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

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

Landuse/landcover dataset of the Heihe river basin (1980s)

The data was directly clipped from China's 1:100,000 land-use data.China 1:100000 data of land use is a major application in the Chinese Academy of Sciences "five-year" project "the national resources and environment remote sensing macroscopic investigation and study of dynamic organized 19 Chinese Academy of Sciences institute of remote sensing science and technology team, by means of satellite remote sensing, in three years based on Landsat MSS, TM and ETM remote sensing data established China 1:100000 images and vector of land use database.A hierarchical land cover classification system was adopted for the land use data of heihe basin of 1:100,000, and the whole basin was divided into 6 primary categories (arable land, forest land, grassland, water area, urban and rural areas, industrial and mining areas, residential land and unused land) and 26 secondary categories.The data type is vector polygon, which is stored in Shape format.There are two types of data projection: WGS84/ALBERS;Data coverage covers the new heihe watershed boundary (lack of outer Mongolia data).

0 2020-09-07

Landuse dataset in China (1980-2015)

The remote sensing monitoring database of China's land use status is a multi temporal land use status database covering the land area of China after years of accumulation under the support of national science and technology support plan, important direction project of knowledge innovation project of Chinese Academy of Sciences. The data set includes seven periods: the end of 1980s, 1990, 1995, 2000, 2005, 2010 and 2015. The data production is based on the Landsat TM / ETM Remote Sensing Images of each period as the main data source, which is generated by manual visual interpretation. Data are missing from some islands in the South China Sea. Spatial resolution: 30m, projection parameters: Albers_ Conic_ Equal_ Area central meridian 105, standard weft 1: 25, standard weft 2: 47. The remote sensing monitoring database of China's land use status is a relatively high precision land use monitoring data product in China, which has played an important role in the national land resources survey, hydrology and ecological research. The land use types include six first-class types of cultivated land, woodland, grassland, water area, residential land and unused land, and 25 second-class types.

0 2020-08-24

Land use and land cover in Central Asia (1990-2015)

The data defines LC classes using a set of classifiers. The system was designed as a hierarchical classification, which allows adjusting the thematic detail of the legend to the amount of information available to describe each LC class, whilst following a standardized classification approach. As the CCI-LC maps are designed to be globally consistent, their legend is determined by the level of information that is available and that makes sense at the scale of the entire world. The “level 1” legend – also called “global” legend – presented in Table 3-1 meets this requirement. This legend counts 22 classes and each class is associated with a ten values code (i.e. class codes of 10, 20, 30, etc.). The CCI-LC maps are also described by a more detailed legend, called “level 2” or “regional”. This level 2 legend makes use of more accurate and regional information – where available – to define more LCCS classifiers and so to reach a higher level of detail in the legend. This regional legend has therefore more classes which are listed in Appendix 1. The regional classes are associated with nonten values (i.e. class codes such as 11, 12, etc.). They are not present all over the world since they were not properly discriminated at the global scale.

0 2020-08-18

Time space matching data set of water and soil resources in the Qinghai Tibet Plateau (1970-2016)

The matching data of water and soil resources in the Qinghai Tibet Plateau, the potential evapotranspiration data calculated by Penman formula from the site meteorological data (2008-2016, national meteorological data sharing network), the evapotranspiration under the existing land use according to the influence coefficient of underlying surface, and the rainfall data obtained by interpolation from the site rainfall data in the meteorological data, are used to calculate the evapotranspiration under the existing land use according to the different land types of land use According to the difference, the matching coefficient of water and soil resources is obtained. The difference between the actual rainfall and the water demand under the existing land use conditions reflects the matching of water and soil resources. The larger the value is, the better the matching is. The spatial distribution of the matching of soil and water resources can pave the way for further understanding of the agricultural and animal husbandry resources in the Qinghai Tibet Plateau.

0 2020-08-15

Land cover of Qing-Tibet Plateau (2012)

The dataset is the land cover of Qing-Tibet Plateau in 2012. The data format is a TIFF file, spatial resolution is 300 meters, including crop land, grassland, forest land, urban land, and so on. The dataset offers a geographic fundation for studying the interaction between urbanization and ecological reservation of Qing-Tibet Plateau. This land cover data is a product of CCI-LC project conducted by European Space Agency. The coordinate reference system of the dataset is a geographic coordinate system based on the World Geodetic System 84 reference ellipsoid. There are 22 major classes of land covers. The data were generated using multiple satellite data sources, including MERIS FR/RR, AVHRR, SPOT-VGT, PROBA-V. Validation analysis shows the overall accuracy of the dataset is more than 70%, but it varies with locations and land cover types.

0 2020-08-15