4 papers
Global-Scale Self-Supervised Spatiotemporal Learning for NDVI Time-Series Reconstruction
Ang Li, Menghui Jiang, Xiaobin Guan +2
Accurate and efficient reconstruction of cloud-contaminated and noise-corrupted NDVI time series remains a challenge in remote sensing. Deep learning provides a promising solution…
A Mechanism-Coupled Split Window Network for Medium- to High-Resolution Land Surface Temperature Retrieval
Tian Xie, Menghui Jiang, Chao Zeng +4
Land surface temperature (LST) is a fundamental physical variable in land-atmosphere interactions, surface energy budgets, and climate processes. LST derived from medium- to high-r…
30-meter Land Surface Temperature from Landsat via Progressive Self-Training Downscaling
Huanfeng Shen, Chan Li, Menghui Jiang +3
Land surface temperature (LST) is a critical parameter for characterizing surface energy balance and hydrothermal processes. While Landsat provides invaluable LST observations at m…
A Mechanism-Learning Deeply Coupled Model for Remote Sensing Retrieval of Global Land Surface Temperature
Tian Xie, Menghui Jiang, Huanfeng Shen +5
Land surface temperature (LST) retrieval from remote sensing data is pivotal for analyzing climate processes and surface energy budgets. However, LST retrieval is an ill-posed inve…