基于机载MASTER数据的果园叶面积指数遥感反演

Leaf area index retrieval of orchards based on airborne MASTER data

叶面积指数(leaf area index,LAI)是描述植被冠层结构的重要参数,准确获取果树的LAI对果树长势监测和果树估产均有重要作用。以美国加州中部的果园为研究区,基于沿太阳主平面飞行成像的机载MODIS/ASTER模拟传感器(MODIS/ASTER airborne simulator,MASTER)数据,利用实测LAI数据与归一化差值植被指数(normalized difference vegetation index,NDVI)、归一化差值红外指数(normalized difference infrared index,NDII)和归一化差值水体指数(normalized difference water index,NDWI)分别建立回归模型,并选取NDWI进行研究区LAI的反演。结果表明:由于地物的二向性反射,垂直太阳主平面飞行获取的遥感数据具有明显的亮度梯度现象,而沿太阳主平面飞行获取的遥感数据几乎不受亮度梯度的影响;NDVI在高植被覆盖区容易达到饱和,而NDWI比NDVI和NDII具有更高的拟合度和更小的均方根误差,更加适合研究区LAI的遥感反演;该研究结果可以丰富LAI反演理论,也可以为研究LAI尺度问题提供理论和数据支持。

Leaf area index （ LAI ） is an important parameter for decrypting canopy structure, and the accurate acquisition of orchards LAI plays an important role in monitoring the growing condition and estimating the yield of orchards. In this paper, the orchard blocks in the middle of California in USA were chosen as the study area, and LAI was retrieved using normalized difference water index （ NDWI ） through comparing regression models with surveyed leaf area indices and three vegetation indices composed of normalized difference vegetation index （ NDVI） , normalized difference infrared index （ NDII） and NDWI based on the MODIS/ASTER airborne simulator （ MASTER） image, which acquired flying along the solar plane. The results show that the image acquired by flying perpendicular to the solar plane has the phenomenon of maximum brightness gradients because of the bidirectional reflectance of surface object, whereas the image acquired by flying along the solar plane fails to show such a phenomenon. The comparison between three vegetation index models also shows that NDVI is easy to reach saturation in higher coverage area, and NDWI is more suitable for LAI retrieval in the study area because NDWI model has higher R2 and smaller RMSE. The results of this study can enrich the LAI retrieval theory and provide theoretical and data support for LAI scale problem.