Spatiotemporal variation map of temperate grassland types in Eurasia- Inner Mongolia region three class classification (2009)- A Big Earth Data Platform for Three Poles

This data set is a spatiotemporal variation map of temperate grassland types in Eurasia - three level classification of Inner Mongolia region of China (2009). The data is in TIF grid format with a spatial resolution of 1km. The data is processed on the basis of the existing grass type map of Inner Mongolia grassland. The grassland type map of Inner Mongolia grassland is based on the field survey data, neimengqi County as the unit, the grassland type classification system, on the basis of prediction, the field sample data, remote sensing image and other information data are superposed, and the local historical grassland survey data and relevant data are referred to, and the field plot is modified.

We select 2000-2009 historical meteorological data, further analyze and modify the satellite data, and carry out spatial interpolation calculation. The classification of temperate grassland in Inner Mongolia was obtained. The data can be used to provide the basis for the distribution information and temporal and spatial variation analysis of warm grassland in Eurasia.

File naming and required software

The file naming rules: region + time + theme, and the file format is standard TIF and jpg.
Data reading: remote sensing image processing software such as ENVI can be used to read and use.

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Cite as:

Tang, J. (2020). Spatiotemporal variation map of temperate grassland types in Eurasia- Inner Mongolia region three class classification (2009). A Big Earth Data Platform for Three Poles, DOI: 10.11888/Ecolo.tpdc.270424. CSTR: 18406.11.Ecolo.tpdc.270424. (Download the reference： RIS | Bibtex )

Using this data, the data citation is required to be referenced and the related literatures are suggested to be cited.

Support Program

Pan-Third Pole Environment Study for a Green Silk Road-A CAS Strategic Priority A Program (No:XDA20000000)

Copyright & License

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License： This work is licensed under an Attribution 4.0 International (CC BY 4.0)