This data set includes 30 m cultivated land and construction land distribution products in Qilian Mountain Area in 2021. The product comes from the land cover classification product of 30 m in Qilian Mountain Area in 2021. The overall accuracy of the product is better than 85%.
YANG Aixia, ZHONG Bo
The evaluation of the potential of cropland development under the influence of future climate change changes was carried out for the sustainable development of agriculture in five Central Asian countries, with cropland as the target. The evaluation factors of cropland development potential include: topographic factors (elevation, slope, slope direction, distance to water resources), soil factors (salinity, soil texture, soil organic matter content, soil pH), climate factors (rainfall, temperature, solar radiation), and economic factors (road density, population density). Using 2020 as the base year, the future potential for cropland development in Central Asia under the SSP5-8.5 scenario was estimated using the average precipitation and temperature from the ESM1 climate model in CMIP6, with other indicators held constant. The data provide evaluation results of the cropland development potential of the five Central Asian countries for the time periods 2020s, 2030s (2021-2040) and 2050s (2041-2060) with a spatial resolution of 0.01° × 0.01°. The dataset can provide basic data support for future land resource development and utilization and agricultural development in the five Central Asian countries.
JIANG Xiaohui, ZHANG Junjun
Facing the sustainable development of agriculture in the Central Asia, the risk assessment of land resources exploitation under the influence of future climate change and land use change is carried out with the goal of cultivated land. The evaluation indices of land resources exploitation risk for farmland include topographic factors (such as elevation and slope), land use type, soil texture, precipitation, GDP per capita, grain production per capita, growth rate of agricultural economy, urbanization rate, natural growth rate of population, soil organic matter content, etc. Taking 2015 as the baseline and keeping other indicators remain unchanged, we use multi-model ensemble mean precipitation of climate models in CMIP6 (BBC-CSM2-MR, CanESM5, IPSL-CM6A-LR, MIROC6 and MRI-ESM2-0) and the land cover data under different emission scenarios in the future to estimate the risk of land resources exploitation in Central Asia under different scenarios in the future (SSP1-2.6, SSP2-4.5 and SSP5-8.5). The datasets include land resources exploitation in 2030s (2021-2040) and 2050s (2041-2060) under three future scenarios, with a spatial resolution of 0.5°×0.5°. It is expected to provide basic information for future agricultural production and land resources exploitation in five countries in Central Asia.
HUANG Farong, LI Lanhai
Facing the sustainable development of agriculture in the Central Asia, the risk assessment of the land resources exploitation is carried out with the aim of cultivated land. The evaluation indices of land resources exploitation risk for farmland include topographic factors (such as elevation and slope), precipitation, land use type, soil texture, GDP per capita, grain production per capita, growth rate of agricultural economy, urbanization rate, natural growth rate of population, soil organic matter content, etc. The above indices are normalized dimensionless, and the weight of each index to the risk of land resources exploitation is determined based on the multiple linear regression model between grain production and each index. The datasets include land resources exploitation risk in 1995, 2000, 2005, 2010 and 2015 with a spatial resolution of 0.5°×0.5°. It is expected to provide basic information for agricultural production and land resources exploitation in five countries in Central Asia.
LI Lanhai, HUANG Farong
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.
YANG Aixia, ZHONG Bo, JUE Kunsheng, WU Junjun
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
YANG Zhongkang
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.
LIU Junguo
The Huanghuang Valley was one of the most important agricultural development areas on the Qinghai-Tibet Plateau, especially by the Qing Dynasty, the land cover of the area underwent significant changes. By collating and correcting the 1726 cropland data recorded in the historical documents of the area, with a view to revealing the basic conditions of arable land changes and human activities in the typical river valley agricultural area of the Qinghai-Tibet Plateau, we provide a theoretical basis. This data contains raster data on the spatial distribution pattern of arable land in the Huanghuang Valley in 1726 with a spatial resolution of 1km*1km. The area of cropland is mainly obtained from the New Records of Xining Prefecture，Records of Xuanhua Hall，New Records of Gansu， which were recorded during the Qianlong period of 20 years. The determination of county administrative boundaries refers to Atlas of Chinese History edited by Tan Qixiang and Comprehensive Table of Administrative Region Evolution in Qing Dynasty edited by Niu Hanping. The original data on cropland collected from the historical literature was corrected and then the quantitative data was assigned to space using a grid drawing method.
LIU Fenggui, LUO Jing
Tibetan Plateau with high altitude,cold climate,poor natural conditions and fragile ecological environment become the sensitive and promoter region of global climate change.Studying for Land reclamation of historical period in Qinghai-Tibet Plateau is not only the specific way to participate in the global environmental change, but also can provide the comprehensive research of land use change with abundant regional information,there is important significance for studying history in our country even the whole world of land use/cover change research.The region of Brahmaputra River and its two tributaries in Tibetan Plateau pastoral transitional zone is one of the important typical agricultural area, and is the area with the most intense land reclamation activities and the fastest population growing.Proceeding deep historical data mining in the study area to reconstruct the cropland spatial patterns over the past 300 years has important significance to study the human land use activities under the background of global climate change. This data contains raster data on the spatial distribution pattern of arable land in Brahmaputra River and Its Two Tributaries in 1730 with a spatial resolution of 500m*500m.The data of cultivated land in 1730 comes from tiehu Inventory，the missing data of two counties were interpolated.The land area recorded in the data is converted into modern mu units, and the missing counties are calculated using the area's per capita cultivated land and population.
LIU Fenggui, GU Xijing
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.
LV Changhe, ZHANG Zemin
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.
YANG Yanzhao
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.
YOU Zhen
The data sources of this dataset mainly include domestic satellite images such as HJ-1A/B, GF-1/2, ZY-3, and Landsat TM/ETM+/OLI series satellite image data. Using the domestic satellite images supplemented by Google Earth images to generate the component training sample and validation sample data of different geographical divisions. Using Google Earth Engine (GEE) to test and correct the model algorithm parameters. The normalized settlement density index (NSDI) is obtained based on random forest algorithm, Landsat TM/ETM+/OLI series satellite images and auxiliary data. The vector boundary of urban built-up area is obtained by density segmentation method after manual interactive interpretation and correction. The NSDI, vegetation coverage index and vector boundary of the Tibetan Plateau are used to produce the original data of urban impervious surface and urban green space fractions in the Tibetan Plateau. After correction and accuracy evaluation, the datasets of urban impervious surface area and green space fractions in the Tibetan Plateau from 2000 to 2020 are generated. The resolution of the data product is 30 m, and the coordinate system and storage format of the data files are unified. The geographic coordinate system is WGS84, the projected coordinate system is Albers, and the data storage format is GeoTIFF, the data unit is percentage (the value range is 0~10000), and the scale factor is 0.01. In order to quantify the change of urban land cover more accurately, samples from several typical cities are selected to verify the dataset. The specific verification methods and accuracy are shown in the published results. The data can be used to analyze and reveal the impact of land cover change and future scenario simulation on the Tibetan Plateau, to provide a scientific basis for building environmentally livable cities and improving the quality of human settlements on the Tibetan Plateau.
KUANG Wenhui, GUO Changqing, DOU Yinyin
The data set records the statistical data of grassland construction in Qinghai Province in the main years, covering the period from 2011 to 2017. The data are divided by fenced grassland area, new enclosure area in the current year, reserved area of artificial grass planting, area of new species in the current year, rodent damage area in the year, rodent damage control area in the year, etc. The data set contains seven data tables, which are: Grassland Construction in major years (2011), grassland construction in major years (2012), grassland construction in major years (2013), grassland construction in major years (2014), grassland construction in major years (2015), grassland construction in major years (2016) and grassland construction in major years (2017). The data table structure is similar. For example, the data sheet of grassland construction in major years (2011) has 10 fields: Field 1: indicator Field 2: 1995 Field 3: year 2000 Field 4: year 2005 Field 5: year 2006 Field 6: year 2007 Field 7: year 2008 Field 8: year 2009 Field 9: year 2010 Field 10: year 2011
AGRICULTURAL AND RURAL Department of Qinghai Province
Sediment ancient DNA is biological ancient DNA scattered in Paleoenvironmental samples, which is different from ancient DNA directly extracted from ancient animal bones and plant remains. Paleoenvironmental DNA is mainly mixed with multi species ancient DNA extracted from environmental samples such as glaciers, frozen soil, lake sediments, peat sediments, site cultural layer, dental calculus and fecal fossils. These DNA enter the environment with biological residues (including remains, hair, feces and urine), degrade rapidly and denature slowly in the environment, and finally adsorb on minerals and other particles or integrate into their own genome by microorganisms for long-term preservation, thus forming paleoenvironmental DNA. Sediment DNA is a new ancient DNA analysis technology. The sediments of archaeological sites can track the DNA preservation status of relevant sites and possible humans, make up for the shortcomings that human fossils are generally available but not available, greatly expand the research object and open a new window to study the population evolution of Paleolithic archaeological sites. The ancient DNA of stratum sediments from baishiya karst cave site where Xiahe human mandible was found was systematically sampled and analyzed.
ZHANG Dongju , FU Qiaomei
The basic principle of ancient recipe analysis based on carbon and nitrogen stable isotope analysis method is you are what you eat, that is, the chemical composition of animal tissues and organs is closely related to their diet. Through the detection of isotope ratio of relevant elements, the food structure of ancient people and animals can be directly revealed Then it discusses the research means of people's livelihood and livestock domestication. The collagen of human and animal bones from shilinggang site in Nujiang, Yunnan Province in the southwest of Qinghai Tibet Plateau was analyzed by carbon and nitrogen stable isotopes.
DONG Guanghui , REN Lele
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.
YANG Xiaoyan, WANG Yanren
The data set of land desertification distribution in Sanjiangyuan area is derived from the desertification pattern and change data of Qinghai Tibet Plateau. This data is obtained based on the integration of remote sensing images, auxiliary data and other multi-source data. The main data used and referred to include: 1) remote sensing image data: Landsat was selected to extract the images from June to September as the main data source for land desertification monitoring on the Qinghai Tibet Plateau, and five images were selected to monitor land desertification in 1980, 1990, 2000, 2010 and 2015. 2) auxiliary data: terrain data, soil type data, vegetation type data Land use data, Google Earth image and other auxiliary data are important data in the interpretation of desertification land; 3) The indicators of desertification are wind erosion rate, percentage of quicksand area and vegetation coverage; 4) The area of the source area of the three rivers is 382312 km2. The data set is cut out from the land desertification distribution data of the Qinghai Tibet Plateau, so as to carry out the research and analysis of the source area of the three rivers separately; 5) This data format is ShapeFile format. It is recommended to use ArcMap to open data.
NAN Weige
Land cover data of typical mineral development project areas include land cover data set of Gannan Tibetan Autonomous Prefecture (2000), land cover data set of Gannan Tibetan Autonomous Prefecture (2010) and land cover data set of Gannan Tibetan Autonomous Prefecture (2020). The data format is shape file with a spatial resolution of 30m, including ten categories: cultivated land, forest land, grassland, shrub land, wetland, water body, tundra, artificial surface, bare land, glacier and permanent snow, and the time resolution is years. The data comes from globeland30 (global geographic information public product), http://www.globallandcover.com/ ）, obtained by mosaic and reorganization. The data accuracy evaluation of source data is led by Tongji University and Aerospace Information Innovation Research Institute of Chinese Academy of Sciences, and the overall accuracy of data exceeds 83.50%. The data set can provide high-precision basic geographic information for relevant research, and can be applied to the comprehensive effect assessment of land cover in typical mineral development areas of super large gold belt in Qilian Mountain metallogenic belt in the northeast of Qinghai Tibet Plateau. It has important applications in the environmental effect assessment of mineral development, natural disaster risk assessment and disaster prevention and reduction.
CHENG Hao
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.
LIU Shiliang, LIU Yixuan, SUN Yongxiu, LI Mingqi
