New remote sensing image fusion for exploring spatiotemporal evolution of urban land use and land cover

An evaluation of land use and cover change is a vital component any study into climate change, ecological evolution, human civilization’s long-term growth. Remote sensing image data-based (LUCC) research has become an essential frequently utilized approach. Given the scarcity high spatial resolution imagery in urban remote sensing, as well low accuracy efficiency classification, new satellite fusion methodology defined nonshear wave transformation, pulse linked neural network, intensity–hue–saturation theory are suggested. From 2000 to 2020, upgraded convolutional network approach used classify fused pictures perform in-depth investigation spatiotemporal evolution features LUCC Zhengzhou, Henan, China. According findings, extent urbanized Zhengzhou expanded dramatically during last 20 years. The share risen from 9% 22% by 2020. comprehensive dynamic degree single grade display varied different areas counties; index demonstrates more evident regional disparities. findings can expose man-land system’s inherent conflicting interaction mechanism give data promote urban-related research.