We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Estimating Leaf Area Index with Dynamic Leaf Optical Properties.
- Authors
Zhang, Hu; Li, Jing; Liu, Qinhuo; Dong, Yadong; Li, Songze; Zhang, Zhaoxing; Zhu, Xinran; Liu, Liangyun; Zhao, Jing
- Abstract
Leaf area index (LAI) plays an important role in models of climate, hydrology, and ecosystem productivity. The physical model-based inversion method is a practical approach for large-scale LAI inversion. However, the ill-posed inversion problem, due to the limited constraint of inaccurate input parameters, is the dominant source of inversion errors. For instance, variables related to leaf optical properties are always set as constants or have large ranges, instead of the actual leaf reflectance of pixel vegetation in the current model-based inversions. This paper proposes to estimate LAI with the actual leaf optical property of pixels, calculated from the leaf chlorophyll content (Chlleaf) product, using a three-dimensional stochastic radiative transfer model (3D-RTM)-based, look-up table method. The parameter characterizing leaf optical properties in the 3D-RTM-based LAI inversion algorithm, single scattering albedo (SSA), is calculated with the Chlleaf product, instead of setting fixed values across a growing season. An algorithm to invert LAI with the dynamic SSA of the red band (SSAred) is proposed. The retrieval index (RI) increases from less than 42% to 100%, and the RMSE decreases to less than 0.28 in the simulations. The validation results show that the RMSE of the dynamic SSA decreases from 1.338 to 0.511, compared with the existing 3D-RTM-based LUT algorithm. The overestimation problem under high LAI conditions is reduced.
- Subjects
LEAF area index; OPTICAL properties; RADIATIVE transfer; ALGORITHMS; GROWING season
- Publication
Remote Sensing, 2021, Vol 13, Issue 23, p4898
- ISSN
2072-4292
- Publication type
Article
- DOI
10.3390/rs13234898