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A Superresolution Land-Cover Change Detection Method Using Remotely Sensed Images With Different Spatial Resolutions.
- Source :
- IEEE Transactions on Geoscience & Remote Sensing; Jul2016, Vol. 54 Issue 7, p3822-3841, 20p
- Publication Year :
- 2016
-
Abstract
- The development of remote sensing has enabled the acquisition of information on land-cover change at different spatial scales. However, a tradeoff 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 superresolution 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 superresolution 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 paper, SRCD was applied to a synthetic multispectral image, a Moderate-Resolution Imaging Spectroradiometer multispectral image, and a Landsat-8 Operational Land Imager multispectral image. The land-cover from-to change maps are found to have the highest overall accuracy (higher than 85%) in all of the three experiments. Most of the changed land-cover patches, which were larger than the coarse-resolution pixel, were correctly detected. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01962892
- Volume :
- 54
- Issue :
- 7
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Geoscience & Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- 118691543
- Full Text :
- https://doi.org/10.1109/TGRS.2016.2528583