Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 219-222, 2016
https://doi.org/10.5194/isprs-archives-XLI-B7-219-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
21 Jun 2016
GLOBAL LAND COVER CLASSIFICATION USING MODIS SURFACE REFLECTANCE PROSUCTS
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%.
Conference paper (PDF, 1401 KB)


Citation: Fukue, K. and Shimoda, H.: GLOBAL LAND COVER CLASSIFICATION USING MODIS SURFACE REFLECTANCE PROSUCTS, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 219-222, https://doi.org/10.5194/isprs-archives-XLI-B7-219-2016, 2016.

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