期刊文献+

玉米地组分亮度温度分类变化研究 被引量:7

Study on the Classification of Component Brightness Temperature Over a Maize Canopy
下载PDF
导出
摘要 以玉米整个生长期野外热红外辐射观测数据为基础,对两种组分亮温分类方法作了比较,并对玉米地组分亮温的变化特征展开了分析。结果表明,农田亮温组分的数目和数值随测量时间和日期改变。在整个测量期间,在当地时间中午前后,农田呈现出3个亮温组分植被、被阳光照到的亮土和植被阴影下的暗土。观测早期,植被亮温分布相对集中;随着农田植被覆盖率的增高,植被亮温分布逐步分散,组分间温差缩小,部分亮温值相互重叠。产生这些现象的原因将在以后的研究中加以探讨。 This paper researches on the methodology for brightness temperature component classification and temporal variations of these component values by an in situ experiment dedicated to maize canopy brightness temperature distribution. Results show the number of components and their brightness temperature values vary with time of day and biomass density. Three components of vegetation, sunlit and shaded soil could be identified at midday during the measuring period. When the canopy is highly co-vered, vegetation's brightness temperature has a wider range, and the components are difficult to be distinguished. The interpretation of these phenomena will be conceived in the further research.
出处 《遥感学报》 EI CSCD 北大核心 2005年第1期16-23,共8页 NATIONAL REMOTE SENSING BULLETIN
基金 法国农科院奖学金 自然科学基金(40371088) 国家重点基础研究发展规划项目(G2000077902) 国家高技术研究发展计划项目(2002AA130010) 中国科学院知识创新工程领域前沿项目资助(CX020011)。
关键词 玉米地 组分亮温 分类 maize canopy classification component brightness temperature
  • 相关文献

参考文献16

  • 1Friedl M A. Modeling land surface fluxes using a sparse canopy mo-del and radiometric temperature measurements[J]. Journal of geophysics research, 1985,100(D12):25435-25446.
  • 2Jackson R D, Reginato R J, Pinter P J J, Idso S B, Plant canopy information extraction from composite scene reflectance of row crops[J], Applied Optics, 1979,18: 3775-3782.
  • 3Weiss M, Baret F, Leroy M, Bégué A, Hautecoeur O, Santer R. Hemisphrical reflectance and albedo estimation from the accumulation of across-track sun-synchronous satellite data[J]. Journal of Geophysical Research, 1999,104(D18): 22221-22232.
  • 4Vining R C, Blad B L. Estimation of sensible heat flux from remotely sensed canopy temperatures[J], Journal of Geophysical Research, 1992,97(D17):18951-18954.
  • 5Moran M S, Clarke T R, Inove Y, Vidal A. Estimating crop water deficit using the relationship between surface-air temperature and spectral vegetation index [J]. Remote Sensing of Environment, 1994,49:246-263.
  • 6Norman J M, Divakarla M, Goel N S. Algorithms for extracting information from remote thermal-IR observations of the earth's surface [J]. Remote Sensing of Environment. 1995,51: 157-168.
  • 7Kimes D S, Remote sensing of row crop structure and component temperatures using directional radiometric temperatures and inversion technique[J]. Remote Sensing of Environment. 1983,13:33-55.
  • 8Kustas W P. Ground and aircraft infrared observations over a partially-vegetated area[J]. International Journal of Remote Sensing, 1990,11: 409-427.
  • 9Francois C, Ottlé C, Prévot L. Analytical parameterization of canopy directional emissivity and directional radiance in the thermal infrared. Application on the retrieval of soil and foliage temperature using two directional measurements[J]. International Journal of Remote Sensing, 1997,12: 2587-2621.
  • 10Anthoni P M, Beverly E L, Michael H U, Richard J V. Variation of net radiation over heterogeneous surface: measurements and simulation in a juniper-sagebrush ecosystem[J]. Agricultural and Forest Meteorology. 2000,102: 275-286.

同被引文献78

引证文献7

二级引证文献32

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