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• W2016242051 abstract "Although several studies have reported that rule-based methods are better than other image classification methods, no study has quantified their performance for tropical deciduous vegetation classification. We compared rule-based and maximum likelihood classification (MLC) approaches in classifying tropical deciduous vegetation in Popa Mountain Park, Myanmar. Classification was primarily based on Thematic Mapper (TM) bands of multi-season Landsat images, normalized difference vegetation indices (NDVIs), NDVI differences, mean NDVI and elevation (advanced spaceborne thermal emission and reflection radiometer digital elevation model (Aster DEM)). We used two main approaches for classification, a single-step approach in which all vegetation types were classified in one procedure, and a two-step approach in which forest and non-forest were discriminated first and then forest was classified into additional classes. Each of those approaches was conducted with and without elevation under the rule-based and MLC a..." @default.
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• W2016242051 date "2011-10-14" @default.
• W2016242051 modified "2023-09-24" @default.
• W2016242051 title "Classifying tropical deciduous vegetation: a comparison of multiple approaches in Popa Mountain Park, Myanmar" @default.
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• W2016242051 doi "https://doi.org/10.1080/01431161.2010.531779" @default.
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