This data is the land cover data at 30m resolution of Southeast Asia in 2015. The data format of the data is NetCDF, and the variable name is "land cover type". The data was obtained by mosaicing and extracting the From-GLC data. Several land cover types, such as snow and ice that do not exist in Southeast Asia were eliminated.The legend were reintegrated to match the new data. The data provide information of 8 land cover types: cropland, forest, grassland, shrub, wetland, water, city and bare land. The overall accuracy of the data is 71% (Gong et al., 2019). The data can provide the land cover information of Southeast Asia for hydrological models and regional climate models.
According to the characteristics of the Qinghai Tibet Plateau and the principles of scientificity, systematization, integrity, operability, measurability, conciseness and independence, the human activity intensity evaluation index system suitable for the Qinghai Tibet Plateau has been constructed, which mainly includes the main human activities such as agricultural and animal husbandry activities, industrial and mining development, urbanization development, tourism activities, major ecological engineering construction, pollutant discharge, etc, On the basis of remote sensing data, ground observation data, meteorological data and social statistical yearbook data, the positive and negative effects of human activities are quantitatively evaluated by AHP, and the intensity and change characteristics of human activities are comprehensively evaluated. The data can not only help to enhance the understanding of the role of human activities in the vegetation change in the sensitive areas of global change, but also provide theoretical basis for the sustainable development of social economy in the Qinghai Tibet Plateau, and provide scientific basis for protecting the ecological environment of the plateau and building a national ecological security barrier.
Ecosystem services are many benefits provided by ecosystem for human beings. Soil conservation, as one of the main regulating services provided by terrestrial ecosystem, is an important guarantee to prevent regional land degradation and reduce the frequency of flood disasters. Soil conservation (SC) is often used to evaluate. As an important part of the national ecological security strategy, it is of far-reaching significance to explore the spatial and temporal distribution of soil conservation in the Qinghai Tibet plateau for the construction of ecological civilization and sustainable development in China. Based on the modified universal soil loss equation (RUSLE), the 8 km resolution soil conservation data set (1990-2015) of the Qinghai Tibet Plateau was generated using GIMMS NDVI 3gv1.0 data, aster GDEM, meteorological stations and Chinese soil data set.
"Coupling and Evolution of Hydrologic -Ecologic-Economic Processes of the Heihe River Basin Under the Framework of Water Rights" (91125018) Project data collection 1 - SWater Resources Improvement Plan of Shiyang River Basin 1. Data Overview:The improvement plan of Shiyang River Basin was implemented in 2007 for river basin comparison. 2. Data Content: The released plan.
The data include the datasets of temporal changes in water level, water storage and area of the Aral sea (1911−2017), the inter-decadal change of ecosystem structure (NDVI—Normalized Difference Vegetation Index) of the Aral sea (1977−2017), and dust intensity (EDI—Enhanced Dust Index) in the Aral sea (2000−2018). Using data fusion technology in the construction of a lake basin terrain, terrain based on remote sensing monitoring and field investigation, on the basis of the analysis of the Aral sea terrain data, generalized analyses the water - area - the changes of water content, the formation of water - water - area of temporal variation data set, can clearly reflect the Aral sea water change process and the present situation, provide basic data for the Aral sea environmental change research. The NDVI was used to reflect the vegetation ecology in the receding area. Landsat satellite data, with a spatial resolution of 30 m, was used for NDVI analysis in 1977, 1987, 1997, 2007, and 2017. Based on ENVI and GIS software, remote sensing image fusion, index calculation, and water extraction were used to determine the lake surface and lakeshore line of the Aral sea. The lakeside line in the south of the Aral sea is taken as the starting point, and it extends for 3 km to the receding area. The variation characteristics of vegetation NDVI in the lakeside zone within 0-3 km are obtained to reflect the structural changes of the lakeside ecosystem. EDI was extracted from MODIS image data. This index is introduced into the dust optical density to enhance the dust information to form the enhanced dust index. Based on remote sensing monitoring, the use of EDI, established the Aral sea area-EDI index curve, the curve as the construction of the Aral sea dry lake bed dust release and meteorological factors, quantitative relationship laid the foundation of soil physical and chemical properties, in order to determine the control of sand/salt dust in the reasonable area of the lake.
This data is the spatial distribution map of ecological shelters in Nursultan, the capital of Kazakhstan in 2018. The types of features in the map mainly include shelter forests, roads, buildings, lakes and rivers. The data source is four sentinel images in August 2018, with a resolution of 10 meters. At the same time, overlay the vector map of OSM global features. The data set is more accurate after correction. Through visual interpretation and field investigation, the extraction of shelter forest spot has high precision. The data reflects the spatial distribution of urban ecological shelters in Nursultan, the capital of Kazakhstan. At the same time, it has an important reference value for the long-term monitoring of the spatial and temporal pattern of shelter forests.
The data set records the urbanization rate data of each state of kazakhstan from 2000 to 2018.The data is from kazakhstan's national statistics bureau. Urbanization is a concept with broad implications.In a narrow sense, it generally refers to the urbanization of population, which refers to the increase of the number of cities and the expansion of the urban scale, and the process of population aggregation to cities in a certain period.Urbanization rate refers to the proportion of permanent urban residents in a region in the total permanent resident population.The name of the original index is Russian, which has been translated and edited.The accuracy of the official data can provide basic data basis for the study of the socio-economic development of central Asian countries.