A Superresolution Land-Cover Change Detection Method Using Remotely Sensed Images With Different Spatial Resolutions

Li, Xiaodong; Ling, Feng; Foody, Giles M.; Du, Yun

Abstract

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.

Citation

Li, X., Ling, F., Foody, G. M., & Du, Y. (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), 3822-3841. https://doi.org/10.1109/TGRS.2016.2528583

• Journal Article Type: Article
• Acceptance Date: Jan 11, 2016
• Online Publication Date: Mar 4, 2016
• Publication Date: 2016-07
• Deposit Date: Apr 30, 2016
• Publicly Available Date: Apr 30, 2016
• Journal: IEEE Transactions on Geoscience and Remote Sensing
• Print ISSN: 0196-2892
• Electronic ISSN: 0196-2892
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 54
• Issue: 7
• Pages: 3822-3841
• DOI: https://doi.org/10.1109/TGRS.2016.2528583
• Keywords: Land-cover change detection; super-resolution mapping; the mixed pixel problem.
• Public URL: https://nottingham-repository.worktribe.com/output/788831
• Publisher URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7426366
• 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