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.
The dataset covers 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. There are 54 ground samples with the No. 687 to No. 740. There are one or two landscape photos for each sample. The land use cover and vegetation type have been described in the properties. All the data tags have been carefully checked and examined.
WEI Yanqiang, WANG Xufeng. Source region of the Yangtze River - land cover and vegetation type ground verification point dataset. National Tibetan Plateau Data Center, 2019. doi: 10.11888/Ecolo.tpdc.270975. (Download the reference： RIS | Bibtex )
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Ecological Data Center of Sanjiangyuan National Park (No:SJYNP)
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| East: 94.50 | West: 93.57 |
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| South: 34.50 | North: 35.13 |
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