A satellite-based method for monitoring seasonality in the overstory leaf area index of Siberian larch forest

Reliable monitoring of the leaf area index (LAI) is required to further understand the carbon, water, and energy cycles of forests. In this study, we proposed a new satellite‐based method to estimate the overstory LAI (LAIo) separately from the understory LAI (LAIu) for larch forests covering eastern Siberia. We modeled forest scenes representative of larch forest structure, with particular consideration of the typical clumped shoot structure of larch. Three‐dimensional radiative transfer simulations were then conducted under various forest conditions to establish the relationships between LAIo and seasonal increases in the normalized difference water index after leaf appearance. Model‐based sensitivity analyses indicated a maximum error of up to 26% under known noise levels. Averaged at the continental scale, total LAI from our estimates, the CYCLOPES version 3.1, and the Moderate Resolution Imaging Spectroradiometer MOD15 Collection 5 (main algorithm) showed similar ranges in summer. However, spatial pattern of LAI was slightly different, with smoother variability for CYCLOPES LAI. Our LAI and CYLOPES effective LAI reproduced a realistic seasonal variation with exact timing of spring increase in LAIo. The main drawbacks of MOD15 Collection 5 were unrealistically strong temporal variability, and the fact that LAI began to increase earlier than the overstory leaf appearance date. Overall, the results show that our new method is a good alternative to MOD15 Collection 5 and CYCLOPES, as it provides separate estimates of LAIo and LAIu and true LAI instead of effective LAI.