森林生态系统中的一种中小尺度干扰,是促进森林更新、养分循环、功能提高的重要推动力。本文阐述林窗生态学的研究进展与展望,以期为今后的林窗理论研究和森林经营实践提供参考。林窗生态学研究集中于林窗的形成、基本特征以及林窗对森林小气候和植物群落特征等地上结构与过程的影响;近年来,林窗对细根与枯落物分解、土壤碳氮动态及酶活性以及对森林动物和土壤微生物的生理生态学特征影响研究逐渐增多,但研究的时空尺度较小且不够全面、深入。今后应着重研究林窗如何调控林分结构和森林生态服务过程与功能,重点阐明林窗对土壤碳氮分配、循环和固持,细根分解及根际效应等地下生态过程,以及对动植物与微生物生理生态学的影响与影响机制;同时,应进一步拓展研究的时空尺度,并加强地上与地下生态系统、生物与非生物因子、宏观与微观尺度等的整合研究。
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Gap dynamics and regeneration strategies in Juniperus-Laurus forests of the Azores Islands [J].https://doi.org/10.1007/s11258-008-9442-x URL [本文引用: 1] 摘要
We asked the following questions regarding gap dynamics and regeneration strategies in Juniperus-Laurus forests: How important are gaps for the maintenance of tree diversity? What are the regeneration strategies of the tree species? Thirty canopy openings were randomly selected in the forest and in each the expanded gap area was delimited. Inside expanded gaps the distinction was made between gap and transition zone. In the 30 expanded gaps a plot, enclosing the gap and transition zone, was placed. In order to evaluate the differences in regeneration and size structure of tree species between forest and expanded gaps, 30 control plots were also delimited in the forest, near each expanded gap. In the 60 plots the number of seedlings, saplings, basal sprouts and adults of tree species were registered. Canopy height and width of adult individuals were also measured. The areas of the 30 gaps and expanded gaps were measured and the gap-maker identified. Juniperus-Laurus forests have a gap dynamic associated with small scale disturbances that cause the death, on average, of two trees, mainly of Juniperus brevifolia. Gap and expanded gap average dimensions are 8 and 25 m虏, respectively. Gaps are of major importance for the maintenance of tree diversity since they are fundamental for the regeneration of all species, with the exception of Ilex azorica. Three types of regeneration behaviour and five regeneration strategies were identified: (1) Juniperus brevifolia and Erica azorica are pioneer species that regenerate in gaps from seedlings recruited after gap formation. However, Juniperus brevifolia is a pioneer persistent species capable of maintaining it self in the forest due to a high longevity and biomass; (2) Laurus azorica and Frangula azorica are primary species that regenerate in gaps from seedlings or saplings recruited before gap formation but Laurus azorica is able to maintain it self in the forest through asexual regeneration thus being considered a primary persistent species; (3) Ilex azorica is a mature species that regenerates in the forest.
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Measuring tree height: a quantitative comparison of two common field methods in a moist tropical forest [J].https://doi.org/10.1111/2041-210X.12071 URL [本文引用: 1] |
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基于机载激光雷达的中亚热带常绿阔叶林林窗特征 [J].
<div style="line-height: 150%">机载激光雷达(LiDAR)是一种新型主动式遥感技术,能直接获取多尺度高精度的冠层三维结构信息,将其推广到森林干扰生态学领域,可为林窗研究提供应用支撑.以湖南中亚热带常绿阔叶林为研究对象,利用小光斑LiDAR数据进行林窗识别和几何特征估测.选择合适的分辨率和内插方法生成冠层高程模型,采用计算机图形学方法估测林窗面积、边界木高度和形状指数,并进行野外观测验证.结果表明: 林窗识别率为94.8%,主要影响因素是林窗面积和林窗形成木类型;估测的林窗面积和边界木高与野外观测值呈较强线性相关,R<sup>2</sup>值分别为0.962和0.878,其中估测的林窗面积平均比野外观测值高19.9%,估测的林窗边界木高度平均比野外观测值低9.9%;区域内林窗密度为12.8个·hm<sup>-2</sup>,占森林面积13.3%;林窗面积、边界木高和形状指数的平均值分别为85.06 m<sup>2</sup>、15.33 m和1.71,区域内多为较小面积、边缘效应不太显著的林窗.
Characterization of mid-subtropical evergreen broad-leaved forest gap based on light detection and ranging ( LiDAR) .
<div style="line-height: 150%">机载激光雷达(LiDAR)是一种新型主动式遥感技术,能直接获取多尺度高精度的冠层三维结构信息,将其推广到森林干扰生态学领域,可为林窗研究提供应用支撑.以湖南中亚热带常绿阔叶林为研究对象,利用小光斑LiDAR数据进行林窗识别和几何特征估测.选择合适的分辨率和内插方法生成冠层高程模型,采用计算机图形学方法估测林窗面积、边界木高度和形状指数,并进行野外观测验证.结果表明: 林窗识别率为94.8%,主要影响因素是林窗面积和林窗形成木类型;估测的林窗面积和边界木高与野外观测值呈较强线性相关,R<sup>2</sup>值分别为0.962和0.878,其中估测的林窗面积平均比野外观测值高19.9%,估测的林窗边界木高度平均比野外观测值低9.9%;区域内林窗密度为12.8个·hm<sup>-2</sup>,占森林面积13.3%;林窗面积、边界木高和形状指数的平均值分别为85.06 m<sup>2</sup>、15.33 m和1.71,区域内多为较小面积、边缘效应不太显著的林窗.
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鼎湖山南亚热带常绿阔叶林林窗分布格局及其成因 [J].https://doi.org/10.17520/biods.2017027 URL [本文引用: 1] 摘要
林窗数量特征及其空间分布格局对南亚热带森林生态系统的动态变化、物种共存及生物多样性的维持等具有重要意义。本文基于鼎湖山南亚热带常绿阔叶林20 ha动态监测样地2015年的植被调查数据,结合无人机航拍图像处理技术和地理信息系统,分析了样地内林窗的几何特征和空间分布格局。结果表明:该样地的林窗空隙率为13.72%,密度为35.75个/ha,平均面积38.37 m~2。具体特征有:(1)区域内林窗数量随林窗面积的增加呈负指数分布,整体表现为小林窗多、大林窗少的规律。(2)不同成熟度林分中,过熟林林窗平均面积大于成熟林;成熟林更能体现出小林窗多而大林窗少的特点。(3)各生境林窗分布与大样地整体表现出基本一致的规律,但低谷与其他生境差异显著,林窗平均面积、林窗空隙率等都大于其他生境,而山脊林窗也在林窗空隙率与林窗密度方面低于其他生境。(4)林窗面积和地形因子显著相关:与海拔和凹凸度呈显著负相关;与坡度和坡向呈显著正相关。据此提出建立利用无人机进行森林群落林冠变化与格局的监测体系,是实现林窗与林下群落动态变化同步监测的新手段。
Gap distribution patterns in the south subtropical evergreen broad-leaved forest of Dinghushan .https://doi.org/10.17520/biods.2017027 URL [本文引用: 1] 摘要
林窗数量特征及其空间分布格局对南亚热带森林生态系统的动态变化、物种共存及生物多样性的维持等具有重要意义。本文基于鼎湖山南亚热带常绿阔叶林20 ha动态监测样地2015年的植被调查数据,结合无人机航拍图像处理技术和地理信息系统,分析了样地内林窗的几何特征和空间分布格局。结果表明:该样地的林窗空隙率为13.72%,密度为35.75个/ha,平均面积38.37 m~2。具体特征有:(1)区域内林窗数量随林窗面积的增加呈负指数分布,整体表现为小林窗多、大林窗少的规律。(2)不同成熟度林分中,过熟林林窗平均面积大于成熟林;成熟林更能体现出小林窗多而大林窗少的特点。(3)各生境林窗分布与大样地整体表现出基本一致的规律,但低谷与其他生境差异显著,林窗平均面积、林窗空隙率等都大于其他生境,而山脊林窗也在林窗空隙率与林窗密度方面低于其他生境。(4)林窗面积和地形因子显著相关:与海拔和凹凸度呈显著负相关;与坡度和坡向呈显著正相关。据此提出建立利用无人机进行森林群落林冠变化与格局的监测体系,是实现林窗与林下群落动态变化同步监测的新手段。
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以湖南亚热带次生林为研究对象，利用多时相机载激光雷达（Light detection and ranging，LiDAR）和野外调查数据对林窗及幼树进行监测，分析比较林窗对幼树密度分布和树高生长变化的影响。结果表明，林窗大小和位置对幼树密度分布都有显著影响，喜光树种幼树主要集中在小林窗的中心区或大林窗的过渡区，在大林窗中密度最大（647株／hm^2），耐荫树种幼树主要集中在林窗的边缘区，在中等林窗中密度最大（941株／hm^2）。林窗大小对幼树树高生长有显著影响，喜光树种和耐荫树种幼树分别在大林窗和中等林窗中树高生长量最大（69．3cm／a、57．7cm／a），喜光树种幼树在中心区的树高生长量明显大于其他位置，耐荫树种幼树的树高生长量在位置上的差异不显著。线性混合模型分析显示林窗大小是促进幼树树高生长的最主要因素，幼树树高生长变化在不同林窗中呈聚集性。从幼树密度树高生长情况来看，50～150m^2林窗较适合促进亚热带次生林的群落演替。
Effect of canopy gap on subtropical secondary forest sapling regeneration based on LiDAR .https://doi.org/10.6041/j.issn.1000-1298.2017.03.025 URL [本文引用: 1] 摘要
以湖南亚热带次生林为研究对象，利用多时相机载激光雷达（Light detection and ranging，LiDAR）和野外调查数据对林窗及幼树进行监测，分析比较林窗对幼树密度分布和树高生长变化的影响。结果表明，林窗大小和位置对幼树密度分布都有显著影响，喜光树种幼树主要集中在小林窗的中心区或大林窗的过渡区，在大林窗中密度最大（647株／hm^2），耐荫树种幼树主要集中在林窗的边缘区，在中等林窗中密度最大（941株／hm^2）。林窗大小对幼树树高生长有显著影响，喜光树种和耐荫树种幼树分别在大林窗和中等林窗中树高生长量最大（69．3cm／a、57．7cm／a），喜光树种幼树在中心区的树高生长量明显大于其他位置，耐荫树种幼树的树高生长量在位置上的差异不显著。线性混合模型分析显示林窗大小是促进幼树树高生长的最主要因素，幼树树高生长变化在不同林窗中呈聚集性。从幼树密度树高生长情况来看，50～150m^2林窗较适合促进亚热带次生林的群落演替。
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Identification of gaps in mangrove forests with air borne LIDAR [J].https://doi.org/10.1016/j.rse.2007.10.003 URL [本文引用: 1] 摘要
Mangrove forests change frequently due to disturbances from tropical storms, frost, lightning, and insects. It has been suggested that the death and regeneration of trees in small gaps due to lightning may play a critical role in mangrove forest turnover; however, the large-scale quantification of spatial pattern and areas of gaps is lacking for investigating this issue. Airborne light detection and ranging (LIDAR) technology provides an effective way for identifying gaps by remotely obtaining direct measurements of ground and canopy elevations. A method based on an alternative sequential filter and black top-hat mathematical morphological transformation was developed to extract gap features. Comparison of identified gap polygons with raw LIDAR measurements and field surveys shows that the proposed method successfully extracted gap features in mangrove forests in Everglades National Park. There are 400–500 lightning gaps per square kilometer in mangrove forests at the study sites. The distribution of gap sizes follows an exponential form and the area of gaps with sizes larger than 10002m2 account for 55–61% of the total area of gaps. The area of gaps in the mangrove forest in Everglades National Park is about 4–5% of the total forest area and the average gap formation rate is about 0.3% of the total forest area per year, indicating that lightning gaps play an important role in mangrove forest dynamics.
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Retrieving the gap fraction, element clumping index, and leaf area index of individual trees using single-scan data from a terrestrial laser scanner [J].https://doi.org/10.1016/j.isprsjprs.2017.06.006 URL [本文引用: 1] |
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Remote sensing of forest pest damage: a review and lessons learned from a Canadian perspective [J].https://doi.org/10.4039/tce.2016.11 URL [本文引用: 1] 摘要
Outbreaks of insect pests periodically cause large losses of volume in Canadas vast forest-land base. Remote sensing can augment these methods and extend monitoring capabilities in time and space by incorporating knowledge of pest-host interactions and of how damage translates into a remote sensing signal for detection and mapping. This review provides a brief introduction to major forest insect pests in Canada (two bark beetles (Coleoptera: Curculionidae) and six defoliators) and the damage they cause, a synthesis of the literature involving aerial survey and remote sensing, and a discussion of how these two approaches could be integrated into future pest monitoring from a Canadian perspective. We offer some lessons learned, outline roles that remote sensing could serve in a management context, and discuss what ongoing and upcoming technological advances may offer to future forest health monitoring.
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The progress of operational forest fire monitoring with infrared remote sensing [J].https://doi.org/10.1007/s11676-016-0361-8 URL [本文引用: 1] |
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森林垂直结构参数遥感反演综述 [J].https://doi.org/10.11834/jrs.20132183 Magsci [本文引用: 1] 摘要
随着遥感技术的发展,林业遥感从早期森林分类制图的定性研究,逐步发展到森林整体特性的遥感定量反演研究。目前利用遥感反演的森林叶面积指数、生物量、叶绿素浓度、碳储量等参数以描述森林生化理化特征、水平结构特征为主,而描述森林垂直结构的参数较少。本文针对不同高度处森林的叶面积密度和冠层垂直高度廓线参数,综述了遥感获取森林垂直结构参数的方法以及典型地表类型的垂直结构参数曲线,并总结了森林垂直结构参数提取方法中存在的问题,探讨未来研究方向。
Review of forest vertical structure parameter inversion based on remote sensing technology .https://doi.org/10.11834/jrs.20132183 Magsci [本文引用: 1] 摘要
随着遥感技术的发展,林业遥感从早期森林分类制图的定性研究,逐步发展到森林整体特性的遥感定量反演研究。目前利用遥感反演的森林叶面积指数、生物量、叶绿素浓度、碳储量等参数以描述森林生化理化特征、水平结构特征为主,而描述森林垂直结构的参数较少。本文针对不同高度处森林的叶面积密度和冠层垂直高度廓线参数,综述了遥感获取森林垂直结构参数的方法以及典型地表类型的垂直结构参数曲线,并总结了森林垂直结构参数提取方法中存在的问题,探讨未来研究方向。
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Introduction to forestry applications of airborne laser scanning [J].https://doi.org/10.1007/978-94-017-8663-8_1 URL [本文引用: 1] 摘要
Airborne laser scanning (ALS) has emerged as one of the most promising remote sensing technologies to provide data for research and operational applications in a wide range of disciplines related to management of forest ecosystems. This chapter starts with a brief historical overview of the early forest-related research on airborne Light Detection and Ranging which was first mentioned in the literature in the mid-1960s. The early applications of ALS in the mid-1990s are also reviewed. The two fundamental approaches to use of ALS in forestry applications are presented the area-based approach and the single-tree approach. Many of the remaining chapters rest upon this basic description of these two approaches. Finally, a brief introduction to the broad range of forestry applications of ALS is given and references are provided to individual chapters that treat the different topics in more depth. Most chapters include detailed reviews of previous research and the state-of-the-art in the various topic areas. Thus, this book provides a unique collection of in-depth reviews and overviews of the research and application of ALS in a broad range of forest-related disciplines.
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Quantifying and mapping multiple ecosystem services change in West Africa [J].https://doi.org/10.1016/j.agee.2012.12.001 URL [本文引用: 1] 摘要
Although ecosystem services have been identified to be declining over the previous decades, there is no clear methodology of evaluating the impacts of land use change on ecosystem services. This paper presents a methodology for quantifying and assessing changes in multiple ecosystems services as a result of land use change using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. The model was used to map and quantify biodiversity and four ecosystem services for Ghana and Cote d’Ivoire for 2000, 2005 and 2009 land use conditions: water yield, carbon storage, nutrient retention, and sediment retention. The study developed a suite of indices to analyze land use change impacts on the status, change and spatial patterns of multiple ecosystem services. On a national scale, the results show a mix of increases in service (water yield, N retention and P retention in Ghana, and, N and P retention in Cote d’Ivoire), little change in services (sediment retention in Ghana and sediment retention and water yield in Cote d’Ivoire) and decreases in services (biodiversity and carbon storage in both countries) from 2000 to 2009. The assessment illustrates a methodology that can be employed by land managers in exploring multiple management scenarios and their implications for multiple ecosystem services change.
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基于生态过程模型和森林清查数据的森林生长量估算对比研究 [J].https://doi.org/10.3969/j.issn.1674-5906.2013.10.002 URL [本文引用: 1] 摘要
利用遥感驱动的生态过程模型-Boreal Ecosystem Productivity Simulator(BEPS)、2001-2006年国家森林资源连续清查数据(一类清查-样地尺度)和2003-2009年森林资源规划设计调查数据(二类调查-区域尺度),分别计算江西省吉安市的森林生态系统生长量,从不同空间尺度和森林类型对3种数据源估算的森林生长量进行了分析。结果表明,样点尺度上,BEPS模型模拟的森林生长量(4.18 Mg·hm-2·a-1)低于群落生长量(5.86 Mg·hm-2·a-1),与乔木层生长量(4.29 Mg·hm-2·a-1)基本一致,模型模拟结果与两者的拟合R2分别为0.48和0.43。区域尺度上,BEPS模型模拟、二类调查数据计算的群落及乔木层生长量分别为4.65、4.36和3.34 Mg·hm-2·a-1,BEPS模型估算的吉安市各县森林总生长量与二类调查数据计算的群落、乔木层生长总量拟合R2分别达0.84和0.83。一类清查数据计算结果高于二类清查数据计算结果,BEPS模型模拟森林生长量分别与基于一类清查数据计算的乔木层生长量及二类调查数据群落生长量较为一致。从研究区两种主要森林类型来看,常绿阔叶林年平均生长量高于常绿针叶林,常绿针叶林与模型估算结果差异小于常绿阔叶林。最后利用模型估算了研究区2001-2010年平均生长量,为认识研究区的森林生长空间分布差异及更新森林生物量提供支持。
Comparison of estimated forest biomass increment rate based on a process-based ecological model and forest inventory data .https://doi.org/10.3969/j.issn.1674-5906.2013.10.002 URL [本文引用: 1] 摘要
利用遥感驱动的生态过程模型-Boreal Ecosystem Productivity Simulator(BEPS)、2001-2006年国家森林资源连续清查数据(一类清查-样地尺度)和2003-2009年森林资源规划设计调查数据(二类调查-区域尺度),分别计算江西省吉安市的森林生态系统生长量,从不同空间尺度和森林类型对3种数据源估算的森林生长量进行了分析。结果表明,样点尺度上,BEPS模型模拟的森林生长量(4.18 Mg·hm-2·a-1)低于群落生长量(5.86 Mg·hm-2·a-1),与乔木层生长量(4.29 Mg·hm-2·a-1)基本一致,模型模拟结果与两者的拟合R2分别为0.48和0.43。区域尺度上,BEPS模型模拟、二类调查数据计算的群落及乔木层生长量分别为4.65、4.36和3.34 Mg·hm-2·a-1,BEPS模型估算的吉安市各县森林总生长量与二类调查数据计算的群落、乔木层生长总量拟合R2分别达0.84和0.83。一类清查数据计算结果高于二类清查数据计算结果,BEPS模型模拟森林生长量分别与基于一类清查数据计算的乔木层生长量及二类调查数据群落生长量较为一致。从研究区两种主要森林类型来看,常绿阔叶林年平均生长量高于常绿针叶林,常绿针叶林与模型估算结果差异小于常绿阔叶林。最后利用模型估算了研究区2001-2010年平均生长量,为认识研究区的森林生长空间分布差异及更新森林生物量提供支持。
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Three-dimensional coherent radar backscatter model and simulations of scattering phase center of forest canopies [J].https://doi.org/10.1109/TGRS.2009.2024301 URL [本文引用: 1] |
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