L波段多角度微波植被指数研究

DTM Extraction from ALS Data in Densely Vegetated Slopes Using Wavelet Algorithm

植被指数是卫星遥感领域中用来表征地表植被覆盖,生长状况的一个简单有效的度量参数。通常由于植被光谱受到植被本身、环境条件、大气状况等多种因素的影响,植被指数往往具有明显的区域性和时效性。微波遥感具有全天时、全天候的工作能力,利用被动微波遥感观测数据建立植被指数,将能够弥补现有植被指数的局限性。2009年发射的土壤水分和海洋盐度(SMOS)卫星首次采用L波段多角度微波观测。通过双极化多角度微波辐射信号组合,可以最小化地表辐射的影响,从而发展了仅与植被参数有关的微波植被指数。这种方法为SMOS监测全球植被信息提供新的机会。

Vegetation index is a simple and effective parameter which can be used for characterization of surface vegetation cover and growth in the field of satellite remote sensing.Usually vegetation index has the regional character and time limit because of been affected by environmental,atmospheric conditions and other factors.Microwave remote sensing has capability to work of all-weather;the use of passive microwave remote sensing vegetation index,will be able to compensate for the limitations of existing vegetation index.Soil moisture and ocean salinity （SMOS） Satellite scheduled for launch in 2009,will be the first multi-angle L-band microwave observations.Through many dual-polarized microwave radiation signal combinations,we can minimize the effects of surface radiation and thus develop the microwave vegetation index,which only related with the vegetation parameters.This method will provide new opportunities for SMOS to monitor the global vegetation information.