Distribution dataset of prehistoric era ruins on the Tibetan Plateau and its surrounding areas

This data is the distribution data of the prehistoric era sites on the Qinghai-Tibet Plateau and surrounding areas, which is derived from the Supplementary Maps of the paper: Chen, F.H., Dong, G.H., Zhang, D.J., Liu, X.Y., Jia, X., An, C.B., Ma, M.M., Xie, Y.W., Barton, L., Ren, X.Y., Zhao, Z.J., & Wu, X.H. (2015). Agriculture facilitated permanent human occupation of the Tibetan Plateau after 3600 BP. SCIENCE, 347, 248-250. The Qinghai-Tibet Plateau, with an average altitude of more than 4000m, is the highestand largest plateau all around the world, and also is one of the most unsuitable areas for human life with long-term on the earth. The remains at the archaeological site are direct evidences left behind the ancient human activities. The original data of this data is digitized from the results of the Qinghai-Tibet Plateau high-textual census and archaeological survey (Qinghai Volume and Tibet Volume of the Chinese Cultural Relics Atlas). The map was digitized mainly based on the distribution maps of the sites, and the latitude and longitude coordinates and altitude were obtained. a total of 6,950 sites, most of which are distributed in the northern part of the plateau. The age range of the site is between 7000BP and 2300BP. This data set is of reference value for the research on the process and power of human diffusion to the Tibetan Plateau in the prehistoric era and other studies related to human activities in the Tibetan Plateau and the prehistoric era.

0 2020-11-11

Source region of Yellow River - land cover and vegetation type ground verification point dataset

The dataset is the ground verification point dataset of land cover and vegetation type in the Source Region of Yellow River (in the north of Zaling Lake, Qinghai Province) which collected during August 2018. In the dataset, the homogeneous patches are considered as the main targets of this collection. They are easy to be recognized out and distinguished from other vegetation types. And these samples have high representativeness comparing with other land surface features. In each sample, the geographical references, longitude and latitude (degree, minute, second), time (24h) and elevation (0.1m) are recorded firstly according to GPS positioning. Vegetation types, constructive species, characteristics, land types and features, landmarks, etc. are recorded into the property table manually for checking in laboratory. At last, each sample place has been taken at least 1 photography. In this dataset, 90% or more samples have been taken 2 or more in field landscape photographs for land use type and vegetation classification examination. We have carefully examined the position accuracy of each sample in Google Earth. After 2 rounds of checking and examination, the accuracy and reliability of the property of each sample have been guaranteed.

0 2020-10-13

Hoh Xil - land cover and vegetation type ground verification point dataset

The dataset is the ground verification point dataset of land cover and vegetation type in the Hoh Xil (in the northwest of Qinghai Province) which collected during August 2018. In the dataset, the homogeneous patches are considered as the main targets of this collection. They are easy to be recognized out and distinguished from other vegetation types. And these samples have high representativeness comparing with other land surface features. In each sample, the geographical references, longitude and latitude (degree, minute, second), time (24h) and elevation (0.1m) are recorded firstly according to GPS positioning. Vegetation types, constructive species, characteristics, land types and features, landmarks, etc. are recorded into the property table manually for checking in laboratory. At last, each sample place has been taken at least 1 photography. In this dataset, 90% or more samples have been taken 2 or more in field landscape photographs for land use type and vegetation classification examination. We have carefully examined the position accuracy of each sample in Google Earth. After 2 rounds of checking and examination, the accuracy and reliability of the property of each sample have been guaranteed.

0 2020-10-13

Source region of the Yangtze River - land cover and vegetation type ground verification point dataset

The dataset is the ground verification point dataset of land cover and vegetation type in the Source Region of the Yangtze River (in the south of Qinghai Province) which collected during August 2018. In the dataset, the homogeneous patches are considered as the main targets of this collection. They are easy to be recognized out and distinguished from other vegetation types. And these samples have high representativeness comparing with other land surface features. In each sample, the geographical references, longitude and latitude (degree, minute, second), time (24h) and elevation (0.1m) are recorded firstly according to GPS positioning. Vegetation types, constructive species, characteristics, land types and features, landmarks, etc. are recorded into the property table manually for checking in laboratory. At last, each sample place has been taken at least 1 photography. In this dataset, 90% or more samples have been taken 2 or more in field landscape photographs for land use type and vegetation classification examination. We have carefully examined the position accuracy of each sample in Google Earth. After 2 rounds of checking and examination, the accuracy and reliability of the property of each sample have been guaranteed.

0 2020-10-13

1:100,000 land use dataset of Xinjiang Uygur Autonomous Region (1980s)

This data was derived from "1: 100,000 Land Use Data of China". Based on Landsat MSS, TM and ETM remote sensing data, 1: 100,000 Land Use Data of China was compiled within three years by a remote sensing scientific and technological team of 19 research institutes affiliated to the Chinese Academy of Sciences, which was organized by the “Remote Sensing Macroinvestigation and Dynamic Research on the National Resources and Environment", one of the major application programs in Chinese Academy of Sciences during the "Eighth Five-year Plan". This data adopts a hierarchical land cover classification system, which divides the country into 6 first-class categories (cultivated land, forest land, grassland, water area, urban and rural areas, industrial and mining areas, residential land and unused land) and 31 second-class categories. This is the most accurate land use data product in our country at present. It has already played an important role in national land resources survey, hydrology and ecological research.

0 2020-10-12

Administrative divisions of counties in Qinghai province (1992-2016)

The data set contains the Chinese name, English name and the affiliation between the districts and counties in each administrative division of Qinghai. The data were derived from the Qinghai Society and Economics Statistical Yearbook and the Qinghai Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbook. Table 1: The table of administrative divisions in Qinghai has 5 fields. Field 1: Regions Interpretation: Chinese names of the regions Field 2: English names of the regions Interpretation: English names of the regions Field 3: Districts and counties Interpretation: Chinese names of the districts and counties Field 4: English names of the districts and counties Interpretation: English names of the districts and counties Field 5: Land area Unit: square kilometers Table 2: The table of division changes of each county has 5 fields. Field 1: Districts and counties Field 2: Year Field 3: Area Unit: square kilometers Field 4: Number of townships Field 5: Number of Village Committees

0 2020-10-09

The Birth, Mortality, and Natural Growth Rate of Qinghai (1952-2016)

This data set contains data on the birth rate, mortality rate and natural growth rate in Qinghai. The data were derived from the Qinghai Society and Economics Statistical Yearbook and Qinghai Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbooks. The table contains 8 fields. Field 1: Year of the data Field 2: The number of permanent residents, unit: 10,000 Field 3: The number of births Field 4: Birth rate, unit: ‰ Field 5: The number of deaths Field 6: Mortality rate, unit: ‰ Field 7: Natural growth of the population Field 8: Natural growth rate, unit: ‰

0 2020-10-09

The statistic data of highways, bridges and ferries in Tibet Autonomous Region (1954-2016)

The data set recorded the sequence data of highway traffic mileage, all-weather traffic mileage, highway maintenance, number of bridges, bridge length and ferries from 1954 to 2016 in Tibet. The data were derived from the Tibet Society and Economics Statistical Yearbook and the Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbook. The table contains 7 fields. Field 1: Year Interpretation: Year of the data Field 2: Highway traffic mileage Interpretation: Highway traffic mileage Unit: kilometer Field 3: All-weather traffic mileage Unit: kilometer Field 4: Highway maintenance Interpretation: Highway maintenance mileage Unit: kilometer Field 5: Number of bridges Interpretation: Total number of bridges Field 6: Bridge length Interpretation: Total length of the bridges Unit: meter Field 7: Ferries Interpretation: Number of ferries

0 2020-10-09

The lakes larger than 1k㎡ in Tibetan Plateau (V1.0) (1970s, 1990, 2000, 2010)

The dataset includes vector map of the lakes larger than 1k㎡ on Tibetan Plateau in 1970s, 1990, 2000, 2010. The lake boundry data was extracted from remote sensing image like Landsat MSS, TM, ETM+, by means of visual interpretation. The data type is vector data, and it's attribute class includes Area (km²). The Projected Coordinate System is Albers Conical Equal Area. It is mainly used in the study of changes in lakes, hydrological and meteorological on the Tibetan Plateau.

0 2020-10-09

Land use change in the midstream of Heihe River Basin

According to the statistical yearbook, different types of land use change areas in the middle reaches of China since liberation were collected and sorted out.

0 2020-09-30