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An improved image fusion approach based on enhanced spatial and temporal the adaptive reflectance fusion model

An improved image fusion approach based on enhanced spatial and temporal the adaptive reflectance fusion model
An improved image fusion approach based on enhanced spatial and temporal the adaptive reflectance fusion model
High spatiotemporal resolution satellite imagery is useful for natural resource management and monitoring for land-use and land-cover change and ecosystem dynamics. However, acquisitions from a single satellite can be limited, due to trade-offs in either spatial or temporal resolution. The spatial and temporal adaptive reflectance fusion model (STARFM) and the enhanced STARFM (ESTARFM) were developed to produce new images with high spatial and high temporal resolution using images from multiple sources. Nonetheless, there were some shortcomings in these models, especially for the procedure of searching spectrally similar neighbor pixels in the models. In order to improve these modelsâ?? capacity and accuracy, we developed a modified version of ESTARFM (mESTARFM) and tested the performance of two approaches (ESTARFM and mESTARFM) in three study areas located in Canada and China at different time intervals. The results show that mESTARFM improved the accuracy of the simulated reflectance at fine resolution to some extent.
image fusion, landsat, modis, reflectance
2072-4292
6346-6360
Fu, Dongjie
d5a38410-7e56-4963-9aae-c2c5199621b2
Chen, Baozhang
1106bc47-8770-4aa5-9edb-f2b2723d69b6
Wang, Juan
4f3b5303-f44c-4915-a5c1-e6d748c71d65
Zhu, Xiaolin
f1878a92-aa4b-4858-9799-15018090bb69
Hilker, Thomas
c7fb75b8-320d-49df-84ba-96c9ee523d40
Fu, Dongjie
d5a38410-7e56-4963-9aae-c2c5199621b2
Chen, Baozhang
1106bc47-8770-4aa5-9edb-f2b2723d69b6
Wang, Juan
4f3b5303-f44c-4915-a5c1-e6d748c71d65
Zhu, Xiaolin
f1878a92-aa4b-4858-9799-15018090bb69
Hilker, Thomas
c7fb75b8-320d-49df-84ba-96c9ee523d40

Fu, Dongjie, Chen, Baozhang, Wang, Juan, Zhu, Xiaolin and Hilker, Thomas (2013) An improved image fusion approach based on enhanced spatial and temporal the adaptive reflectance fusion model. Remote Sensing, 5 (12), 6346-6360. (doi:10.3390/rs5126346).

Record type: Article

Abstract

High spatiotemporal resolution satellite imagery is useful for natural resource management and monitoring for land-use and land-cover change and ecosystem dynamics. However, acquisitions from a single satellite can be limited, due to trade-offs in either spatial or temporal resolution. The spatial and temporal adaptive reflectance fusion model (STARFM) and the enhanced STARFM (ESTARFM) were developed to produce new images with high spatial and high temporal resolution using images from multiple sources. Nonetheless, there were some shortcomings in these models, especially for the procedure of searching spectrally similar neighbor pixels in the models. In order to improve these modelsâ?? capacity and accuracy, we developed a modified version of ESTARFM (mESTARFM) and tested the performance of two approaches (ESTARFM and mESTARFM) in three study areas located in Canada and China at different time intervals. The results show that mESTARFM improved the accuracy of the simulated reflectance at fine resolution to some extent.

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Accepted/In Press date: 11 November 2013
Published date: 26 November 2013
Keywords: image fusion, landsat, modis, reflectance
Organisations: Earth Surface Dynamics

Identifiers

Local EPrints ID: 384659
URI: http://eprints.soton.ac.uk/id/eprint/384659
ISSN: 2072-4292
PURE UUID: 9735de79-d997-4f66-8a60-7f80cdf86095

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Date deposited: 14 Apr 2016 15:58
Last modified: 14 Mar 2024 22:02

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Contributors

Author: Dongjie Fu
Author: Baozhang Chen
Author: Juan Wang
Author: Xiaolin Zhu
Author: Thomas Hilker

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