地理科学进展 ›› 2003, Vol. 22 ›› Issue (6): 607-617.doi: 10.11820/dlkxjz.2003.06.009

• 论文 • 上一篇    下一篇

国际草地资源遥感研究新进展

查勇1, Jay Gao2, 倪绍祥1   

  1. 1. 南京师范大学地理科学学院,江苏南京210097;
    2. School of Geography and Environmental Science,University of Auckland,,Auckland,New Zealand
  • 收稿日期:2003-04-01 修回日期:2003-07-01 出版日期:2003-11-25 发布日期:2003-11-25
  • 作者简介:查勇(1963-),男,安徽铜陵人,南京师范大学地理科学学院副教授,主要从事遥感信息技术应用研究,在国内外发表论文30余篇,SC I收录4篇。
  • 基金资助:

    国家自然科学基金资助项目(49971056)

Most Recent Progress of International Research on Remote Sensing of Grassland Resources

ZHA Yong1, GAO Jay2, NI Shaoxiang1   

  1. 1. School of Geographic science, Nanjing Normal University, Nanjing 210097 ,China;
    2. School of Geography and Environmental Science, University of Auckland, Auckland, New Zealand
  • Received:2003-04-01 Revised:2003-07-01 Online:2003-11-25 Published:2003-11-25

摘要: 系统地评论了国际上有关草地资源遥感研究的最近文献。首先,分析了草地遥感的可行性,确定了监测和评估草地资源最有效的光谱波段,阐述了各种遥感影像在草地资源调查与评估中的实用价值。之后,介绍了草地资源遥感的常用方法,即植被指数和其他指数法,对比和分析了各种指数在草地资源遥感应用中的有效性及应用范围。这些草地资源遥感的应用包括草地盖度监测与制图、生物量估算、草地退化监测及草地资源定量分析。最后,探讨了草地资源遥感的发展趋势,包括摄像遥感、高分辨率影像(如CASI,AVIRIS和IKONOS)和GPS的运用。此外,GIS的引入及其与数字影像处理的集合会使草地资源遥感由简单监测逐渐向动态预报和模拟过渡。这些研究新动向对国内相关科学家在选题时具有极大的参考意义。

关键词: GIS, 变化监测, 草地资源, 生物量, 遥感, 植被指数

Abstract: In this paper the progress of research on remotely sensing grassland is comprehensively reviewed through examination of the most recent international literature. First, the feasibility of using remotely sensed data to study grassland is discussed on the basis of its unique spectral reflectance. The most useful spectral bands for the monitoring and assessment of grassland resources are identified next. The common method of studying grassland through the use of vegetation index and other indices is assessed for their effectiveness. The applications of remote sensing in grassland studies, including monitoring and mapping of grassland cover, estimation of biomass, and degradation, are reviewed next. Of these applications, the most challenging is quantitative analysis of grassland resources. This paper then concentrates on the recent trends in remote sensing of grassland. They include use of videography and other air-borne high-resolution image data, digital image analysis, and GIS. It is anticipated that as remote sensing of grassland evolves from simple monitoring and assessment to dynamic modeling, GIS will play an increasingly important role in integrating diverse data into a common database to generate accurate results. The introduction of GIS will make remote sensing of grassland resources more predictive in nature.

Key words: biomass, change detection, GIS, grassland resources, remote sensing, vegetation index

中图分类号: 

  • P237