Multisensor Satellite Image Fusion and Networking for All-Weather Environmental Monitoring

Given the advancements of remote sensing technology, large volumes of remotely sensed images with different spatial, temporal, and spectral resolutions are available. To better monitor and understand the changing Earth's environment, fusion of remotely sensed images with different spatial, temporal, and spectral resolutions is critical for distinctive feature retrieval, interpretation, mapping, and decision analysis. A suite of methods have been developed to fuse multisensor satellite images for different purposes in the past few decades. This paper provides a thorough review of contemporary and classic image fusion methods and presents a summary of their phenomenological applications, with challenges and perspectives, for environmental systems analysis. Cross-mission satellite image fusion, networking, and missing value pixel reconstruction for environmental monitoring are described, and their complex integration is illustrated with a case study of Lake Nicaragua that elucidates the state-of-the-art remote sensing technologies for advancing water quality management.