GLOBAL LAND COVER CLASSIFICATION USING MODIS SURFACE REFLECTANCE PRODUCTS
The objective of this study is to develop high accuracy land cover classification algorithm for Global scale by using multi-temporal MODIS land reflectance products. In this study, time-domain co-occurrence matrix was introduced as a classification feature which provides time-series signature of lan...
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Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
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doaj-1d1cf705897e4a63a2bea31c9a8733dd2020-11-24T21:15:21ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342012-07-01XXXIX-B852552810.5194/isprsarchives-XXXIX-B8-525-2012GLOBAL LAND COVER CLASSIFICATION USING MODIS SURFACE REFLECTANCE PRODUCTSH. Shimoda0K. Fukue1Tokai University Research and Information Center, 2-28-4 Tomigaya, Shibuya-ku, Tokyo 151, JapanTokai University Research and Information Center, 2-28-4 Tomigaya, Shibuya-ku, Tokyo 151, JapanThe objective of this study is to develop high accuracy land cover classification algorithm for Global scale by using multi-temporal MODIS land reflectance products. In this study, time-domain co-occurrence matrix was introduced as a classification feature which provides time-series signature of land covers. Further, the non-parametric minimum distance classifier was introduced for timedomain co-occurrence matrix, which performs multi-dimensional pattern matching for time-domain co-occurrence matrices of a classification target pixel and each classification classes. The global land cover classification experiments have been conducted by applying the proposed classification method using 46 multi-temporal(in one year) SR(Surface Reflectance 8-Day L3) and NBAR(Nadir BRDF-Adjusted Reflectance 16-Day L3) products, respectively. IGBP 17 land cover categories were used in our classification experiments. As the results, SR product and NBAR product showed similar classification accuracy of 99%.http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXIX-B8/525/2012/isprsarchives-XXXIX-B8-525-2012.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
H. Shimoda K. Fukue |
spellingShingle |
H. Shimoda K. Fukue GLOBAL LAND COVER CLASSIFICATION USING MODIS SURFACE REFLECTANCE PRODUCTS The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
author_facet |
H. Shimoda K. Fukue |
author_sort |
H. Shimoda |
title |
GLOBAL LAND COVER CLASSIFICATION USING MODIS SURFACE REFLECTANCE PRODUCTS |
title_short |
GLOBAL LAND COVER CLASSIFICATION USING MODIS SURFACE REFLECTANCE PRODUCTS |
title_full |
GLOBAL LAND COVER CLASSIFICATION USING MODIS SURFACE REFLECTANCE PRODUCTS |
title_fullStr |
GLOBAL LAND COVER CLASSIFICATION USING MODIS SURFACE REFLECTANCE PRODUCTS |
title_full_unstemmed |
GLOBAL LAND COVER CLASSIFICATION USING MODIS SURFACE REFLECTANCE PRODUCTS |
title_sort |
global land cover classification using modis surface reflectance products |
publisher |
Copernicus Publications |
series |
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
issn |
1682-1750 2194-9034 |
publishDate |
2012-07-01 |
description |
The objective of this study is to develop high accuracy land cover classification algorithm for Global scale by using multi-temporal
MODIS land reflectance products. In this study, time-domain co-occurrence matrix was introduced as a classification feature which
provides time-series signature of land covers. Further, the non-parametric minimum distance classifier was introduced for timedomain
co-occurrence matrix, which performs multi-dimensional pattern matching for time-domain co-occurrence matrices of a
classification target pixel and each classification classes. The global land cover classification experiments have been conducted by
applying the proposed classification method using 46 multi-temporal(in one year) SR(Surface Reflectance 8-Day L3) and
NBAR(Nadir BRDF-Adjusted Reflectance 16-Day L3) products, respectively. IGBP 17 land cover categories were used in our
classification experiments. As the results, SR product and NBAR product showed similar classification accuracy of 99%. |
url |
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXIX-B8/525/2012/isprsarchives-XXXIX-B8-525-2012.pdf |
work_keys_str_mv |
AT hshimoda globallandcoverclassificationusingmodissurfacereflectanceproducts AT kfukue globallandcoverclassificationusingmodissurfacereflectanceproducts |
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1716745651191021568 |