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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Main Authors: H. Shimoda, K. Fukue
Format: Article
Language:English
Published: Copernicus Publications 2012-07-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXIX-B8/525/2012/isprsarchives-XXXIX-B8-525-2012.pdf
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spelling 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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