期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2008
卷号：XXXVII Part B1
页码：949-956
出版社：Copernicus Publications
摘要：LAI (Leaf Area Index) is the more important parameter of vegetation canopy, which can depict their growth course. 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. Because of no on-board calibration for BJ-1 multi-spectral images, we can't get the reflectance data, but DN values. Therefore, we get the VI from BJ-1 multi-spectral data. And from analyzing some VIs, we take NDVI as the good index for the LAI estimation. In order to retrieve the leaf area index (LAI), the BRDF forward model is used to simulate the relationship between LAI and NDVI. 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．In this method，the BJ-1 classification image is used to register with MODIS data, then the percentage of classes of FPT classification in the MODIS pixel can be calculated, and the time-series LAI at every classes can be obtained through linear unmixing．At last，the BJ-1 LAI is used to adjust this curve of time-series LAI to estimate the LAI at high spatial and temporal resolution．Through this study, we can get the LAI products of BJ-1, which is with the high spatial resolution and high time resolution (32m, 4-day product). This product will provide more information of vegetation for BJ-1 microsatellite data applications.
