The objective of this study is to develop land cover classification algorithm suited for the eastern Asia by using multi-temporal MODIS land reflectance products; Surface Reflectance 8-Day L3 product and Nadir BRDF-Adjusted Reflectance 16-Day L3 product. In this study, land cover maps derived from these two kinds of source data products are generated and compared. Time-domain co-occurrence matr...

This paper proposed a novel method of decision fusion based on weights of evidence model (WOE). The probability rules from classification results from each separate dataset were fused using WOE to produce the posterior probability for each class. The final classification was obtained by maximum probability. The proposed method was evaluated in land cover classification using two examples. The r...

1. Land Evaluation 1.1. Soil Interpretations 1.2. Land Capability and Land Suitability 1.2.1. Development of the Land Capability Classification in USA 1.2.2. The Canada Land Inventory (CLI) A Modified Land Capability Classification 1.2.3. Land Capability Systems in Europe 1.3. Physical and Integral Land Evaluation 1.4. The International Framework for Land Evaluation 1.5. Quantitative Land Evalu...

Per-pixel and sub-pixel are two common classification methods in land cover studies. The characteristics of a landscape, particularly the land cover itself, can affect the accuracies of both methods. The objectives of this study were to: (1) compare the performance of sub-pixel vs. per-pixel classification methods for a broad heterogeneous region; and (2) analyze the impact of land cover hetero...

The areas of the land consolidation projects are generally small, so the remote sensing images used in land-cover classification for the land consolidation are generally high spatial resolution images. The spectral complexity of land consolidation objects results in specific limitation using pixel-based analysis for land cover classification such as farmland, woodland, and water. Considering th...

 SIR-C quad-pol MLC data acquired in 1994 and ALOS PALSAR quad-pol and dual pol SLC data acquired in 2006 and 2007 over several Indian sites have been processed using PolSARpro software for classification of various land features. The land features include ocean, clear water, settlements, agriculture fields, arid lands, grown and young forest, hilly terrain, mangrove forest, etc. Both unsuperv...