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Soil moisture plays an important role in crop yield estimation, irrigation management, etc. Remote sensing technology has potential for large-scale and high spatial soil moisture mapping. However, offline remote sensing data processing is time-consuming and resource-intensive, and significantly hampers the efficiency and timeliness of soil moisture mapping. Due to the high-speed computing capabilities of remote sensing cloud platforms, a High Spatial Resolution Soil Moisture Estimation Framework (HSRSMEF) based on the Google Earth Engine (GEE) platform was developed in this study. The functions of the HSRSMEF include research area and input datasets customization, radar speckle noise filtering, optical-radar image spatio-temporal matching, soil moisture retrieving, soil moisture visualization and exporting. This paper tested the performance of HSRSMEF by combining Sentinel-1, Sentinel-2 images and in-situ soil moisture data in the central farmland area of Jilin Province, China. Reconstructed Normalized Difference Vegetation Index (NDVI) based on the Savitzky-Golay algorithm conforms to the crop growth cycle, and its correlation with the original NDVI is about 0.99 (P < 0.001). The soil moisture accuracy of the random forest model (R2 = 0.942, RMSE = 0.013 m3/m3) is better than that of the water cloud model (R2 = 0.334, RMSE = 0.091 m3/m3). HSRSMEF transfers time -consuming offline operations to cloud computing platforms, achieving rapid and simplified high spatial resolution soil moisture mapping. [ABSTRACT FROM AUTHOR]

National nature reserves are an important part of classification management on ecological protection in China. Taking the national nature reserves of Jilin Province as examples, this paper introduced the stability index by referring to the intensity model of land-use and land-cover change (LUCC), and analyzed the overall stability of land-use and land-cover (LULC) in the study area from the time interval level and land category level. The stability of LULC in different types of nature reserves was tracked and identified by extracting land-use change trajectory, and the land-use change trajectory was divided into three types: stable type, sub-stable type and unstable type. The impact of LUCC on regional ecosystem services was studied by using hotspot analysis and gravity center analysis. The results showed that: 1) The LULC in the study area was stable on the whole, and the proportion of stable land area reached 86.08%. The intensity of LUCC showed an increasing trend in recent 20 years, and the conversion of cultivated land and construction land was active in continuous time interval. 2) The stability of LULC in forest ecological reserves and wildlife reserves in the eastern part of Jilin Province was the highest, while that in inland wetland reserves and geological relic reserves in the central and western part of Jilin Province was lower. 3) The LUCC in national nature reserves not only changed the value of its own ecosystem service function, but also affected the ecosystem service function of the whole region. The combination of intensity analysis and land-use change trajectory was used to identify the characteristics of stability of LULC in nature reserves, which was conducive to deeply understand the process of LUCC in national nature reserves and provided reasonable suggestions for regional ecological protection. [ABSTRACT FROM AUTHOR]