文献类型： 外文期刊

第一作者： Mao Zhi-Hui

作者： Mao Zhi-Hui;Deng Lei;Duan Fu-Zhou;Qiao Dan-Yu;Deng Lei;Duan Fu-Zhou;Li Xiao-Juan;Li Xiao-Juan;Mao Zhi-Hui

作者机构： Capital Normal Univ, Coll Resource Environm & Tourism, Beijing 100048, Peoples R China;Capital Normal Univ, Key Lab Resource Environm & GIS Beijing, Beijing 100048, Peoples R China;Capital Normal Univ, State Key Lab Incubat Base Urban Environm Proc &, Beijing 100048, Peoples R China;Chinese Acad Fishery Sci, Resource & Environm Res Ctr, Beijing 100141, Peoples R China

关键词： Vegetation index; BRDF; SPAD; Angle effect; Multi-angular hyperspectral remote sensing; Unmanned aerial vehicle

期刊名称：INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION （ 2020影响因子：5.933； 五年影响因子：6.225 ）

ISSN： 1569-8432

年卷期： 2020 年 93 卷

页码：

收录情况： SCI

摘要： To study the anisotropy of vegetation indices (VIs) and explore its influence on the retrieval accuracy of canopy soil-plant analyzer development (SPAD) value, the bidirectional reflectance distribution function (BRDF) models of soybean and maize are calculated from the multi-angle hyperspectral images acquired by UAV, respectively. According to the reflectance extracted from the BRDF model, the dependences of 16 commonly-used VIs on observation angles are analyzed, and the SPAD values of maize and soybean canopy are predicted by using the 16 VI values at different observation angles and their combinations as input parameters. The results show that the 16 VIs have different sensitivity to angle in the principal plane: green ratio vegetation index (GRVI), ratio vegetation index (RVI), red edge chlorophyll index (CIRE), and modified chlorophyll absorption in reflectance index/optimized soil-adjusted vegetation index (MCARI/OSAVI) are very sensitive to angles, among which MCARI/OSAVI of maize fluctuated the most (138.83 %); in contrast, the green optimal soil adjusted vegetation index (GOSAVI), normalized difference vegetation index (NDVI), and green normalized difference vegetation index (GNDVI) hardly change with the observation angles. In terms of SPAD prediction, the accuracy of different VI is different, the mean absolute error (MAE) showed that MCARI1 provided the highest accuracy of retrieval for soybean (MAE=1.617), while for maize it was MCARI/OSAVI (MAE=2.422). However, when using the same VI, there was no significant difference in the accuracy of the predicted results, whether the VI from different angles was used or the combination of multi-angles was used. The present results provide guiding significance and practical value for the retrieval of SPAD value in vegetation canopies and in-depth applications of multi-angular remote sensing.

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