Assessing the effects of understory to forest canopy leaf area index by combining moderate resolution data and geometric optical (GO) model in temperate forest

Abstract

The forest canopy vertical structure, understory spatial distribution as well as bare soil ground under a forest canopy strongly affect the accuracy of retrieving leaf area index (LAI) using optical remotely sensed data. Combining the reflectance from two different view directions and geometric optical (GO) radiative model, we investigated the effects of background information on retrieving forest canopy LAI using moderate resolution data for temperate forest in Northeastern China. Firstly, the forest background reflectance (BR) was computed using the bidirectional reflectance distribution function (BRDF) product from MODIS data. Then the forest canopy effective leaf area index (LAIe) was retrieved using the four scale geometric optical radiative model after removing the effects of forest background. It was found that the LAIe estimates without considering and with considering forest background contribution can explain 46 % and 36 % variations of field measurement-based LAIe (p< 0.01, N=28), respectively. The forest canopy LAIe estimation without removing background influence can result in the LAIe overestimation ranging from 20 % to 46 %, thus it is necessary to separate the contribution of forest background to total forest canopy reflectance.