Abstract
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 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%.
Highlights
Land cover maps of global or continental scale are basic information for many kinds of applications, i.e. global change research, modeling, resource management, etc
NDVI data lose most of information contents which were originally included in many channels
Because the cosine distance classifier has always produced several percent higher mean producer's classification accuracy than that of the Euclidean distance classifier regardless of the time-separation delta-t, only the results when the cosine distance is used is shown in the following
Summary
Land cover maps of global or continental scale are basic information for many kinds of applications, i.e. global change research, modeling, resource management, etc. Several kinds of global land cover maps has been generated, such as IGBP DISCover Global Land Cover, UMD Global Land Cover, and MODIS Land Cover, etc., and these products have been distributed widely Accuracies of these global land maps were not sufficiently high. Most of these land cover maps were generated mainly using NDVI and its seasonal changes. There are two kinds product of Surface Reflectance 8-Day L3 product and Nadir BRDF-Adjusted Reflectance 16-Day L3 product Both are composed of 7 spectral bands (620-670nm, 841-876nm, 459-479nm, 545-565nm, 1230-1250nm, 1628-1652nm, and 2105-2155nm) with 500m ground resolution. The former is the atmospheric corrected surface reflectance, while the latter corrects the BRDF effects in addition to the atmospheric correction. These products are called SR product and NBAR product, respectively
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