This dataset is the spatial distribution map of the marshes in the source area of the Yellow River near the Zaling Lake-Eling Lake, covering an area of about 21,000 square kilometers. The data set is classified by the Landsat 8 image through an expert decision tree and corrected by manual visual interpretation. The spatial resolution of the image is 30m, using the WGS 1984 UTM projected coordinate system, and the data format is grid format. The image is divided into five types of land, the land type 1 is “water body”, the land type 2 is “high-cover vegetation”, the land type 3 is “naked land”, and the land type 4 is “low-cover vegetation”, and the land type 5 is For "marsh", low-coverage vegetation and high-coverage vegetation are distinguished by vegetation coverage. The threshold is 0.1 to 0.4 for low-cover vegetation and 0.4 to 1 for high-cover vegetation.

File naming and required software

The dataset files are uniformly packaged in the “result” folder, and the “resultgrid” grid format file can be opened using ArcGis software to view the classification results of the Yellow River source marsh. You can use the ArcGis Import Symbology feature to import a preset layer by opening the "resultgrid.lyr" layer file.

Data Citations Data citation guideline What's data citation?

Cite as:

Dai, L. (2018). Daily cloud-free snow products of MODIS in the northern hemisphere (2000-2016). A Big Earth Data Platform for Three Poles, DOI: 10.11888/Geogra.tpdc.270560. CSTR: 18406.11.Geogra.tpdc.270560. (Download the reference： RIS | Bibtex )

Related Literatures:

1. 2、Huang XD, Hao XH, Feng QS, Wang W, Liang TG. A new MODIS daily cloud free snow cover mapping algorithm on the Tibetan Plateau. Sciences in Cold and Arid Regions, 2014, 6(2):0116-0123.( View Details | Bibtex)

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

Support Program

CASEarth:Big Earth Data for Three Poles（grant No. XDA19070000） (No:XDA19000000)

Strategic Priority Research Program of the Chinese Academy of Sciences (No:XDA19070100) [XDA19070100]

Copyright & License

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