期刊文献+

国际草地资源遥感研究新进展 被引量:48

Most Recent Progress of International Research on Remote Sensing of Grassland Resources
下载PDF
导出
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。 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.
出处 《地理科学进展》 CSCD 北大核心 2003年第6期607-617,共11页 Progress in Geography
基金 国家自然科学基金资助项目(49971056)
关键词 遥感 草地资源 植被指数 生物量 GIS 变化监测 remote sensing grassland resources vegetation index biomass GIS change detection
  • 相关文献

参考文献75

  • 1Tueller P T. Remote sensing technology for rangeland management applications. Journal of Range Management,1989, 42 (6): 442~453.
  • 2Schmidt K S, Skidmore A K. Exploring spectral discrimination of grass species in African rangelands. International Journal of Remote Sensing, 2001, 22 (17): 3421~ 3434.
  • 3Bork E W, West N E, Price K P, et al. Rangeland cover component quantification using broad (TM) and narrow ~band (1.4 NM) spectrometry. Journal of Range Management, 1999, 52 (3): 249~257.
  • 4Mino N, Saito G, Ogawa S. Satellite monitoring of changes in improved grassland management. International Journal of Remote Sensing, 1998, 19 (3): 439~452.
  • 5Williamson H D. Developing a methodology for estimating grassland variables with remotely sensed data. Area,1992, 24 (1): 36~44.
  • 6McAdam J H. High and low resolution TM data for the assessment of herbage and sward characteristics in small fields. International Journal of Remote Sensing, 1997, 18 (14): 3027~3037.
  • 7Lewis M, Jooste V, de Gasparis A A. Discrimination of arid vegetation with airborne multispectral scanner hyperspectral imagery. IEEE Transactions on Geoscience and Remote Sensing, 2001, 39 (7): 1471~1479.
  • 8Lewis M. Discrimination of arid vegetation composition with high resolution CASI imagery. Rangeland Journal,2000, 22 (1): 141~167.
  • 9Paruelo J M, Golluscio R A. Range assessment using remote sensing in Northwest Patagonia (Argentina). Journal of Range Management, 1994, 47 (6): 498~502.
  • 10Prince S D, Astle, W L. Satellite remote sensing of rangelands in Botswama I: Landsat MSS and herbaceous vegetation. International Journal of Remote Sensing, 1986, 7 (11): 1533~1553.

同被引文献711

引证文献48

二级引证文献823

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部