Developing a Desertification Assessment System Using a Photosynthesis Model with Asimillated Multi Satellite Data

This paper aims to present an integrated approach for assessing the desertification processes on one hand and spot possible source locations of dust storm in Eurasian continent across the central Asia and northern China on the other hand. The authors have bu ilt Remote Sensing Environmental Monitor (RSEM) for Desertification Assessment System (DAS). Such an integrated sensing, monitoring and modeling system consists of three subsystems taking into account photosynthesis rate (PSN) based on vegetation types, water stress conditions based on the meteorological re-analysis data, and land-use/land-cover classification based on vegetation index. Eextracted normalized difference vegetation index (NDVI) anomaly helps identify the possible locations of severe dust storms linking daily photosynthesis rate with observed desertification trend in northern China with the aid of multi-sensor satellite data. To ensure the firm linkage, daily photosynthesis rate calculated were calibrated and validated by the observed tower data collected by FLUXNET at the global scale. The PSN model tends to overestimate the peak photosynthesis rate a little bit in our case study. Nevertheless, such a practice clearly confirms that land degradation in the areas from northwestern Mongolia to Mu Us desert in the Loess Plateau, and to eastern part of Inner Mongolia Autonomous Region remains the same in the past decade creating several hot spots of source locations of dust storms. * Corresponding author.