Multisensor Satellite Image Fusion And Networking For All-Weather Environmental Monitoring
Keywords
Earth observation; environmental systems engineering; feature extraction; image fusion; remote sensing; satellite networking
Abstract
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.
Publication Date
6-1-2018
Publication Title
IEEE Systems Journal
Volume
12
Issue
2
Number of Pages
1341-1357
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/JSYST.2016.2565900
Copyright Status
Unknown
Socpus ID
84973571929 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84973571929
STARS Citation
Chang, Ni Bin; Bai, Kaixu; Imen, Sanaz; Chen, Chi Farn; and Gao, Wei, "Multisensor Satellite Image Fusion And Networking For All-Weather Environmental Monitoring" (2018). Scopus Export 2015-2019. 8650.
https://stars.library.ucf.edu/scopus2015/8650