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A review of assessment methods for cellular automata models of land-use change and urban growth., и . Int. J. Geogr. Inf. Sci., 34 (5): 866-898 (2020)The effects of factor generalization scales on the reproduction of dynamic urban growth., , , , , , , и . Geo spatial Inf. Sci., 25 (3): 457-475 (2022)An Anchor-Free Network With Density Map and Attention Mechanism for Multiscale Object Detection in Aerial Images., , , , , и . IEEE Geosci. Remote. Sens. Lett., (2022)Automatic selection of permanent scatterers-based GCPs for refinement and reflattening in InSAR DEM generation., , , , , и . Int. J. Digit. Earth, 15 (1): 954-974 (декабря 2022)Spatial Patterns of Land Surface Temperature and Their Influencing Factors: A Case Study in Suzhou, China., , , , , и . Remote Sensing, 11 (2): 182 (2019)Calibration of cellular automata models using differential evolution to simulate present and future land use., и . Trans. GIS, 22 (2): 582-601 (2018)Elastic and Inelastic Ground Deformation in Shanghai Lingang Area Revealed by Sentinel-1, Leveling, and Groundwater Level Data., , , , , , , и . Remote. Sens., 14 (11): 2693 (2022)Large-Scale Surface Deformation Monitoring Using SBAS-InSAR and Intelligent Prediction in Typical Cities of Yangtze River Delta., , , , , , , , и . Remote. Sens., 15 (20): 4942 (октября 2023)To move or stay? A cellular automata model to predict urban growth in coastal regions amidst rising sea levels., , , и . Int. J. Digit. Earth, 14 (9): 1213-1235 (2021)Modeling dynamic urban land-use change with geographical cellular automata and generalized pattern search-optimized rules.. Int. J. Geogr. Inf. Sci., 31 (6): 1198-1219 (2017)