Abstract:?Surface reflectance is a key physical variable that affects the energy budget in land-atmosphere interactions, recognition and classification of surface features, and climate change research. This dataset uses the relative radiometric normalization method, and takes the Landsat 8 Operational Land Imager (OLI) surface reflectance products as the reference images to normalize GF-1 satellite WFV sensor cloud-free images of Shandong Province in 2018. Relative radiometric normalization processing includes atmospheric correction, image resampling, image registration, mask, extraction of no-change pixels and calculation of normalization coefficients. After relative radiometric normalization, the no-change pixels of each GF-1 WFV image and its reference image are as follows: R2 is above 0.7295, and RMSE is below 0.0172. In addition to that, the surface reflectance accuracy of GF-1 WFV image is improved, which can be used together with Landsat data to provide data support for remote sensing quantitative inversion. This dataset is in GeoTIFF format, and the spatial resolution of the image is 16 m.
Keywords:?GF-1 WFV;?Shandong Province;?surface reflectance;?relative radiometric normalization;?no-change pixels