The spatial distribution of vegetation foliage greatly affects the estimation of gross primary productivity (GPP) and evapotranspiration (ET) from various ecosystem and land surface models. Canopy clumping index (CI), a proxy of foliage spatial distribution, is a critical variable in many terrestrial models. Multi-angle remote sensing data provide an effective way to generate long-term global CI data.
Global CI data products have been derived based on the relationship with the normalized difference between hotspot and darkspot (NDHD). Nevertheless, current global CI data products failed to account for the impact of solar zenith angle (SZA) and the surface reflectance model, which greatly hamper product accuracy. Moreover, current products are limited to describe the seasonal and inter-annual CI variation that is needed by many land surface models.
A new global CI product (LIS-CI-A1) was generated by the research team of Prof. FANG Hongliang, Institute of Geographic Sciences and Natural Resources Research (IGSNRR), Chinese Academy of Sciences. After comparing various surface reflectance models and SZA effects, the optimal BRDF model and SZA were used to derive the new CI. Preliminary validation studies have shown that the new CI is superior to other existing products, especially over sparsely vegetation areas.
The product is available at a 500 m spatial resolution every 8 days from 2001 to 2016. The research is supported by National Natural Science Foundation of China and the National Key Research and Development Program of China.