地理科学 ›› 2019, Vol. 39 ›› Issue (3): 367-376.doi: 10.13249/j.cnki.sgs.2019.03.002

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定量遥感尺度转换方法研究进展

姚远1,3,4(), 陈曦1,4, 钱静1,2()   

  1. 1.中国科学院新疆生态与地理研究所荒漠与绿洲生态国家重点实验室,新疆 乌鲁木齐 830011
    2. 中国科学院深圳先进技术研究院,广东 深圳 518055
    3. 中国科学院大学,北京 100049
    4. 中国科学院中亚生态与环境研究中心,新疆 乌鲁木齐 830011
  • 收稿日期:2018-03-05 修回日期:2018-07-18 出版日期:2019-03-10 发布日期:2019-03-10
  • 作者简介:

    作者简介:姚远(1987-),男,新疆乌鲁木齐人,博士研究生,主要从事干旱区资源遥感研究。E-mail: xinjiangyaoyuan@sina.com

  • 基金资助:
    中国科学院A类战略性先导科技专项(XDA20060303)、中国科学院“西部之光”人才培养引进计划青年学者A类项目(2016-QNXZ-A-5)、国家自然科学基金项目(41761144079)、深圳国际合作研究项目(GJHZ20160229194322570)和广东省省级科技计划项目(2017A050501027)资助

A Review on the Methodology of Scale Issues in Quantitative Remote Sensing

Yuan Yao1,3,4(), Xi Chen1,4, Jing Qian1,2()   

  1. 1. State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, Xinjiang, China
    2. Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, Guangdong, China
    3. University of Chinese Academy of Sciences, Beijing 100049, Beijing, China
    4. Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi 830011, Xinjiang, China
  • Received:2018-03-05 Revised:2018-07-18 Online:2019-03-10 Published:2019-03-10
  • Supported by:
    The Strategic Priority Research Program of Chinese Academy of Sciencess (XDA20060303), Chinese Academy of Sciences “Light of West China” Program (2016-QNXZ-A-5), National Natural Science Foundation of China (41761144079) , Shenzhen International S&T Cooperation Project (GJHZ20160229194322570) and Science and Technology Planning Project of Guangdong Province (2017A050501027)

摘要:

首先对遥感科学和气象学、水文学、生态学、地理学和的尺度概念及其转换方法进行了区分。其次对遥感数据空间尺度转换方法的国内外研究进展情况进行了系统梳理,重点比对了目前空间尺度转换常用6种转换方法:统计转换法、分类转换法、数据融合转换方法、分形分析法、基于局域动态模型的转换方法和基于物理意义尺度转换方法及其各自所属方法的优点和缺点。再次以遥感时间尺度转换应用最为广泛的地表蒸散发和农业旱情监测等2个领域为例,对遥感时间尺度转换方法进行了总结。最后预测了今后定量遥感尺度转换研究可能的研究重点,以期为今后更好地开展尺度效应和尺度转换研究工作提供参考。

关键词: 定量遥感, 尺度效应, 尺度转换, 时间尺度, 空间尺度

Abstract:

The advance of remote sensing technology provides an effective way for disaster prediction, environmental monitoring, resource surveys. Remote sensing technology has become a effective tools to get geo-information comprehensively, accurately, and quickly. Undoubtedly, remote sensing technology in the 21th century has entered an era of quantitative analysis. Thus, the scale issues have always attracted increasing the attention in quantitative remote sensing owing to scale effects limite the accuracy of retrieval the development of its applications. It is a significant problem in remote sensing research, and the methods of scale transformation have been proved is useful to resolve this problem. In ordert to study the scale issues of remote sensing, the advances in methodology of scale issues in quantitative remote sensing must be discussed. Firstly, as we know, the concept of scale is now suffering from a discrepancy in different research area, such as remote sensing, meteorology, hydrology, ecology and geography. Therefore, the definition of scale and relevant methodology in above mentioned research area are introduced in the first of this paper. Secondly, in reviewing the scale issues in remote sensing, the approaches for spatial and temporal scale transformation are reviewed. We summarize the advanges and disadvantages of the mainly spatial scale transformation methods, such as statistical transformation method, classification transformation method, data fusion transformation method, fractal analysis method, local dynamic model based scaling approach and scale transformation method based on physical meaning. Thirdly, the application of measured vapotranspiration and agricultural drought are restricted by remotely sensed data owing to the direct result are instantaneous value estimated at the passing time of satellite. Consequently, different time scales values have practiacal significance. We have summarized many remote sensing data time scale extrapolation methods. The results obtained show that each method has its own advantages and disadvantages. Finally, the future research directions were equally proposed in order to provide a reference for future researchers interested in quantitative remote sensing.

Key words: quantitative remote sensing, scale effect, scale transformation, spatial scale, temporal scale

中图分类号: 

  • P237