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Downscaling MODIS images with area-to-point regression kriging

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Downscaling MODIS images with area-to-point regression kriging. / Wang, Qunming; Shi, Wenzhong; Atkinson, Peter Michael; Zhao, Yuanling.

In: Remote Sensing of Environment, Vol. 166, 01.09.2015, p. 191-204.

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Wang, Q, Shi, W, Atkinson, PM & Zhao, Y 2015, 'Downscaling MODIS images with area-to-point regression kriging', Remote Sensing of Environment, vol. 166, pp. 191-204. https://doi.org/10.1016/j.rse.2015.06.003

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Wang, Qunming ; Shi, Wenzhong ; Atkinson, Peter Michael ; Zhao, Yuanling. / Downscaling MODIS images with area-to-point regression kriging. In: Remote Sensing of Environment. 2015 ; Vol. 166. pp. 191-204.

Bibtex

@article{1abe7fdc1817499dbc61738b357465ee,
title = "Downscaling MODIS images with area-to-point regression kriging",
abstract = "The first seven bands of the Moderate Resolution Imaging Spectroradiometer (MODIS) data have been used widely for global land-cover/land-use (LCLU) monitoring (e.g., deforestation over the Amazon basin). However, the spatial resolution of MODIS bands 3–7 (i.e., 500 m) is coarser than that of bands 1 and 2 (i.e., 250 m), and may be too coarse for a large number of applications. In this paper, a new geostatistical approach based on area-to-point regression kriging (ATPRK) is proposed for downscaling coarse spatial resolution bands 3–7 such as to produce a complete set of MODIS images at 250 m. ATPRK takes advantages of the fine spatial resolution information in bands 1 and 2 by regression modeling, and uses area-to-point kriging to downscale the coarse residuals from the regression. ATPRK was compared to four existing methods, including the principal component analysis, wavelets, high-pass filter and kriging with external drift (KED) methods for downscaling in two experiments on MODIS data from the Brazilian Amazon. Both visual and quantitative evaluations (in terms of the root mean square error, correlation coefficient, relative global-dimensional synthesis error, universal image quality index, spectral angle mapper and spectral information divergence) showed that ATPRK produced sharpened images with the greatest quality. In addition, ATPRK perfectly preserved the spectral properties of the original coarse data and was faster than KED. The results reveal the great potential of ATPRK applied to MODIS data for a wide variety of applications, including global monitoring of deforestation. The ATPRK proposed in this paper is an entirely new image fusion approach based on a new conceptualization.",
keywords = "Downscaling, Geostatistics, Area-to-point regression kriging (ATPRK), Moderate Resolution Imaging Spectroradiometer (MODIS)",
author = "Qunming Wang and Wenzhong Shi and Atkinson, {Peter Michael} and Yuanling Zhao",
year = "2015",
month = sep,
day = "1",
doi = "10.1016/j.rse.2015.06.003",
language = "English",
volume = "166",
pages = "191--204",
journal = "Remote Sensing of Environment",
issn = "0034-4257",
publisher = "Elsevier Inc.",

}

RIS

TY - JOUR

T1 - Downscaling MODIS images with area-to-point regression kriging

AU - Wang, Qunming

AU - Shi, Wenzhong

AU - Atkinson, Peter Michael

AU - Zhao, Yuanling

PY - 2015/9/1

Y1 - 2015/9/1

N2 - The first seven bands of the Moderate Resolution Imaging Spectroradiometer (MODIS) data have been used widely for global land-cover/land-use (LCLU) monitoring (e.g., deforestation over the Amazon basin). However, the spatial resolution of MODIS bands 3–7 (i.e., 500 m) is coarser than that of bands 1 and 2 (i.e., 250 m), and may be too coarse for a large number of applications. In this paper, a new geostatistical approach based on area-to-point regression kriging (ATPRK) is proposed for downscaling coarse spatial resolution bands 3–7 such as to produce a complete set of MODIS images at 250 m. ATPRK takes advantages of the fine spatial resolution information in bands 1 and 2 by regression modeling, and uses area-to-point kriging to downscale the coarse residuals from the regression. ATPRK was compared to four existing methods, including the principal component analysis, wavelets, high-pass filter and kriging with external drift (KED) methods for downscaling in two experiments on MODIS data from the Brazilian Amazon. Both visual and quantitative evaluations (in terms of the root mean square error, correlation coefficient, relative global-dimensional synthesis error, universal image quality index, spectral angle mapper and spectral information divergence) showed that ATPRK produced sharpened images with the greatest quality. In addition, ATPRK perfectly preserved the spectral properties of the original coarse data and was faster than KED. The results reveal the great potential of ATPRK applied to MODIS data for a wide variety of applications, including global monitoring of deforestation. The ATPRK proposed in this paper is an entirely new image fusion approach based on a new conceptualization.

AB - The first seven bands of the Moderate Resolution Imaging Spectroradiometer (MODIS) data have been used widely for global land-cover/land-use (LCLU) monitoring (e.g., deforestation over the Amazon basin). However, the spatial resolution of MODIS bands 3–7 (i.e., 500 m) is coarser than that of bands 1 and 2 (i.e., 250 m), and may be too coarse for a large number of applications. In this paper, a new geostatistical approach based on area-to-point regression kriging (ATPRK) is proposed for downscaling coarse spatial resolution bands 3–7 such as to produce a complete set of MODIS images at 250 m. ATPRK takes advantages of the fine spatial resolution information in bands 1 and 2 by regression modeling, and uses area-to-point kriging to downscale the coarse residuals from the regression. ATPRK was compared to four existing methods, including the principal component analysis, wavelets, high-pass filter and kriging with external drift (KED) methods for downscaling in two experiments on MODIS data from the Brazilian Amazon. Both visual and quantitative evaluations (in terms of the root mean square error, correlation coefficient, relative global-dimensional synthesis error, universal image quality index, spectral angle mapper and spectral information divergence) showed that ATPRK produced sharpened images with the greatest quality. In addition, ATPRK perfectly preserved the spectral properties of the original coarse data and was faster than KED. The results reveal the great potential of ATPRK applied to MODIS data for a wide variety of applications, including global monitoring of deforestation. The ATPRK proposed in this paper is an entirely new image fusion approach based on a new conceptualization.

KW - Downscaling

KW - Geostatistics

KW - Area-to-point regression kriging (ATPRK)

KW - Moderate Resolution Imaging Spectroradiometer (MODIS)

U2 - 10.1016/j.rse.2015.06.003

DO - 10.1016/j.rse.2015.06.003

M3 - Journal article

VL - 166

SP - 191

EP - 204

JO - Remote Sensing of Environment

JF - Remote Sensing of Environment

SN - 0034-4257

ER -