1:100,000 land use dataset of Tibet 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 2020-06-11

1:100,000 land use dataset of Tibet Autonomous Region (1995)

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 2020-06-10

The surface elevation structure in Tibet Autonomous Region (1988-1994)

The data set contains the surface elevation structure data in Tibet from 1988 to 1994, including the proportions of land area at different altitudes in each year of the total land area 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 3 fields. Field 1: Year Interpretation: Year of the data Field 2: Altitude Unit: m Field 3: The proportion in land area of Tibet %

0 2020-05-28

The altitude and temperature characteristics of Tibet Autonomous Region (1988-1994)

The data set includes altitude data and temperature characteristics from 1988 to 1994 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 10 fields. Field 1: Year Interpretation: Year of the data Field 2: Location Field 3: Altitude Unit: meter Field 4: Extreme maximum temperature date Field 5: Extreme maximum temperature Unit: °C Field 6: Extreme minimum temperature date Field 7: Extreme minimum temperature Unit: °C Field 8: Annual average temperature Unit: °C Field 9: Average temperature in January Unit: °C Field 10: Average temperature in July Unit: °C

0 2020-05-28

The precipitation, hail days and gale days in Tibet Autonomous Region (1989-1994)

The data set includes data on precipitation, hail days and gale days in Tibet from 1989 to 1994. 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: Location Field 3: Annual precipitation Unit: mm Field 4: Precipitation during May to October Unit: mm Field 5: Precipitation during November to the next April Unit: mm Field 6: Hail day Field 7: Gale day

0 2020-05-28

The Area of Water System Basins in Tibet Autonomous Region (1988-2016)

The data set contains sequence data of the area composition of the water system basins in Tibet from 1988 to 2016. 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 4 fields. Field 1: Year Interpretation: Year of the data Field 2: Basin Field 3: Area Unit: Square kilometers Field 4: Proportion Unit: %

0 2020-05-28

The lakes larger than 200 k㎡ in Tibet Autonomous Region (1988-2016)

The data set includes data on lakes with areas greater than 200 square kilometers in Tibet from 1988 to 2016. 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 has 5 fields. Field 1: Year Field 2: Lake Name Field 3: Lake elevation Unit: meter Field 4: Lake area Unit: square kilometer Field 5: Lake Type

0 2020-05-28

Basic data on natural resources in the Tibetan Autonomous Region (1988-1994)

The data set contains data on the natural resources in Tibet from 1988 to 1994. The data were derived from the Tibet Society and Economics Statistical Yearbook and Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbooks. The table contains 37 fields. Field 1: Year Field 2: Total surface area of the whole region, unit: 10,000 square kilometres. Field 3: Cultivated land area, unit: 10,000 mu (1 mu=0.0667 hectares) Field 4: Paddy field area, unit: 10,000 mu (1 mu=0.0667 hectares) Field 5: Forest area, unit: 10,000 mu (1 mu=0.0667 hectares) Field 6: Forest coverage proportion, unit: % Field 7: Forest stocks, unit: 100 million cubic metres Field 8: Grassland area, unit: 100 million mu (1 mu=0.0667 hectares) Field 9: Grassland available area, unit: 100 million mu (1 mu=0.0667 hectares) Field 10: Total annual runoff of rivers, unit: 100 million cubic metres. Field 11: Hydraulic resource reserves, unit: 10,000 kilowatt Field 12: Hydraulic potential exploitation amount, unit: 10,000 kilowatt Field 13: Length of the national boundary, unit: kilometres Field 14: Iron mine reserve amount, unit: 100 million tons Field 15: Chromite reserve amount, unit: 10,000 tons Field 16: Copper (ore), unit: 100 million tons Field 17: Borate ore reserve amount, unit: 10,000 tons Field 18: Salt reserve amount, unit: 100 million tons Field 19: Graphite reserve amount, unit: 10,000 tons Field 20: Gypsum reserve amount, unit: 100 million tons Field 21: Coal reserve amount, unit: 10,000 tons Field 22: Peat reserve amount, unit: 10,000 tons Field 23: Geothermal reserve amount, unit: 10,000 cubic metres / day and night Field 24: Species number of national key protected animals Field 25: Species number of class 1 national key protected animals Field 26: Species number of class 2 national key protected animals Field 27: Species number of national key protected plants Field 28: Species number of class 1 national key protected plants Field 29: Species number of class 2 national key protected plants Field 30: Species number of class 3 national key protected plants Field 31: Number of nature reserves Field 32: Number of national nature reserves Field 33: Number of local nature reserves Field 34: Total area of nature reserves, unit: 10,000 mu Field 35: Proportion of nature reserves to the total area of the region Field 36: Annual average precipitation, unit: mm Field 37: Annual sunshine duration, unit: hour

0 2020-05-28

Basic data on nature reserves in the Tibetan Autonomous Region (1984-2012)

Among the different regions in China, Tibet contains the largest number of natural ecosystem types. It is an ideal scientific research base and a natural laboratory for the geosciences, biology and other related disciplines. To better protect this precious natural heritage, to develop and utilize the natural resources rationally and to carry out scientific research, 13 national and autonomous regional nature reserves were established in the Tibetan Autonomous Region in 1984, covering an area of 326,000 square kilometres. These reserves account for 49.3% of the total area of nature reserves in China. By the end of 2012, Tibet had established 47 nature reserves of various types, including 9 national reserves, 14 provincial reserves, 3 municipal reserves, and 21 prefectural reserves, with a total area of 412,200 square kilometres. These reserves accounted for 34.35% of the land area of the Tibetan Autonomous Region and include 22 different types of ecological function reserves. The data were extracted from the Chinese Nature Reserve Specimen Information Sharing Infrastructure. Serial number: unified number of nature reserves Name of the nature reserves Administrative region: administrative region of the nature reserves Area (hectare) Primary protection objects Type: Type of nature reserves Class: Class of the nature reserves Established time: The date the nature reserves were established Responsible authority

0 2020-05-28

1:100,000 land use dataset of Tibet Autonomous Region (2000)

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 2020-03-31