High spatial and temporal resolution multispectral remote sensing images (2000 to 2016) of the Belt and Road key node areas
High spatial and temporal resolution remote sensing image plays a very important role in land use change detection, disaster monitoring and bio-geochemical parameter estimation.Currently, Landsat multi-spectral series satellite data (including Landsat TM, ETM+ and OLI multi-spectral bands) is one of the most widely used multi-spectral data.Taking the One Belt And One Road key node area as the research area, and based on the data of Landsat TM/ETM+/OLI series with good quality from 2000 to 2016, python was used to clip the data in the research area with the masks .To solve the partial data missing problem, MODIS imagery on the missing date and Landsat-MODIS data pair of adjacent phases are combined for spatio-temporal fusion to obtain Landsat-like data.Finally, the high spatial and temporal resolution remote sensing images of 34 key node area during 2001 to 2016 lasted for 8 to 16 days was obtained.
Multispectral remote sensing images are stored in raster format with the file name "yyyy-mm-dd.tif ”For example, 2000-01-13.tif represents this raster file describing the multispectral remote sensing image of January 13, 2000
Yin, Z., Ling, F. (2020). High spatial and temporal resolution multispectral remote sensing images (2000 to 2016) of the Belt and Road key node areas. A Big Earth Data Platform for Three Poles, (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.
1.X. Li, G. M. Foody, D. S. Boyd, Y. Ge, Y. Zhang, Y. Du and F.Ling, “SFSDAF: An enhanced FSDAF that incorporates sub-pixel class fraction change information for spatio-temporal image fusion,” Remote Sensing of Environment, vol. 237, pp. 111537, 2020. (View Details )
Pan-Third Pole Environment Study for a Green Silk Road-A CAS Strategic Priority A Program (No:XDA20000000)
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