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遥感学报  2003 

Analysis of Seasonal Change of Land Cover Characteristics with SSM/I Data in China
SSM/I微波辐射计数据中国陆地覆盖特征季节变化分析

Keywords: SSM/I,microwave radiometer,multi,temporal,NDPI,land cover characteristics,land cover change
SSM/I微波辐射计
,归一化极化指数,陆地覆盖,多时相

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Abstract:

By processing and analyzing space borne multi frequency microwave radiometry data acquired by SSM/I in different time, we aim at carrying out research on seasonal change of land cover characteristics in China. Through a short review on passive microwave remote sensing applications,we choose Normalized polarization index( NDPI ) to describe land cover characteristics. Because NDPI is independent of surface temperature, it diminishes difference caused by acquiring time in data in various regions. It is also shown that NDPI is actually a normalized emissivity of different polarization. Its main influence factors are vegetation biomass and soil surface moisture. With biomass increasing, NDPI becomes smaller;with soil moisture increasing, NDPI increases also. Multi frequency SSM/I data acquired in April,July,October of 1997 and January of 1998(20 th and 24 th of every month )were processed and analyzed. Then the SSM/I NDPI maps over land in China were put forward for the first time. These maps express seasonal change of land cover characteristics in China. By analyzing all of these data and maps, we found that specific land cover has specific NDPI value and NDPI value changes with season.It is concluded that the NDPI maps has great potential to monitor land cover characteristics. The general trend of NDPI is (from high to low):desert, semi desert, plateau(grassland), agricultural region and forest .The research illustrates that 19GHz NDPI is a good indicator of seasonal change of land cover characteristics. This paper also provides a new method to research on global change (such as vegetation and soil moisture change) because we have demonstrated in the paper that a NDPI map covering all of China can be formed by using only two day's SSM/I data,and furthermore, this map is affected little by cloud and is independent of surface temperatrue.

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