## 1 Introduction
The reward and subsidy standard should be adjusted each round by central government, and the specific regions and local accordance subsidy need to be adjusted every year by local government according to the changing condition of grassland. Continuous observation and real-time monitoring of grassland change and pixel-specific analysis are important for an optimal implementation of policy and to balance the interests of relevant stakeholders. To identify the spatio-temporal grassland cover change, the traditional and effective method is based on in situ surveys, which can provide creditable and precise results but, considering the wide expanses of grassland, this also goes along with costly and time-consuming intensive fieldwork, limited sites and lagging data processing [13]. With the improvement of spatio-temporal resolution of remote sensing (RS) and data processing technologies, mapping and monitoring of grassland cover change becomes more efficient and is often combined with in situ data for validation [14]. Many researches implement vegetation indexes (VIs) extracted from spectral sensors for grassland monitoring, including normalized difference vegetation index (NDVI) [15], enhanced vegetation index (EVI) [16], net primary productivity (NPP) and surface vegetation coverage [17], etc. There are also synthetic researches based on the analysis of multiple VIs addressing the importance of multiple perspectives [18] through analysis of variations in species composition, grassland desertification and above ground biomass of grassland degradation in semiarid grasslands. Although the VIs are abundant and flexible, and the information on grassland degradation and condition classification show large differences [19], grassland monitoring activities on a regional and global level are gradually providing more specific information to support sustainable grassland management. In recent decades, many studies have concentrated on the monitoring of vegetation dynamics in IMAR. Some results indicate that vegetation growth has been poor since the beginning of the 21 st century and that vegetation cover is lower in comparison to the 1980s or 1990s [20]. Other contradictory results have shown an increase of vegetation cover or productivity since the year 2000, possibly due to governmental decisions in the field of grassland management and conservation [21; 22]. Historic change is always under debate. Considering that SISGC is an annual-based adjustment project, the grassland development analysis during the implementation period seems more practical for local stakeholders. In this research, we attempt to use open access RS data to monitor changes in grassland coverage at pixel level, combining Fractional Vegetation Cover (FVC) and NPP to qualitatively and quantitatively explore the annual grassland change in IMAR. The main objectives of this research are to understand grassland development and its trend since SISGC implementation in 2011. The results can help to support sustainable grassland management strategies for local governments when adjusting to SISGC on an annual basis and provide management references for other global grassland areas.