Find research datasets worth reusing

opencc-by-4.0Oct 2023View details →

Long-Term Net Primary Productivity Dataset of the Tibetan Plateau from 1982 to 2013

<ul><li>This dataset is generated by the advanced CASA model, encompassing vegetation net primary productivity (NPP) raster data for the Tibetan Plateau from 1982 to 2013. The model's input parameters comprise NDVI time series, monthly average temperature, monthly total precipitation, monthly total solar radiation, and vegetation type. The data is provided at an 8 km × 8 km spatial resolution and is formatted in ENVI format (.dat).</li><li>Remarkably, during cross-validation with the MODIS 500m resolution product (MOD17A3HGF.061), it exhibited significantly strong correlations, with the correlation coefficients (R) ranging from 0.74 to 0.82.</li><li>Please cite this dataset as Tan, Q., Sun, G., & Pang, Y. (2023). Long-Term Net Primary Productivity Dataset of the Tibetan Plateau from 1982 to 2013 (V1.0) [Data set]. Zenodo. https://doi.org/<a href="https://doi.org/10.5281/zenodo.10040818">10.5281/zenodo.10040818</a></li></ul>

opencc-by-4.0Dec 2023View details →

Integrated disturbance mapping over the Tibetan Plateau based on multiple detection algorithms

This dataset contains the mapped representation of vegetation disturbance across the Tibetan Plateau, rendered at a 30-meter spatial resolution. The dataset comprehensively illustrates the extent of vegetation disturbance on the Tibetan Plateau during the period spanning 1986 to 2020. Notably, the map employs a categorization system, with values assigned to distinct classes: 0 denotes areas of disturbed vegetation, 1 denotes regions characterized by undisturbed vegetation, and 2 denotes zones devoid of vegetation.

opencc-by-4.0Nov 2021View details →

Seasonal Terrestrial Water Load Modulation of Seismicity at the Southeastern Margin of the Tibetan Plateau Constrained by GNSS and GRACE Data

Data Set S1. The earthquake catalog is used to decluster aftershocks and background events, and the time range is from July 2004 to July 2021. This data set includes 672585 events in the study area. Data Set S2. Focal mechanism solutions of M ≥ 4 earthquakes at the southeastern margin of the Tibetan Plateau. The data set includes 634 solutions of earthquakes M ≥ 4, and the time range is from 2009 to 2017.

opencc-by-4.0Apr 2022View details →

Geographical and geological GIS boundaries of the Tibetan Plateau and adjacent mountain regions

Introduction Geographical scale, in terms of spatial extent, provide a basis for other branches of science. This dataset contains newly proposed geographical and geological GIS boundaries for the Pan-Tibetan Highlands (new proposed name for the High Mountain Asia), based on geological and geomorphological features. This region comprises the Tibetan Plateau and three adjacent mountain regions: the Himalaya, Hengduan Mountains and Mountains of Central Asia, and boundaries are also given for each subregion individually. The dataset will benefit quantitative spatial analysis by providing a well-defined geographical scale for other branches of research, aiding cross-disciplinary comparisons and synthesis, as well as reproducibility of research results. The dataset comprises three subsets, and we provide three data formats (.shp, .geojson and .kmz) for each of them. Shapefile format (.shp) was generated in ArcGIS Pro, and the other two were converted from shapefile, the conversion steps refer to 'Data processing' section below. The following is a description of the three subsets: (1) The GIS boundaries we newly defined of the Pan-Tibetan Highlands and its four constituent sub-regions, i.e. the Tibetan Plateau, Himalaya, Hengduan Mountains and the Mountains of Central Asia. All files are placed in the "Pan-Tibetan Highlands (Liu et al._2022)" folder. (2) We also provide GIS boundaries that were applied by other studies (cited in Fig. 3 of our work) in the folder "Tibetan Plateau and adjacent mountains (Others’ definitions)". If these data is used, please cite the relevent paper accrodingly. In addition, it is worthy to note that the GIS boundaries of Hengduan Mountains (Li et al. 1987a) and Mountains of Central Asia (Foggin et al. 2021) were newly generated in our study using Georeferencing toolbox in ArcGIS Pro. (3) Geological assemblages and characters of the Pan-Tibetan Highlands, including Cratons and micro-continental blocks (Fig. S1), plus sutures, faults and thrusts (Fig. 4), are placed in the "Pan-Tibetan Highlands (geological files)" folder. Note: High Mountain Asia: The name ‘High Mountain Asia’ is the only direct synonym of Pan-Tibetan Highlands, but this term is both grammatically awkward and somewhat misleading, and hence the term ‘Pan-Tibetan Highlands’ is here proposed to replace it. Third Pole: The first use of the term ‘Third Pole’ was in reference to the Himalaya by Kurz & Montandon (1933), but the usage was subsequently broadened to the Tibetan Plateau or the whole of the Pan-Tibetan Highlands. The mainstream scientific literature refer the ‘Third Pole’ to the region encompassing the Tibetan Plateau, Himalaya, Hengduan Mountains, Karakoram, Hindu Kush and Pamir. This definition was surpported by geological strcture (Main Pamir Thrust) in the western part, and generally overlaps with the ‘Tibetan Plateau’ sensu lato defined by some previous studies, but is more specific. More discussion and reference about names please refer to the paper. The figures (Figs. 3, 4, S1) mentioned above were attached in the end of this document.   Data processing We provide three data formats. Conversion of shapefile data to kmz format was done in ArcGIS Pro. We used the Layer to KML tool in Conversion Toolbox to convert the shapefile to kmz format. Conversion of shapefile data to geojson format was done in R. We read the data using the shapefile function of the raster package, and wrote it as a geojson file using the geojson_write function in the geojsonio package.   Version Version 2022.1.   Acknowledgements This study was supported by the Strategic Priority Research Program of Chinese Academy of Sciences (XDB31010000), the National Natural Science Foundation of China (41971071), the Key Research Program of Frontier Sciences, CAS (ZDBS-LY-7001). We are grateful to our coauthors insightful discussion and comments. We also want to thank professors Jed Kaplan, Yin An, Dai Erfu, Zhang Guoqing, Peter Cawood, Tobias Bolch and Marc Foggin for suggestions and providing GIS files.   Citation Liu, J., Milne, R. I., Zhu, G. F., Spicer, R. A., Wambulwa, M. C., Wu, Z. Y., Li, D. Z. (2022). Name and scale matters: Clarifying the geography of Tibetan Plateau and adjacent mountain regions. Global and Planetary Change, In revision   Jie Liu & Guangfu Zhu. (2022). Geographical and geological GIS boundaries of the Tibetan Plateau and adjacent mountain regions (Version 2022.1). https://doi.org/10.5281/zenodo.6432940   Contacts Dr. Jie LIU: E-mail: <a>liujie@mail.kib.ac.cn</a>; Mr. Guangfu ZHU: <a>zhuguangfu@mail.kib.ac.cn</a> Institution: Kunming Institute of Botany, Chinese Academy of Sciences Address: 132# Lanhei Road, Heilongtan, Kunming 650201, Yunnan, China   Copyright This dataset is available under the Attribution-ShareAlike 4.0 International (<a href="https://creativecommons.org/licenses/by-sa/4.0/">CC BY-SA 4.0</a>).

opencc-by-4.0May 2022View details →

Data file for: Three-Dimensional Electrical Imaging Across the Cona Woka Rift and Yalaxiangbo Dome in Southern Tibetan Plateau

The magnetotellurics data were used to study  the lithospheric electrical  structure across the Cona Woka rift and Yalaxiangbo dome in the southern Tibetan plateau, conducted by Institute of Geophysical and Geochemical Exploration, Chinese Academy of Geological Sciences.  The data file of CN6.dat was generated by the Matlab code EM3DVP. You are recommended to refer to the Kelbert et al., 2014 paper: https://doi.org/10.1016/j.cageo.2014.01.010 for a brief understanding of the data file formats.

opencc-by-4.0Jul 2022View details →

Intensified atmospheric branch of the hydrological cycle over the Tibetan Plateau during the Last Interglacial from a dynamical downscaling perspective

We provide the datasets run for investigating the atmospheric branch of the hydrological cycle over the Tibetan Plateau during the Last Interglacial (127 ka), based on the  mesoscale Weather Research and Forecasting (WRF) model driven by the Community Earth System Model (CESM). We upload summer mean of the model outputs from the WRF over the Tibetan Plateau used in estimating the atmospheric branch of the hydrological cycle.

opencc-by-4.0Feb 2024View details →

The 0.1° stem area index dataset over Tibetan Plateau from 1981 to 2018

Description: Based on the method of Zeng et al. (2002), we built the monthly stem area index (Ls) data product over the Tibetan Plateau (TP) at 0.1°×0.1° spatial resolution from 1981-09 to 2018-12 by using leaf area index data (LAI) from GLASS (Liang et al., 2021) and grass fractional cover data from Lawrence and Chase (2007). Here, We revised the method, considering that grass is completely green (no WGS) from May to August, the Ls,min is set to 0; in September when the grass begins to wither (Xiao et al., 2023), its Ls value is obtained by subtracting the Lgv in September from that in August; from October (when grass turns completely withered) to the April of next year, the Ls is calculated without adding of withered leaves, considering the small magnitude of LAI (<0.2) in non-growing season; the monthly remaining rate of withered leaves and stems (α) is obtained from the observed total area of leaf and stem data of Xiao et al. (2023), which actually represents the neutralization of monthly removal of dead leaves and the withering part, especially in October. The calculation of Ls starts from September, 1981. Based on the above, the Ls is calculated on the sub-grid scale, then it multiplies by the fractional vegetation cover of grass to obtain the stem area index on the grid scale. Dataset Characteristics: Spatial Coverage: 75º~105ºE, 25º~40ºN;  Temporal Coverage: Sep. 1981-Dec. 2018;  Spatial Resolution: 0.1º;  Temporal Resolution: Monthly;  Data Format: NetCDF. Citation: Qi, Q., Yang, K., Li, H., Ai, L., Wang, C., Wu, T. (2024). Negative impacts of the withered grass stems on winter snow cover over the Tibetan Plateau. Agric. For. Meteorol., 352, 110053. https://doi.org/10.1016/j.agrformet.2024.110053 If you have any questions, please contact Dr. Kai Yang (yangkai@lzu.edu.cn)

opencc-by-4.0Jul 2024View details →

Typical Village UAV Aerial Photography Dataset in northeastern Tibetan Plateau (2022)

This dataset was collected during a field survey in the Hehuang Valley, located in the northeastern Tibetan Plateau, in July and August 2022. Using a DJI Mavic 2 Pro equipped with a Hasselblad L1D-20c camera, over 4,600 aerial photographs were captured from 55 typical villages across the region. These images were processed into high-resolution orthophotos using Agisoft PhotoScan 1.25 software, resulting in ultra-high-precision orthophoto data for the 55 villages. The "Village Information" section provides detailed information on each village, including its full name, abbreviation, latitude and longitude coordinates, and elevation. This dataset accurately reflects the overall situation, spatial patterns, and surrounding environment of the typical villages, offering a high-resolution data source for spatial structure analysis, land use mapping, and correction tasks.

opencc-by-4.0Jul 2024View details →

Ultra-high Resolution Land Use Data Set of Typical Villages in Northeastern Tibetan Plateau

This dataset was collected by a research team during a field investigation in the Hehuang Valley of Qinghai Province from July to August 2022. Using the DJI Mavic2pro equipped with a Hasselblad L1D-20c camera, 55 typical villages were selected in the Hehuang Valley and over 4600 aerial photographs were obtained using drone photogrammetry technology as raw data. Using AgisfphotoScan 1.25 software to synthesize orthophoto images with a spatial resolution of 0.05m. The vector data of human settlement boundaries in villages was extracted through visual interpretation. Based on the object-oriented human-machine interaction interpretation method, 55 typical village land use datasets in 2022 were obtained (including forests, grasslands, forest land, cultivated land, water bodies, roads, unused land, and building land, totaling 8 categories). By establishing 1050 sample points and using confusion matrix analysis, it was found that the overall accuracy of the dataset was 96.86%, with a Kappa coefficient of 0.95. It can accurately reflect the spatial form, land use composition, and surrounding environment of typical villages. Aerial photographs all have longitude, latitude, and altitude information, providing ultra-high resolution data sources for village spatial structure analysis, land use mapping, and analysis work, effectively assisting in the improvement of human housing and rural revitalization strategies.

opencc-by-4.0Aug 2022View details →

Validation of MODIS11A2 LST and glacier surface heatwave during 2001-2020 over Tibetan Plateau

1,Validation of MODIS11A2 LST in  2019 using AWS temperature on the glacier 2,Validation of MODIS11A2 LST during 2001-2020 using CMA station temperature over the Tibetan Plateau 3,Glacier surface heatwave during 2001-2020 over the Tibetan Plateau glacier

edi44/100

Phenotypic trait variation of Herminium monorchis in the Qinghai-Tibetan Plateau with grazing intensity and climatic conditions

This data set contains raw data supporting the research entitled “Livestock grazing outweighs climate in driving trait variation of a widespread alpine plant” (currently under peer review), which documents how phenotypic traits of a widespread herbaceous plant in the Qinghai-Tibetan Plateau, Herminium monorchis, vary with grazing intensity and environmental conditions.

openCC0Mar 2023View details →

Figure 10 in A new species of crown-antlered deer Stephanocemas (Artiodactyla, Cervidae) from the middle Miocene of Qaidam Basin, northern Tibetan Plateau, China, and a preliminary evaluation of its phylogeny

Figure 10. Species ranges, phyletic relationship, and zoogeographical positions of the Paradicrocerus–Stephanocemas clade. Most of the species ranges are approximate. Phyletic relationship is based on one of the shortest trees in our cladistic analysis, and some indeterminate taxa not included in the cladogram are inserted here based on our estimates of their relationships. The antlers are scaled to their approximate relative size, and dashed lines are mostly our own reconstructions of missing tines.

Figure 9 in A new species of crown-antlered deer Stephanocemas (Artiodactyla, Cervidae) from the middle Miocene of Qaidam Basin, northern Tibetan Plateau, China, and a preliminary evaluation of its phylogeny

Figure 9. Strict consensus of four shortest trees (tree length = 12) of the Paradicrocerus–Stephanocemas clade found by the branch and bound option of the PAUP program on a ten taxa ¥ nine characters data matrix (Table 1).

Figure 8. IVPP V15726 in A new species of crown-antlered deer Stephanocemas (Artiodactyla, Cervidae) from the middle Miocene of Qaidam Basin, northern Tibetan Plateau, China, and a preliminary evaluation of its phylogeny

Figure 8. IVPP V15726, Stephanocemas sp. from IVPP locality CD0406. A, dorsal, and B, ventral views of antler fragment. Scale is for both views.

Figure 6. IVPP V15724 in A new species of crown-antlered deer Stephanocemas (Artiodactyla, Cervidae) from the middle Miocene of Qaidam Basin, northern Tibetan Plateau, China, and a preliminary evaluation of its phylogeny

Figure 6. IVPP V15724, referred specimen of Stephanocemas palmatus sp. nov. A, dorsal, B, ventral, and C, medial views of posterior palm portion of a juvenile antler.

Figure 7. IVPP V15725 in A new species of crown-antlered deer Stephanocemas (Artiodactyla, Cervidae) from the middle Miocene of Qaidam Basin, northern Tibetan Plateau, China, and a preliminary evaluation of its phylogeny

Figure 7. IVPP V15725, Stephanocemas sp. from IVPP locality CD9818. A, stereophoto of dorsal view, B, lateral view, and C, ventral view of partial antler.

Figure 5. IVPP V15723 in A new species of crown-antlered deer Stephanocemas (Artiodactyla, Cervidae) from the middle Miocene of Qaidam Basin, northern Tibetan Plateau, China, and a preliminary evaluation of its phylogeny

Figure 5. IVPP V15723, referred specimen of Stephanocemas palmatus sp. nov. A, dorsal, and B, ventral views of palm portion of antler.

Figure 4. IVPP V15722 in A new species of crown-antlered deer Stephanocemas (Artiodactyla, Cervidae) from the middle Miocene of Qaidam Basin, northern Tibetan Plateau, China, and a preliminary evaluation of its phylogeny

Figure 4. IVPP V15722, left antler without pedicel, holotype of Stephanocemas palmatus sp. nov. from Qaidam Basin, northern Tibetan Plateau. A, medial, and B, ventral views. Left is posterior and right is anterior.