Separating of Overstory and Understory Leaf Area Indices for Global Needleleaf and Deciduous Broadleaf Forests by Fusion of MODIS and MISR Data

Forest overstory and understory layers differ in carbon and water cycle regimes, phenology, as well as ecosystem functions. Separate retrievals of Leaf Area Index (LAI) for these two layers would help to improve modeling forest biogeochemical cycles and evaluating forest ecosystem functions. In this paper, overstory and understory LAI values were estimated separately for global needleleaf and deciduous broadleaf forests by fusing MISR and MODIS observations. Monthly forest understory LAI was retrieved from the forest understory reflectivity estimated using MISR data. After correcting for the background contribution using monthly mean forest understory reflectivities, the forest overstory LAI was estimated from MODIS observations. The results demonstrate that forest understory vegetation is mainly distributed in the boreal forest zones at northern latitudes. Significant seasonal variations are presented for understory vegetation in these zones with LAI values up to 2–3 from June to August. Higher understory LAI values are found in needleleaf forests (with mean value of 1.06 for evergreen needleleaf forests and 1.04 for deciduous needleleaf forests) than in deciduous broadleaf forests (0.96) due to the more clumped foliage and easier penetration of light to the forest floor in needleleaf forests. The magnitude of seasonal variations of overstory LAI is larger for deciduous needleleaf forests than those of evergreen and deciduous needleleaf forests. In contrast, for forest understory, needleleaf forests show larger seasonal variations than broadleaf forests. Spatially and seasonally variable forest understory reflectivity helps to account for the effects of the forest background on LAI retrieval while compared with constant forest background. The retrieved forest overstory and understory LAI values were compared with an existing dataset for larch forests in Northern Eurasia. The retrieved overstory and understory LAI is close to that of the existing dataset, with an absolute error of 0.34 (0.06), relative error of 21.1 % (14.3 %) and RMSE of 0.93 (0.29) for overstory (understory). The comparisons between our results and field measurements in eight forest sites show that the R2 are 0.62 and 0.52, and the RMSE are 0.62 and 1.36 for understory and overstory LAI, respectively.