A superresolution land-cover change detection method using remotely sensed images with different spatial resolutions

Li, Xiaodong, Ling, Feng, Foody, Giles M. and Du, Yun (2016) A superresolution land-cover change detection method using remotely sensed images with different spatial resolutions. IEEE Transactions on Geoscience and Remote Sensing, 54 (7). pp. 3822-3841. ISSN 0196-2892

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The development of remote sensing has enabled the acquisition of information on land-cover change at different spatial scales. However, a trade-off between spatial and temporal resolutions normally exists. Fine-spatial-resolution images have low temporal resolutions, whereas coarse spatial resolution images have high temporal repetition rates. A novel super-resolution change detection method (SRCD)is proposed to detect land-cover changes at both fine spatial and temporal resolutions with the use of a coarse-resolution image and a fine-resolution land-cover map acquired at different times. SRCD is an iterative method that involves endmember estimation, spectral unmixing, land-cover fraction change detection, and super-resolution land-cover mapping. Both the land-cover change/no-change map and from–to change map at fine spatial resolution can be generated by SRCD. In this study, SRCD was applied to synthetic multispectral image, Moderate-Resolution Imaging Spectroradiometer (MODIS) multispectral image and Landsat-8 Operational Land Imager (OLI) multispectral image. The land-cover from–to change maps are found to have the highest overall accuracy (higher than 85%) in all the three experiments. Most of the changed land-cover patches, which were larger than the coarse-resolution pixel, were correctly detected.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/788831
Additional Information: © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Issue date: July 2016
Keywords: Land-cover change detection; super-resolution mapping; the mixed pixel problem.
Schools/Departments: University of Nottingham, UK > Faculty of Social Sciences > School of Geography
Identification Number: https://doi.org/10.1109/TGRS.2016.2528583
Depositing User: Eprints, Support
Date Deposited: 30 Apr 2016 14:50
Last Modified: 04 May 2020 17:50
URI: https://eprints.nottingham.ac.uk/id/eprint/32947

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