This data set is a 30m land cover classification product in the Qilian Mountains in 2021. This product is based on the land cover classification product in 2021, based on the Landsat series data and strong geodetic data processing capability of Google Earth engine platform, and is produced by using the ideas and methods of change detection. The overall accuracy is better than 85%. This product is the continuation of land cover classification products from 1985 to 2020. Land cover classification products from 1985 to 2020 can also be downloaded from this website. Among them, the land use products from 1985 to 2015 are five years and one period, and the land use products from 2015 to 2021 are one year and one period.
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.
1) In mountainous areas, due to the complex topographic and geological background conditions, landslides are very easy to occur triggered by external factors such as rainfall, snow melting, earthquake and human engineering activities, resulting in the loss of life and property and the destruction of the natural environment. In order to meet the safety of project site construction, the rationality of land use planning and the urgent needs of disaster mitigation, it is necessary to carry out regional landslide sensitivity evaluation. When many different evaluation results are obtained by using a variety of different methods, how to effectively combine these results to obtain the optimal prediction is a technical problem that is still not difficult to solve at present. It is still very lack in determining the optimal strategy and operation execution of the optimal method for landslide sensitivity evaluation in a certain area. 2) Using the traditional classical multivariate classification technology, through the evaluation of model results and error quantification, the optimal evaluation model is combined to quickly realize the high-quality evaluation of regional landslide sensitivity. The source code is written based on the R language software platform. The user needs to prepare a local folder separately to read and store the software operation results. The user needs to remember the folder storage path and make corresponding settings in the software source code. 3) The source code designs two different modes to display the operation results of the model. The analysis results are output in the standard format of text and graphic format and the geospatial mode that needs spatial data and is displayed in the standard geographic format. 4) it is suitable for all people interested in landslide risk assessment. The software can be used efficiently by experienced researchers in Colleges and universities, and can also be used by government personnel and public welfare organizations in the field of land and environmental planning and management to obtain landslide sensitivity classification results conveniently, quickly, correctly and reliably. It can serve regional land use planning, disaster risk assessment and management, disaster emergency response under extreme induced events (earthquake or rainfall, etc.), and has great practical guiding significance for the selection of landslide monitoring equipment and the reasonable and effective layout and operation of early warning network. It can be popularized and applied in areas with serious landslide development
The data were passed through the data center of institute of Tibetan Plateau research, Chinese Academy of Sciences（ http://www.data.tpdc.ac.cn/ ）China's land use status remote sensing monitoring database products are obtained. The Irtysh River and Tarim River Basin are all seven periods of data in 1980, 1990, 1995, 2000, 2005, 2010 and 2015. The data production is based on the Landsat of each period TM / ETM Remote sensing image is the main data source, which is generated by manual visual interpretation. The spatial resolution is 1km, and the projection parameter is Albers_ Conic_ Equal_ Area central meridian 105, standard weft 1:25, standard weft 2:47. The land use types include six first-class types of cultivated land, woodland, grassland, water area, residential land and unused land, and 25 second-class types.
This dataset was captured during the field investigation of the Qinghai-Tibet Plateau in June 2021 using uav aerial photography. The data volume is 3.4 GB and includes more than 330 aerial photographs. The shooting locations mainly include roads, residential areas and their surrounding areas in Lhasa Nyingchi of Tibet, Dali and Nujiang of Yunnan province, Ganzi, Aba and Liangshan of Sichuan Province. These aerial photographs mainly reflect local land use/cover type, the distribution of facility agriculture land, vegetation coverage. Aerial photographs have spatial location information such as longitude, latitude and altitude, which can not only provide basic verification information for land use classification, but also provide reference for remote sensing image inversion of large-scale regional vegetation coverage by calculating vegetation coverage.
Quantitative evaluation and comprehensive measurement of resource and environment carrying capacity is the key technical link of resource and environment carrying capacity research from classification to synthesis. Based on the evaluation of the suitability of human settlements, the limitation of resource carrying capacity and socio-economic adaptability, and according to the research idea and technical route of "suitability zoning restrictive classification adaptability classification warning classification", a three-dimensional tetrahedral model for the comprehensive evaluation of resource and environmental carrying capacity with balanced significance is constructed. Based on the 10km grid, a comprehensive study on the resource and environment carrying capacity was carried out, and the resource and environment carrying capacity index of the areas along the silk road was quantitatively simulated. Taking 1 as the equilibrium significance, it provided support for the comprehensive evaluation of the resource and environment carrying capacity of the areas along the silk road.
The supply capacity of land resources is an important index to determine the carrying capacity of land resources. The data set includes: (1) the supply capacity of cultivated land resources in the Qinghai Tibet Plateau; (2) Data on grassland resource supply capacity of Qinghai Tibet Plateau. The supply capacity of cultivated land resources is based on the output of main agricultural products of Tibet Bureau of statistics, and summarizes the output of grain, meat, eggs and dairy livestock products at key nodes; The grassland resource supply capacity is based on the grassland area and livestock quantity data of Tibet Bureau of statistics, combined with field sampling data and climate data, and based on the aboveground biomass model to calculate the average biomass and total biomass of grassland in typical counties at key nodes. The data can be used to analyze the spatial difference of land supply capacity of the Qinghai Tibet Plateau, which is of great significance to the study of land carrying capacity of the Qinghai Tibet Plateau.
The alpine and anoxic environment of the Qinghai Tibet Plateau is a major challenge for human survival and life. When human beings boarded the Qinghai Tibet Plateau and adapted to the extreme environment of the plateau has always been a hot issue in the academic circles. At present, in the study of prehistoric culture of the Qinghai Tibet Plateau, except the northeast, most areas of the Qinghai Tibet Plateau have not established archaeological cultural sequences. Yajiang river basin is one of the areas with dense distribution of human activity relics, but there are few archaeological excavations and studies, and the activity history of the ancients in this area is not clear. Based on the systematic dating of cultural archaeological sites in Linzhi Area, Southeast Tibet, 33 carbon fourteenth age data were obtained.
The data set records the basic information of cultivated land in the Tibet Autonomous Region and contains two data tables. Among them, the data table 1 has 7 fields, and the data table has 5 fields, respectively recording the cultivated land area, dry land area, paddy field area, effective irrigation area, and national infrastructure area of Tibet Autonomous Region and each district and county from 1959 to 2016. , The units are all hectares. The data comes from: "Tibet Statistical Yearbook" and "Tibetan Social and Economic Statistical Yearbook", with the same accuracy as the statistical yearbook extracted from the data. This data set has important value for understanding the situation of cultivated land in the Tibet Autonomous Region, evaluating the level of cultivated land utilization, and researching agricultural production and food security.
As the roof of the world, the water tower of Asia and the third pole of the world, the Qinghai Tibet Plateau is an important ecological security barrier for China and even Asia. With the rapid development of social economy, human activities have increased significantly, and the impact on the ecological environment is growing. In this paper, eight factors including cultivated land, construction land, National Road, provincial road, railway, expressway, GDP and population density were selected as the threat factors, and the attributes of the threat factors were determined based on the expert scoring method to evaluate the habitat quality of the Qinghai Tibet Plateau, so as to obtain six data sets of the habitat quality of the agricultural and pastoral areas of the Qinghai Tibet Plateau in 1990, 1995, 2000, 2005, 2010 and 2015. The production of habitat quality data sets will help to explore the habitat quality of the Qinghai Tibet Plateau and provide effective support for the government to formulate sustainable development policies of the Qinghai Tibet Plateau.