The Agricultural Remote Sensing Innovation Team at the Institute of Agricultural Resources and Regional Planning of the Chinese Academy of Agricultural Sciences has achieved groundbreaking advancements in global soil and vegetation temperature retrieval. Their pioneering research, "Retrieval of global surface soil and vegetation temperatures based on multisource data fusion," have been published in the top-tier journal in the field of remote sensing, "Remote Sensing of Environment" (IF=11.1).

Soil and vegetation temperatures are key parameters in agricultural production, providing vital metrics for soil quality assessment and crop growth monitoring. Conventional methods rely on model simulations or data assimilation techniques, while remote sensing technology can directly acquire the actual distribution at the regional scale. Despite its benefits, it faces shortcomings such as limited temporal sampling frequency and data gaps due to cloud cover. In response to these challenges, the Agricultural Remote Sensing Team has proposed a multisource data Fusion-based global surface Soil and Vegetation Temperature retrieval method (FuSVeT).

Compared to previous retrieval method that relies solely on satellite-based temporal and spatial information, FuSVeT presents enhanced accuracy, more complete spatial coverage, and improved computational efficiency. This novel approach not only fills the gap in vegetation temperature data but also outperforms existing soil temperature products, by capturing significant spatial heterogeneities within biomes. Therefore, FuSVeT is expected to provide more precise and comprehensive data support for areas such as agricultural monitoring, ecological assessment, and climate change analysis.

Figure 1: Distribution of soil-vegetation temperature differences across various levels of FVC at different latitudes. 

Liu Xiangyang, Associate Researcher from the Institute of Agricultural Resources and Regional Planning of the Chinese Academy of Agricultural Sciences, is the first author of the paper. The research was supported by the State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China, the National Natural Science Foundation of China Innovative Research Group Project "Agricultural Remote Sensing Mechanisms and Methods", and the Youth Innovation Program of the Chinese Academy of Agricultural Sciences " Biophysical Responses of Component Temperatures to Land Cover Changes". 

Original Article Link:

 https://www.sciencedirect.com/science/article/abs/pii/S003442572400590X