Abstract

LAI is the more important parameter of vegetation canopy, so LAI inversion from remote sensing observations is the hot study field, especially for the high spatial and high temporal resolution remote sensing data. Beijing-1 microsatellite is an applied earth observing microsatellite of China, which can also give us the good data of short cycle time and wider coverage. So it is necessary to generate the quantitative product of BJ-1 remote sensing data. In this paper, the main object is to study on the method of the leaf area index inversion for producing BJ-1 LAI product. The neuronal network method is used to get the relationship between LAI and reflectance in green, red and NIR band. Based on the BJ-1 LAI inversion, the second object of this paper is to generate of high spatial and high temporal resolution LAI product. A method is proposed to get high spatial and temporal resolution LAI product by fusing the time-series MODIS LAI product(1 km, 8-day product)and BJ-1 LAI. Through this study, we can get the LAI products of BJ-1, which is with the high spatial resolution and high time resolution. This product will provide more information of vegetation for BJ-1 microsatellite data applications.

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