The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLI-B7
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 219–222, 2016
https://doi.org/10.5194/isprs-archives-XLI-B7-219-2016
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 219–222, 2016
https://doi.org/10.5194/isprs-archives-XLI-B7-219-2016

  21 Jun 2016

21 Jun 2016

GLOBAL LAND COVER CLASSIFICATION USING MODIS SURFACE REFLECTANCE PROSUCTS

Kiyonari Fukue and Haruhisa Shimoda Kiyonari Fukue and Haruhisa Shimoda
  • Tokai University Research and Information Center, 2-28-4 Tomigaya, Shibuya-ku, Tokyo 151, Japan

Keywords: Global, Land Cover, Classification Algorithm, Multi-temporal, Multi-spectral, Co-occurrence Matrix, Non-Parametric Classifier

Abstract. 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) and NBAR(Nadir BRDF-Adjusted Reflectance) products, respectively. IGBP 17 land cover categories were used in our classification experiments. As the results, SR and NBAR products showed similar classification accuracy of 99%.