Measurement of Eastern Siberian larch forest LAI using the Normalized Difference Water Index

In this study, we describe a new remote sensing method to measure the canopy leaf area index (LAI) over the larch forests in Eastern Siberia, and we compare the measured LAI to ground observations and to other remote sensing products. The method was established using a set of radiative transfer simulations for several scenes representative of the larch forest structure, including the typical clumped shoot structure. The results indicate that the Normalized Difference Water Index (NDWI) is more sensitive than the Normalized Difference Vegetation Index (NDVI) for higher LAI, and that the dNDWI, which is the increase in NDWI from the leaf appearance date, is a good indicator for canopy LAI estimation. Based on these simulation results, we developed a semi-empirical method to measure the canopy LAI in larch forests during the growing season: we first estimate the date of canopy leaf appearance, then the forest floor conditions, and then the LAI seasonal variations. The algorithm was then applied to the reflectance measured by an airborne sensor in the Yakutsk region. The results were compared to the time series of LAI measured in situ at four sites, showing that the timing and magnitude are of the LAI increase are correct. Then, the algorithm was applied to the SPOT VEGETATION S10 reflectance, and the measured LAI were compared to the LAI from the MODIS MOD15 collection 5 dataset and to the CYCLOPE dataset. The LAI time series from our algorithm are very close to those from CYCLOPE in term of timing and magnitude. In contrary, the MOD15 LAI magnitude is larger than the other two datasets, and it starts increasing earlier than them and than the in situ time series, indicating the MOD15 collection 5 may be unreliable over larch forests in Eastern Siberia.