The lower reaches of the Tarim River Basin serve as a crucial ecological barrier in China's extreme arid region,with its plant diversity playing a key role in maintaining regional ecological balance and addressing global climate change.This study combines field survey data with literature data to systematically construct a plant species inventory dataset for the lower reaches of the Tarim River.The field survey was conducted from July 30 to August 19,2024,utilizing remote sensing and GIS technologies.A 10 m x 10 m plot was established in the lower reaches of the Tarim River Basin(39°25′12″N-40°40′12″N,87°35′24″E-88°30′0″E).To ensure data quality and accuracy,the research team invited plant experts to identify plant information during the collection process.The authors meticulously documented information on 24 families,65 genera,and 81 species of plants,compiling them into the Dataset of plant species of the lower reaches of the Tarim River(2024).The dataset includes:(1)geo-locations of the sample sites;(2)plant list and statistics of families and life forms.The plan list is composed of family,genus,species,classification,life form,national protection status,common names,and collection locations;(3)plants' photos.The dataset is archived in.shp,.xlsx,and.jpg formats,and consists of 87 data files with data size of 1.63 GB(compressed into 4 files with 1.62 GB).
As a crucial ecological barrier and a major hydropower energy base in China,hydropower development on the Qinghai-Xizang Plateau exerts a profound influence on the regional ecological environment.To support the evaluation of ecological effects of major construction projects under the Second Comprehensive Scientific Expedition to the Qinghai-Xizang Plateau,this study systematically collected and organized data on large and medium-sized hydropower stations that have been built or are currently under construction across the plateau.The dataset encompasses 61 hydropower stations distributed across 6 major river basins-the Yarlung Zangbo River,Yellow River,Jinsha River,Lancang River,Yalong River,and Min River-and includes key attributes such as station name,geographical location,total reservoir capacity,installed capacity,annual power generation,regulation performance,development mode,and construction period.The data sources consist of field surveys and literature review.There was a"dense in the east and sparse in the west"spatial pattern of the large and medium-sized hydropower stations on the Qinghai-Xizang Plateau.Significant inter-basin differences were observed in both installed capacity and reservoir scale.Although the pace of hydropower construction has slowed,the scale of individual projects has increased,and dam-type development remains predominant.This dataset provides a solid scientific foundation for assessing ecological impacts of hydropower projects,managing regional water resources,and planning energy systems under the goal of carbon neutrality.
Total soil nitrogen(TN)content is a key indicator reflecting soil nutrient status and ecological functions.Based on the Google Earth Engine(GEE)cloud computing platform,we integrated multi-source remote sensing data and selected key environmental variables-including MODIS-derived NDVI,Sentinel-2 near-infrared reflectance(Band 8),surface soil moisture,precipitation,land surface temperature,and digital elevation model(DEM)—as input features.3 machine learning algorithms were employed for TN content prediction:Random Forest(RF),Classification and Regression Tree(CART),and Gradient Boosting Regression Tree(GBRT).Using these models,we generated a 2020 soil total nitrogen dataset for Taiyuan City,China.The SoilGrids global soil nitrogen dataset,provided by the International Soil Reference and Information Centre(ISRIC),was used as the reference data.Model performance was evaluated using root mean square error(RMSE)and coefficient of determination(R2)through cross-validation.The average RMSE values for RF,CART,and GBRT across different soil depths were 0.16 g/kg,0.21 g/kg,and 0.33 g/kg,respectively,with corresponding average R2 values of 0.62,0.64,and 0.85.The validation results indicate that the dataset exhibits high accuracy and reliability,providing robust scientific support for regional soil nutrient assessment,agricultural decision-making,and ecological-environmental management.The dataset includes soil total nitrogen content at 6 soil depths(0-5 cm,5-15 cm,15-30 cm,30-60 cm,60-100 cm,and 100-200 cm)for Taiyuan City in 2020,with a spatial resolution of 30 m.The dataset is archived in.tif format,and consists of 18 data files with data size of 1.52 GB(compressed to 1 file with 219 MB).
Qinghai-Xizang Plateau plays a crucial role in regional water cycles and ecosystem functioning through its surface soil moisture dynamics.This study developed a surface soil moisture dataset for the Qinghai-Xizang Plateau covering the period from 2015 to 2100 with a spatial resolution of 0.1°×0.1°.First,in situ measurements from the MAQU,NAQU,and NGARI networks were used to evaluate the accuracy of 21 CMIP6 soil moisture datasets,along with SMAP and ERA5-Land products,using bias,correlation coefficient(R),root mean square error(RMSE),and unbiased RMSE(ubRMSE).Meanwhile,the Enhanced Triple Collocation(ETC)method was employed to obtain random error standard deviation(RESD)and correlation coefficient(CC),based on which 4 Earth system models were selected for data fusion.Second,SMAP and ERA5-Land datasets were fused using differential weighting guided by the ETC evaluation results,and the optimal fusion result was identified.Finally,a Random Forest algorithm was used to integrate multiple sources of explanatory variables for monthly model training,and the model's prediction accuracy was validated against in situ observations.The resulting dataset includes:(1)monthly soil moisture data under 4 Shared Socioeconomic Pathways(SSP1-2.6,SSP2-4.5,SSP3-7.0,and SSP5-8.5)from 2015 to 2100 at 0.1° spatial resolution;(2)monthly in situ measurements(0-0.1 m depth)from the MAQU,NAQU,and NGARI networks.The dataset is archived in.mdd,.tif,.shp,and.csv formats,consisting of 4,838 data files with data size of 0.99 GB(compressed into 1 file with data size of 315 MB).Results indicate that compared to the original CMIP6 model outputs,the fused product exhibits significantly higher accuracy and lower error,enhancing the characterization of soil moisture dynamics over the Qinghai-Xizang Plateau.
The Qinghai-Xizang Plateau is characterized by ecological fragility and high sensitivity to climate change,with soil erosion posing a major threat to the ecological security of the Pan-Third Pole region.To reduce discrepancies in current assessments of soil erosion on the Qinghai-Xizang Plateau and to provide a more reliable representation of the spatial distribution and temporal dynamics in soil erosion,the authors applied an ensemble RUSLE model.This model integrates multiple datasets,including the China Meteorological Forcing Dataset(CMFD),Climate Hazards group Infrared Precipitation with Stations(CHIRPS)and ERA-Interim,SoilGrids soil data,and a 90-m DEM,combined with diverse erosion factor schemes(9 R factors × 3 K factors × 3 LS factorsx3 C factors).The model was used to evaluate soil erosion on the Qinghai-Xizang Plateau from 1981 to 2018.The"RUSLE-IC-SDR"method was compared with measured sediment yield data to develop a soil erosion dataset for the Qinghai-Xizang Plateau.The dataset includes:(1)multi-year average water erosion data for the periods 1981-2018,1981-1998,and 1999-2018,corresponding to the median values from the ensemble model;and(2)rates of change in water erosion for 1981-2018,1981-1998,and 1999-2018.The spatial resolution of the data is 100 m.The dataset is archived in.tif format and consists of 26 data files,with a total size of 12.3 GB(compressed into 6 files,5.38 GB).
As the backbone of modern transportation infrastructure,railways not only embody the level of transport development in different countries,but also capture the profound transformations in economic,social,and geopolitical structures.To address the gaps in historical data on the global length of railways in operation,this study integrates data from Brian Mitchell's International historical statistics,the World Bank,the International Union of Railways,and national statistical offices to construct a dataset of the global length of railways in operation for the period from 1825 to 2021.The missing data were systematically categorized into 3 types:mid-series gaps,end-period gaps,and gaps caused by national boundary adjustments.To complete the dataset,we apply linear interpolation,regression-based forecasting,and static/dynamic weighting methods tailored to each type.Building on the reconstructed dataset,we conduct a spatiotemporal analysis of global railway development at regional as well as national scales.The findings reveal that:(1)global railway development can be divided into 5 distinct stages with clear phases and fluctuations;(2)significant regional disparities exist,with Europe and North America leading in the early stages,and Asian countries emerging as key growth engines in the 21st century;and(3)railway development has been shaped significantly by geopolitical and geo-economic dynamics,with shifting patterns of interaction across historical periods that determine the trajectory of global railway evolution.This study provides systematic data support for understanding the historical evolution of global infrastructure,establishing a solid foundation for exploring the interplay between transportation and socioeconomic changes.
Oases are non-zonal geographical units formed on a desert matrix in arid regions driven by stable water sources.They serve as crucial habitats for biodiversity,bases for human livelihoods,and important pillars of human civilization.Oases play a pivotal role in maintaining the stability of terrestrial ecosystems in arid zones,preventing land degradation,regulating local climates,and enhancing ecological well-being.However,fundamental research on the global distribution digital data of oases is still lacking,and systematic global oasis cataloging has not yet been established.This has caused significant discrepancies and gaps in the available data,resulting in inconsistencies and inaccuracies in numerous related studies,thereby hindering the progress in oasis science.To fill this gap,this data product,based on high-resolution remote sensing imagery provided by the Google Earth Pro platform,manually delineated global oasis boundaries through visual interpretation.A global oasis dataset was created using 2020 as the baseline year,and the first comprehensive global oasis catalog was systematically completed.The dataset,comprising a total of 54 files,has been published in the Global Change Research Data Publishing & Repository the regular member of World Data System of the International Science Council and is freely available for download globally.The research results show that oases are distributed across 5 continents and 54 countries,covering a total area of 2,482,193.27 km2 and encompassing 4,850 oases.Among them,China has the largest area(275,535.39 km2)of oases,containing 1,398 oases.Based on this high-precision dataset,we selected the most relevant four attributes(continent,country,river,and oasis area)—to code the global oases.Each oasis larger than 1 km2 was assigned a unique ID,thereby establishing a clear'identity'for each oasis and addressing the long-standing absence of a global cataloging system.Moreover,regular future updates related to the catalog information will enable the precise tracking of dynamic processes such as oasis expansion and contraction,providing a quantitative basis for the scientific assessment of ecosystem health and evolutionary trends.
The Zhangzi big green pepper,named after its origin in Zhangzi County,Changzhi City,Shanxi Province,is a representative specialty vegetable of the warm temperate semi-humid basin region.Located at the southwestern edge of the Shangdang Basin,Zhangzi County is one of China's key regions for facility-based pepper cultivation.In recent years,local agricultural production has gradually shifted from traditional open-field farming to a facility-oriented,standardized,and large-scale model dominated by greenhouses and plastic tunnels,forming a multi-season cropping system.The main production areas feature weakly alkaline soils with heavy metal contents far below national limits,enriched with organic matter and various available trace elements.Irrigation water quality is high,with pH and pollutant indicators meeting national standards,ensuring the ecological safety of water sources.The region also has a high vegetation coverage,with farmland accounting for nearly half of the county's total area.The big green pepper fruits are well-shaped,bright in color,thick-fleshed,juicy,and nutritionally rich,containing abundant chlorophyll and vitamin C,and are sold widely both domestically and internationally.The dataset of the GIES(Geographical Indications Environment and Sustainability)case on the Zhangzi big green pepper includes 4 categories:administrative divisions,physical geography,varietal and quality characteristics,and production management,comprising 66 files with a total data volume of 48.3 MB.
The Yellow River Basin in Qinghai covers area of northeastern edge of the Qinghai-Xizang Plateau,its wetland ecosystem is vital for waterbirds during breeding,stopover,and wintering.In August 2024,335 sites across 21 units in the basin were monitored using the plot method to obtain the monitoring dataset of waterbirds in the late breeding season in the Qinghai Section of the Yellow River Basin(2024).The dataset includes:(1)locations of sample sites and general information of 21 monitoring units;(2)species composition and numbers in each unit;(3)species composition and dominant species across the basin;(4)location,elevation,and habitat type of 335 sites;(5)waterbird species list for the basin;(6)diversity indices of waterbird communities in each unit and basin section,etc.The dataset is archived in.xlsx,.shp,.jpg and.doc formats,and consists of 19 data files with data size of 36.2 MB(compressed into one file with 35.0 MB).
Based on a litterbag decomposition experiment on Carex litter and an additive experiment with droppings from herbivorous wintering waterbirds conducted in 2017 on the beaches of Poyang Lake,this study systematically collected data on wetland organic matter decomposition and carbon,nitrogen,and phosphorus cycling.This work led to the construction of the Dataset of Poyang Lake herbivorous wintering waterbird droppings and Carex cinerascens Kükenth.decomposition.The results indicated that the addition of bird droppings significantly accelerated the decomposition of Carex litter.In the mixed treatment,the residual rates of dry matter,lignin,and cellulose of Carex(66.80％,61.03％,and 44.54％respectively after 150 days)were significantly lower than those in the single Carex treatment(71.96％,69.97％,and 62.53％).Furthermore,the nutrient release rates(Relative Return Index)of carbon,nitrogen,and phosphorus(42.73％,53.95％,and 14.65％ respectively)were significantly higher than those in the single Carex treatment(34.91％,17.96％,and 5.7％).The bird droppings themselves decomposed slowly but exhibited high nitrogen and phosphorus release characteristics.This suggests that wintering waterbirds,through excretory activities that input allochthonous nutrients and microbial communities,likely promote the decomposition of structural components(cellulose,lignin)of Carex and the net release of carbon,nitrogen,and phosphorus.This is achieved by altering substrate composition,enhancing nutrient availability,and stimulating microbial activity,thereby profoundly influencing wetland material cycling processes and carbon pool dynamics.The dataset includes:(1)geo-location information of the sample plots;(2)dry matter decomposition rate of samples;(3)lignin decomposition data;(4)cellulose decomposition data;(5)total carbon return;(6)total nitrogen return;and(7)total phosphorus return.It provides a key scientific basis for revising global carbon models and the managing of wetland ecosystems.
2025年9月2-4日,在联合国粮农组织(FAO)与中国科学院地理科学与资源研究所关于地标生境合作备忘录框架下,由FAO尼泊尔办公室、中国科学院地理科学与资源研究所、尼泊尔容县政府、尼泊尔农业与畜牧业部国立大豆蔻开发中心联合举办的"尼泊尔'一国一品'大豆蔻(Large Cardamon)项目地标生境技术实施"为主题的"地理大数据百校(乡)传播"第44场报告会在尼泊尔容县政府、尼泊尔农业与畜牧业部国立大豆蔻开发中心成功举办.
Electric power infrastructure is a crucial guarantee for production and daily life.High-voltage power grids are spread throughout the city,and high-voltage power towers are important nodes in the power network.Collapse accidents often occur,and in the event of an accident,emergency response from fire rescue is required.This study takes Guangzhou City as an example,comprehensively collects the data of the spatial distribution of high-voltage power towers,and utilizes the spatial analysis method of Geographic Information System(GIS).By analyzing the buffer zones of high-voltage power towers,roads and buildings,overlaying them to produce the adjacent risk areas,and calculating the fire rescue accessibility of high-voltage power towers,we propose a comprehensive spatial analysis method for calculating the risk areas and rescue accessibility of high-voltage power towers.The analysis process includes the statistics of the number of high-voltage power towers,the delineation of the spatial distribution of high-voltage power tower risk areas,the calculation of fire rescue time,and the calculation of fire rescue accessibility.Among them,the delineation process of high-voltage power tower risk areas includes the delineation of road-near risk areas,building-near risk areas,and comprehensive risk areas,as well as the calculation of area with risk areas and population in risk areas.This method provides a reference for the rescue operation of high-voltage power tower collapse accidents and the resilience construction of megacities.
Earthquake emergency shelters are a crucial component of the urban public safety and emergency management system.They are closely linked to national security and represent an integral part of comprehensive all-hazard emergency management.During major sudden events dominated by earthquake disasters,these evacuation sites play a critical role by providing early warning response,disaster relief,rescue operations,and temporary accommodation.Their functions help achieve the goals of safe evacuation,sheltering disaster victims,and maintaining social stability.Based on the statistical information of 180 earthquake emergency shelters released by the Beijing Emergency Management Bureau,this study utilizes the geocoding interface of internet map services to extract the geographic coordinates of each site and establish a spatial distribution dataset of earthquake emergency shelters in Beijing.The dataset includes information such as the name,type,address,XY coordinates,and total area of each site.It is archived in.shp and.xls formats,comprising 9 data files with a total data volume of 333 KB(compressed into 1 file of 47.9 KB).
2025年9月24日,由中国科学院新疆生态与地理研究所、埃及国家研究中心农业与生物研究所、中国科学院地理科学与资源研究所全球变化科学研究数据出版系统世界数据中心等单位联合研发的"世界绿洲分布数据与编目"成果在第五届世界生物圈保护大会正式发布.
Root zone soil moisture(RZSM)is a key variable linking surface water cycling with vegetation ecological processes,and it serves as an important indicator for medium-to long-term drought monitoring,agricultural water management,and ecohydrological assessment.However,current spatiotemporally continuous RZSM data face considerable challenges due to limitation in direct observation and model uncertainties.In this study,RZSM data from 2 land surface models and 3 reanalysis datasets were integrated using the Triangle Corned Hat(TCH)method to produce a daily,0.25° root zone(0-100 cm)soil moisture dataset for China's mainland covering 2018-2021.The dataset is archived in.tif format.Validation using observations from 2,061 soil moisture monitoring stations across China indicates that the fused dataset achieves a median RMSE of 0.077 m3/m3,a median correlation coefficient(r)of 0.5,a bias peak close to 0,and a median unbiased RMSE(ubRMSE)of 0.04 m3/m3.These results demonstrate that the dataset is robust and reliable,providing valuable support for regional-scale drought monitoring,eco-hydrological analyses,and agricultural applications.
Urban built-up area and core built-up area are the basic units for urban built-up environmental assessment,and their size directly affects the level of built-up environmental indicators.This paper makes full use of the advantages of multi-source big data,formulates a unified delineation method and technical process,and produces a dataset of built-up areas and core built-up areas of 19 cities,including Beijing and Shanghai,etc.(2022).For built-up area,the proportion of impervious surface,road network,POI density and population density are comprehensively considered,and high-resolution imagery are used to form a delineation index system and method for built-up area,and the scope of urban built-up area is scientifically and quickly delineated at the grid scale of 500 m×500 m.For the core built-up area,the scope of the core built-up areas of key cities is delineated through 4 steps:identifying urban centers,identifying high-density streets and towns,verifying the main functional areas and facilities of the city,and deducting the open space of large non-construction land.By unifying the data sources and delineation methods,2 basic spatial ranges with horizontal comparability in the research of urban built environment assessment are formed.The dataset is archived in.shp format and consists of 16 data files with a data size of 2.23 MB(compressed into 1 file,1.37 MB).
Zhushan County in Hubei Province of China is located in Qinling-Daba Mountain and the north-south climate transition zone of China with thousands of years of tea planting history.Survey results show that 59.38％of Zhushan County is in low mountains at an elevation of 500-1,000 m,65％ of the area has a slope of less than 25°,the annual precipitation is 959 mm,and the average annual temperature is 16℃.Except for July,the average daily sunshine duration over multiple years is less than 6 h.All soil and water quality indicators of the tea plantations meet national standards,and no pesticide residues were detected.Zhushan tea is characterized by high water extract,high soluble sugar,high amino acids,selenium content,and a unique aroma.It includes both black tea and green tea:Zhushan green tea is high in tea polyphenols and catechins,while Zhushan black tea is high in theaflavins and relatively high in Theasinensins.By the end of 2024,the registered population of Zhushan County was 440,000,among which 200,000 were tea farmers.The comprehensive output value of Zhushan's tea industry exceeded 7 billion CNY,accounting for more than half of the county's GDP.The GIES case dataset on Zhushan tea from northern subtropical low and middle mountains includes case area boundary,physical geographic environment data(elevation classification,slope classification,climate,soil,water quality,vegetation),tea characteristics,social development,brand,and culture,etc.The dataset is archived in.shp,.xlsx,.tif,.docx,and.jpg formats,consisting of 56 data files with a total size of 548 MB(compressed into 1 file of 153 MB).
Yunyang Olive is planted in the subtropical low mountain and hilly area of the Han River valley in Anyang Town and Yangxipu Town of Yunyang District,Shiyan City,Hubei Province of China,with a core area of 2,060 ha.The case area has average annual temperature of 16 ℃,annual sunshine duration of 1,768 hours,and annual precipitation of 939 mm.The soil is predominantly calcareous gravelly yellow-brown soil,with heavy metal content remains far below the national standard,and the area is free from soil environmental pollution.As a designated conservation area within China's South-to-North Water Diversion Project,all indicators of irrigation water are below the limit values specified in both the"Standards for Irrigation Water Quality"and"Environmental Quality Evaluation Standards for Farmland of Edible Agricultural Products".The case area is one of China's twelve pioneering experimental zone for olive introduction and cultivation since 1964,and a set of olive cultivation practices adapted to the local climatic conditions has been developed.This case proposes a model of core water source area protection and sustainable development of Yuyang olives,covering their ecological and geographical environment,product characteristics,cultivation techniques,and industrial operation and management.The dataset includes:(1)case study area;(2)physical geographical data;(3)olive variety characteristics data;(4)management,economic and historical cultural tradition data.The dataset is archived in.shp,.tif,.xlsx,.jpg,.txt and.doc data formats,and consists of 85 data files with data size of 169 MB(compressed into one file with 89.1 MB).
Metropolitan areas are a vital spatial unit for advancing new-type urbanization and fostering high-quality development.Scientific delineation of metropolitan boundaries is fundamental for conducting related research and guiding planning practices.Building on a clear conceptual framework,this study initially identifies central cities,then constructs an intercity human mobility network using Baidu Migration data,and finally delineates the spatial extent of China's metropolitan areas through DBSCAN(Density-Based Spatial Clustering of Applications with Noise)clustering under dominant flow constraints.The resulting dataset includes:(1)a list of metropolitan core cities and their spatial distribution,(2)a matrix of intercity human mobility intensities and the corresponding mobility network,(3)the delineated metropolitan areas and their spatial distribution.The dataset is archived in.shp and.xlsx formats,comprising 29 data files with a total size of 67.9 MB(compressed into a single file of 31.3 MB).
