Data scarcity is a major obstacle for high-resolution mapping of permafrost on the Tibetan Plateau (TP). This study produces a new permafrost stability distribution map for the 2010s (2005-2015) derived from the predicted mean annual ground temperature (MAGT) at a depth of zero annual amplitude (10 - 25 m) by integrating remotely sensed freezing degree-days and thawing degree-days, snow cover days, leaf area index, soil bulk density, high-accuracy soil moisture data, and in situ MAGT measurements from 237 boreholes on the TP by using an ensemble learning method that employs a support vector regression (SVR) model based on distance-blocked resampling training data with 200 repetitions. Validation of the new permafrost map indicates that it is probably the most accurate of all available maps at present. This map shows that the total area of permafrost on the TP, excluding glaciers and lakes, is approximately 115.02 (105.47-129.59) ✖104 km2. The areas corresponding to the very stable, stable, semi-stable, transitional, and unstable types are 0.86✖104 km2, 9.62✖104 km2, 38.45✖104 km2, 42.29✖104 km2, and 23.80✖104 km2, respectively. This new map is of fundamental importance for engineering planning and design, ecosystem management, and evaluation of the permafrost change in the future on the TP as a baseline.
China's second glacier inventory uses the high-resolution Landsat TM/ETM+ remote sensing satellite data as the main glacier boundary data source and extracts the data source with the latest global digital elevation model, SRTM V4, as the glacier attribute, using the current international ratio threshold segmentation method to extract the glacier boundary in bare ice areas. The ice ridge extraction algorithm is developed to extract the glacier ice ridge, and it is used for the segmentation of a single glacier. At the same time, the international general algorithm is used to calculate the glacier attributes, so that the vector data and attribute data that contain the glacier information of the main glacier regions in west China are obtained. Compared with some field GPS field measurement data and higher resolution remote sensing images (such as from QuickBird and WorldView), the glacial vector data in the second glacier inventory data set of China have higher positioning accuracy and can meet the requirements for glacial data in national land, water conservancy, transportation, environment and other fields. Glacier inventory attributes: Glc_Name, Drng_Code, FCGI_ID, GLIMS_ID, Mtn_Name, Pref_Name, Glc_Long, Glc_Lati, Glc_Area, Abs_Accu, Rel_Accu, Deb_Area, Deb_A_Accu, Deb_R_Accu, Glc_Vol_A, Glc_Vol_B, Max_Elev, Min_Elev, Mean_Elev, MA_Elev, Mean_Slp, Mean_Asp, Prm_Image, Aux_Image, Rep_Date, Elev_Src, Elev_Date, Compiler, Verifier. For a detailed data description, please refer to the second glacier inventory data description.
In the permafrost area of the upper reaches of Heihe River, 11 numbered typical boreholes are selected, and the thickness values of permafrost and seasonal permafrost are calculated by the temperature interpolation of boreholes. The 0 degree isothermal surface is set as the bottom plate of permafrost and seasonal permafrost. The data include borehole number, longitude and latitude, thickness of frozen soil and type of frozen soil.
This data includes the distribution along the height of the blowing snow flux collected during the wind-blown snow event at the big winter tree pass observation station (longitude 100 degrees 14 minutes 28 seconds east and latitude 38 degrees 00 minutes 58 seconds north) on December 17, 2013 at solstice on July 9, 2014.
Glaciers are sensitive to climate change and are important indicators and amplifiers of global change. In inland river regions, river runoff mainly comes from mountain ice and snow melt. Glaciers are very important "solid reservoirs" in these regions, and glacial melt water is an important source of supply for the tributaries of the Heihe River. The inventory of glaciers in the Heihe River Basin was completed from 1979 to 1980. For related information, please refer to "Chinese Glacier Inventory-Qilian Mountains" edited by Wang Zongtai and others. In 2004, the relevant results of the "China Glacier Inventory" were systematically digitized and a database was established. The final results were released through the "China Glacier Information System". However, in the process of coordinate restoration, the accuracy of the reference data was poor, and the glaciers in the Heihe River Basin had obvious position shifts. Therefore, we used the Landsat remote sensing image corrected by ortho-geometric correction. The processed Heihe Glacier distribution data is highly consistent with the existing basic geographic information in China in terms of geometric accuracy, and consistent with the first glacier inventory in terms of attributes.
This data set is extracted from the second Glacier Inventory Data Set of China for Three River Source area. The file is SHP format. The attribute data are as follows: Glc_Name (glacier name), Drng_Code (basin code), FCGI_ID (first glacier catalogue code), GLIMS_ID (GLIMS glacier code), Mtn_Name (mountain system name), Pref_Name (administrative division), Glc_Long (glacier longitude), Glc_Lati (glacier latitude), Glc_Area (glacier area), Abs_Accu (absolute area accuracy), Rel_Accu (relative area accuracy), Deb_Area (surface Moraine Area), Deb_A_Accu (absolute accuracy of surface moraine Area), Deb_R_Accu (relative accuracy of surface moraine area)、Glc_Vol_A (estimation of glacier volume 1)、Glc_Vol_B (estimation of glacier volume 2)、Max_Elev (maximum glacier elevation)、Min_Elev (minimum glacier elevation)、Mean_Elev (average glacier elevation)、MA_Elev (median area height of glacier)、Mean_Slp (average glacier slope)、Mean_Asp (average glacier slope direction)、Prm_Image (major remote sensing data)、Aux_Image (auxiliary remote sensing data)、Rep_Date (glacier catalogue represents date)、Elev_Src (elevation data source)、Elev_Date (elevation represents date)、Compiler (glacier cataloguing editor)、Verifier (glacier cataloguing verifier).
From 1982 to 2015, the NDVI change data sets of different types of permafrost regions in the northern hemisphere have a temporal resolution of once every five years, covering the entire Arctic countries with a spatial resolution of 8km. Based on multi-source remote sensing, simulation, statistics and measured data, the regulation and service functions of Permafrost on Ecosystem in the northern hemisphere are quantified by using GIS and ecological methods, All the data are under quality control.
This map was compiled by Li Xin and others in 2008 in order to re-count the permafrost area in China and based on the analysis of the existing permafrost map in China. It consists of three parts, of which the Qinghai-Tibet Plateau part uses the simulated permafrost map of the Qinghai-Tibet Plateau (Nanzhuo Copper, 2002), the northeast part comes from the "14 million map of China's Glacier, Frozen Soil and Desert" (Institute of Environment and Engineering in Cold and Arid Regions, Chinese Academy of Sciences, 2006), and the other part uses the map of China's permafrost zoning and types (1: 10 million) (Zhou Youwu and others, 2000). More Information References (Institute of Environment and Engineering in Cold and Arid Regions, Chinese Academy of Sciences, 2006; Nanzhuo Copper, 2002; Zhou Youwu et al., 2000; Li et al, 2008）。
Snow pits were observed daily at Altay base station（lon：88.07、lat: 44.73） from November 27, 2015 to March 26, 2016. Parameters include: snow stratification, stratification thickness, density, particle size, temperature. The frequency of observation was daily. The particle size was observed by a microscope with camera, the density was observed by snowfork, snow shovel and Snow Cone, and the temperature was automatically observed by temperature sensor. The observation time was 8:00-10:100 am local time. The snow particle size is observed according to the natural stratification of snow. The snow particles of each layer are collected, and at least 2 photos are taken. The long axis and short axis of at least 10 groups of particles are measured by corresponding software. Unit: mm. The density was observed at equal intervals, snowfork every 5 cm, snow shovel every 10 cm, snow cone to observe the density of the whole snow layer, and the density of each layer was observed three times. The unit is g / cm3. The height of temperature observation is 0cm, 5cm, 10cm, 15cm, 25cm, 35cm, 45cm, 55cm. The recording frequency was once every 1 minute. The unit is OC.
The data set includes the mass balances of Hailuogou Glacier, Parlung No.94 Glacier, Qiyi glacier, Xiaodongkemadi Glacier, Muztagh No.15 Glacier, Meikuang Glacier and NM551 Glacier in the Qinghai Tibet Plateau from 1975 to 2013. Based on several mass balance observations collected from World Glacier Inventory (https://nsidc.org/data/g10002/versions/1) and The Third Pole Environment Database (http://en.tpedatabase.cn/, doi:10.11888/GlaciologyGeocryology.tpe.96.db) by Tandong Yao and the meteorological data obtained from Global Land Assimilation System (GLDAS), the mass balances of the above seven glaciers from 1975 to 2013 are reconstructed by using the glacier material balance calculation formula. This reconstruction data is based on the published glacier material balance data to calibrate the parameters in the glacier material balance formula, and to reconstruct the long-time series material balance by using the glacier material balance formula, in which the parameter calibration results and the reconstruction results of the long-time series data are compared with the relevant research results, demonstrating the rationality of the data results Please refer to the following papers. The data can be used to study the change of water resources in the glacial region, expand the data set of Glacier Mass Balance in the Qinghai Tibet Plateau, and provide reference for the future research of Glacier Mass Balance reconstruction.
Contact SupportNorthwest Institute of Eco-Environment and Resources, CAS 0931-4967287 email@example.com
LinksNational Tibetan Plateau Data Center