地理科学 ›› 2016, Vol. 36 ›› Issue (1): 135-141.doi: 10.13249/j.cnki.sgs.2016.01.017

• 研究论文 • 上一篇    下一篇

基于减小叶片水分影响的湿地芦苇氮浓度高光谱反演研究

王莉雯(), 卫亚星   

  1. 辽宁师范大学海洋经济与可持续发展研究中心 辽宁师范大学自然地理与空间信息科学辽宁省重点实验室 辽宁师范大学城市与环境学院, 辽宁 大连 116029
  • 收稿日期:2014-12-11 修回日期:2015-03-10 出版日期:2016-01-20 发布日期:2016-01-20
  • 作者简介:

    作者简介:王莉雯(1971-),女,山东蓬莱人,副教授,博士,研究领域为遥感和地理信息系统应用。E-mail: wlw9585@163.com

  • 基金资助:
    国家自然科学基金(41271421)、教育部人文社会科学研究规划基金(14YJA630064)、教育部人文社会科学研究青年基金项目(10YJCZH156)资助

Estimating Nitrogen Concentrations in Wetland Reeds Based on Reducing Foliar Water Effect by Hyperspectral Data

Liwen Wang(), Yaxing Wei   

  1. College of Urban and Environmental Science, Liaoning Normal University, Dalian 116029, Liaoning, China
  • Received:2014-12-11 Revised:2015-03-10 Online:2016-01-20 Published:2016-01-20
  • Supported by:
    National Natural Science Foundation of China (41271421), The Humanities and Social Sciences Planning Fund Research Project of the Ministry of Education in China (14YJA630064), The Humanities and Social Sciences Youth Fund Research Project of the Ministry of Education in China (10YJCZH156)

摘要:

以盘锦双台河口湿地国家级自然保护区作为研究区,采用基于bootstrap的偏最小二乘回归模型(PLSR),分别构建不同光谱变换技术(包括光谱水分影响减小技术WR、包络线去除CR、光谱一阶微分FD、光谱倒数的对数LR)和原光谱数据(R)的芦苇叶片氮浓度预测模型。使用变量投影重要性指标VIP,计算了各光谱波段在估算芦苇叶片氮浓度时的重要性。研究结果表明,WR光谱变换技术的芦苇叶片氮浓度估算精度最高(R2=0.87,均方根误差=0.57),该方法可以有效减小叶片水分的影响,增强鲜叶片光谱中细微的氮吸收特征。

关键词: 叶片氮浓度, 叶片水分影响, 光谱变换技术, 高光谱分辨率, 湿地植被

Abstract:

The high-accuracy quantitative inversions of foliar nitrogen concentrations in wetland plants from hyperspectral data contribute to make the advanced comprehensions of wetland ecosystem functioning, biochemical processes and nitrogen circles. The study area in this paper was located in the Panjin Shuangtaihekou Wetland National Nature Reserve Administration. The wetland was mainly dominated by phragmites australis (Cav.) Trin. ex Steud with an area of 900 km2. Foliar spectral reflectance data were measured using an ASD spectroradiometer (FieldSpec Pro FR) with a 25° field-of-view (FOV) and a spectral range of 350 to 2 500 nm. Subsequently, sampling reeds at each plot were cut at ground level and sent immediately to the laboratory. The nitrogen concentration of the vegetation was measured using a standard method of the Kjeldahl technique. Based on the different spectral transformation techniques and original spectral data (R), partial least-squares regressions (PLSR) integrating with the bootstrapping approaches were used to develop the prediction models of nitrogen concentrations in reedleaves. The set of spectral transformation techniques used in this study included the water removal (WR), continuum removal (CR), first derivative (FD), and reciprocal-logarithm transformation (LR). The variable importance of projection (VIP) was used as a metric to quantify the important degree of a spectral band for estimating foliar nitrogen concentrations with the various spectral transformation techniques. The results indicated that WR spectral transformation in combination with PLSR estimated foliar nitrogen concentration with the highest accuracy (R2=0.87,RMSE=0.57). The WR approachcan effectively reduce the water absorption effects on the subtle nitrogen absorption features across the fresh leaf spectrum. This study demonstrated the performance of the WR technique in increasing the accuracy of foliar nitrogen estimation for wetland plants. The estimation accuracies achieved from the applications of all spectral transformation techniques were higher compared to the original spectral data. The selected feature bands for estimating foliar nitrogen concentrations from the WR technique were all centered at the shortwave infrared (SWIR) spectral region, and forty percent (40%) of the selected bands from WR were associated with known nitrogen estimation bands. While, the selected feature bands from other spectral transformation techniques were located in both the SWIR and visible near-infrared (VNIR) spectral region. Phenology plays an important role in foliar nitrogen estimation using spectroscopy data. Therefore, there is a need for the future studies for understanding how phenology influences the performance of the WR technique in estimating foliar nitrogen concentrations in wetland plants.

Key words: foliar nitrogen concentration, foliar water effect, spectral transformation techniques, hyperspectral, wetland vegetation

中图分类号: 

  • X144