Desertification is one of the most serious eco-environmental and socio-economic problems in the world. Mongolia is a hot area of global desertification because of its fragile ecological environment and serious land degradation. In this study, based on Google Earth Engine platform, we selected Landsat7 remote sensing images, normalized vegetation index (NDVI), surface albedo (Albedo), improved soil adjusted vegetation index (MSAVI) and topsoil grain size index (TGSI) as desertification discrimination indexes, and combined the geographical division with desertification inversion characteristic space models to complete the fine inversion of Mongolian desertification information. In this way, we obtained a dataset of desertification distribution in Mongolia in 2015. The quality and accuracy of this dataset are verified by referring to field survey data and high-resolution Google Earth images. The overall evaluation accuracy is 87.00% and the Kappa coefficient is 83.19%. This dataset directly reflects the spatial distribution of different degrees of desertification in Mongolia, and can provide detailed and reliable data support for the delineation of key areas for desertification control and the formulation of restoration strategies in Mongolia. It is of great significance for the ecological environment and green and sustainable development of the China-Mongolia-Russia Economic Corridor.

The Mongolian Plateau is in the interior of Northeast Asia, and is extremely vulnerable to climate change and the deleterious effects of human activities. Mongolia is an important component unit of the Mongolian Plateau, and its resources, environment and ecological problems are closely related to the ecological barrier and resource security in northern China and the sustainable development of the China-Mongolia-Russia Corridor. However, there is still a lack of high-precision land cover data products suitable for the regional characteristics of Mongolia. In this study, according to the landscape pattern of Mongolia, we constructed a land cover classification system suitable for Mongolia; and based on the object-oriented remote sensing interpretation method, we adopted the split-scene interpretation to select a variety of indexes. According to certain rules and classification thresholds, we obtained a dataset of land cover classifications with a spatial resolution of 30m in Mongolia in 2005 and 2015. The land cover classifications of Mongolia includes 11 categories: forest, meadow steppe, real steppe, desert steppe, bare land, sand, desert, ice and snow, water, cropland and built areas. Based on multi-source validation point information and high-resolution Google Earth images, we completed an overall quality assessment and a single classification quality assessment of land cover classification results in Mongolia. In 2005, the overall classification accuracy is 78.85% and the Kappa coefficient is 0.77. In 2015, the overall classification accuracy is 80.49% and the Kappa coefficient is 0.78. The average annual classification accuracy is 79.67%, which meets the accuracy requirements. The dataset can directly reflect the changes of land cover pattern and trend in Mongolia and provide basic scientific data to support the sustainable development of Mongolia.