A New Self-Adaptive Approach for Producing Clear-Sky Viirs Composites at Continental Scale for the Studies of Belt and Road Initiative

Abstract

The implementation of the Belt and Road (B&R) initiative is of great significance to promoting economic development and regional cooperation in China and other countries along the corridors. Remote sensing technology can provide strong supports for ecological environment monitoring in the process of Belt and Road construction. However, due to frequent cloud contamination, the time series remote sensing images are not continuous in both spatial and temporal domain. This study proposed a new self-adaptive compositing approach (SACA) to produce the clear-sky VIIRS surface reflectance composites for the B&R regions. An evaluation was made for the SACA method by comparing it to the maximum NDVI (MaxNDVI), minimum Red (MinRed) and maximum ratio (MaxRatio) compositing schemes. Results showed that the SACA approach outperformed all other three methods. The results highlighted that the SACA method was feasible and effective at compositing continental VIIRS data, which has great potential for the B&R eco-environment studies.