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叶面积指数(Leaf Area Index,LAI)是定量研究陆地生态系统物质和能量交换的一个重要结构参数,具有重要的研究意义。针对HJ-1A卫星HSI数据,利用野外实测LAI值,探讨利用HJ-1A星HSI数据反演叶面积指数的可行性。选用比值植被指数(RVI)、归一化植被指数(NDVI)及改良型土壤调整植被指数(MSAVI)3种植被指数,与实测叶面积指数进行回归分析,构建回归模型。研究结果表明,基于影像提取的RVI、NDVI和MSAVI 3种植被指数均与叶面积指数有较好的定量关系。其中,MSAVI的拟合结果最优,其回归确定性系数为0.622。验证模型的确定性系数为0.547,均方根误差RMSE为0.202,说明实测和模拟LAI值之间具有较好的变化一致性。最后基于HJ-1A星HSI影像和MSAVI的估测模型生成研究区叶面积指数空间分布图。
Leaf Area Index (LAI) is an important structural parameter for the quantitative study of the exchange of matter and energy in terrestrial ecosystems. It has important research significance. According to the HSI data of HJ-1A satellite, the field measured LAI values were used to explore the feasibility of using HSI-HSI star HSI data to retrieve leaf area index. The vegetation index (RVI), normalized vegetation index (NDVI) and modified soil adjustment vegetation index (MSAVI) were selected to conduct regression analysis with the measured leaf area index to construct a regression model. The results showed that the three vegetation indices of RVI, NDVI and MSAVI based on image extraction had a good quantitative relationship with leaf area index. Among them, MSAVI has the best fitting result, and the regression coefficient of determination is 0.622. The validation coefficient of the validation model is 0.547, and the root mean square error RMSE is 0.202, which shows that there is a good consistency between measured and simulated LAI values. Finally, based on the HJ-1A satellite HSI images and the MSAVI estimation model, the leaf area index spatial distribution map of the study area was generated.