An Efficient and Effective Approach for Georeferencing AVHRR and GaoFen-1 Imageries Using Inland Water Bodies

National Oceanography and Atmosphere Administration's Advanced Very High Resolution Radiometer (AVHRR) (1970s–present, ∼1 km) and China's GaoFen-1 (GF-1) image series (2013–present, ∼16 m), can both provide extremely useful information of land use and land cover, due to the long history and, wide scanning width of AVHRR and the high resolution of GF-1. However, both data sets have apparent weaknesses of large and inconsistent geometric and geolocation errors (AVHRR: 1–20 pixels, GF-1: 1–10 pixels), prohibiting them from many interdisciplinary applications. This paper, based on feature point detection method, presents a new approach to improve the georeferencing of AVHRR and GF-1 data using inland water bodies. No need of a prior knowledge of the error source and only based on the image information and the base map, this method is able to automatically search and find the optimal water threshold value (reflectance), conduct feature point detecting and matching, and perform affine transformation. In the case study of the Tibetan Plateau, water body (i.e., lake) with its lower reflectance and relatively stable location and shape, is used as the referencing mask (i.e., base map) for detecting feature point pairs. The accuracy of the geometric correction is found within subpixel level, with average RMSE = 0.76 for AVHRR and RMSE = 0.91 for GF-1. The developed georeferencing method can be potentially applied to other less accessible areas that are difficult to derive ground control points for numerous applications with improved location and geometric accuracies.