Reconstruction of 30 m Land Cover in the Qilian Mountains from 1980 to 1990 Based on Super-Resolution Generative Adversarial Networks  
[PERSON]  
1 State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China; [EMAIL_ADDRESS] (C.W. ); [EMAIL_ADDRESS] (K.A. ); [EMAIL_ADDRESS] (B.D. ); [EMAIL_ADDRESS] (L.H. ); [EMAIL_ADDRESS] (H.C.); [EMAIL_ADDRESS] (Y.Q. ); [EMAIL_ADDRESS] (J.W. ); [EMAIL_ADDRESS] (A.Y. ); [EMAIL_ADDRESS] (A.Y. ); [EMAIL_ADDRESS] (Q.L)  
[PERSON]  
1 State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China; [EMAIL_ADDRESS] (C.W. ); [EMAIL_ADDRESS] (K.A. ); [EMAIL_ADDRESS] (B.D. ); [EMAIL_ADDRESS] (L.H. ); [EMAIL_ADDRESS] (H.C.); [EMAIL_ADDRESS] (Y.Q. ); [EMAIL_ADDRESS] (J.W. ); [EMAIL_ADDRESS] (A.Y. ); [EMAIL_ADDRESS] (A.Y. ); [EMAIL_ADDRESS] (A.Y. ); [EMAIL_ADDRESS] (S.W. ); [EMAIL_ADDRESS] (Q.L)  
Kai Ao  
1 State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100010, China; [EMAIL_ADDRESS] (C.W. ); [EMAIL_ADDRESS] (K.A. ); [EMAIL_ADDRESS] (B.D. ); [EMAIL_ADDRESS] (L.H. ); [EMAIL_ADDRESS] (H.C.); [EMAIL_ADDRESS] (C.W. ); [EMAIL_ADDRESS] (J.W. ); [EMAIL_ADDRESS] (  
global land cover datasets have been publicly released [3; 4; 5; 6; 7; 8; 9]. These datasets exhibit strong consistency on a global scale but show significant discrepancies at regional scales. The main issues include the following: (1) the relatively low resolution of most land cover datasets (500 m or lower), with accuracies typically below 75% [4; 5]; among the published datasets, GlobeLand30 [6] and FROM-GLC30 [7] have a spatial resolution of 30 m, with overall accuracies of 80% and 72%, respectively; (2) the classification accuracy of these datasets at regional scales is much lower than their claimed accuracy, particularly in heterogeneous regions, making them insufficient for modeling needs; (3) most datasets cover periods post-2000, lacking the long time series needed for analyzing long-term climate, environmental, and ecological changes. Recently, satellite constellations and sensors with large swaths, such as Sentinel-2, FORMOSAT-2, Chinese HJ-1, and GF-1, were launched, enabling global scans every few days at high resolution. Consequently, time series of remote sensing images have become increasingly available. Regional land cover maps with a spatial resolution of 30 m have been generated [3; 6; 7; 8; 9; 10; 11; 12; 13] through time series analysis of satellite images. Furthermore, the authors of [14] developed a land cover mapping method (LCMM) using multi-classifiers and multisource remotely sensed imagery, employing HJ-1/CCD and Landsat time series images to produce finer land cover maps at Heihe River Basin (HRB) for the years 1986, 1990, 1995, 2000, 2005, and 2011-2015 [14; 15]. The earliest 30 m land cover products can be traced back to 1985, but they are limited to a few discontinuous datasets with poor accuracy before 2000. Due to the large volume of data and inconsistent quality, obtaining annual regional land cover products before the 1990s is highly challenging. Additionally, although Landsat time series imagery dates back to 1972, the availability of high-quality images with low cloud cover in China is limited, and the majority of data availability started from 1986. Therefore, long time series of historical land cover datasets before 1986 have been in great demand but still unavailable, even at the regional scale. To make long time series of land cover datasets dating back to 1980 and even earlier that support the analysis of long-term climate, environmental, and ecological changes, the advanced very high resolution radiometer (AVHRR) sensor aboard NOAA satellites is the only instrument capable of providing continuous remote sensing data with the longest temporal coverage since the early 1980s.