In a study published in Remote Sensing of Environment, Dr. WEI Shanshan and Prof. FANG Hongliang from Institute of Geographic Sciences and Natural Resources Research of the Chinese Academy of Sciences and other international scholars proposed a new look-up table (LUT) method based on an improved Normalized Difference between Hotspot and Darkspot (NDHD) method to estimate the daily CI from the MODIS V006 MCD43 BRDF (bidirectional reflectance distribution function) product.
Global validation studies showed that the new CI product has a higher accuracy than those in existing studies. The deciduous broadleaf forest and mixed forests showed strong seasonal CI variation, and this character could to be used to detect the vegetation phenology change.
The scientists found that CI showed a negative correlation to the leaf area index (LAI) for all vegetation types, especially forests, the global CI demonstrated an inter-annual variation that correlates with the global precipitation change, and from 2001 to 2017, the global CI showed a decreasing trend, consistent with the increasing LAI.
These findings showed that with the increasing amount of global leaves, their spatial distribution has become more aggregated. This study revealed for the first time the unique seasonal and long term variation patterns for the leaf spatial distribution. It provides a new prospective to examine the global vegetation change.
52 Sanlihe Rd., Xicheng District,
Beijing, China (100864)