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Decision tree (DT) induction has been widely used in different pattern classification. However, most traditional DTs have the disadvantage that they consider only non-spatial attributes (ie, spectral ...
Image classification is a compulsory step in any remote sensing research. Classification uses the spectral information represented by the digital numbers in one or more spectral bands and attempts to ...
It is important to explore the ability of Bidirectional Reflectance Distribution Function (BRDF) to improve classification accuracy using MODerate Resolution Imaging Spectroradiometer (MODIS) BRDF and...
A lot of wetlands exist in the Yellow River Delta area, Shandong China and exhibit significance for the delta ecological environmental evolution and animal habitat protection. It is important for wetl...
This paper examines the applicability of binary decision tree (DT) classifier and ASTER data for the monitoring of wetland vegetation at plant family level (eight dominant plant families in the study ...
According to the deficiency of the process in Land Use Status quo Maps updating, this paper puts forward to a way to update The Land Use Status quo Maps based on decision tree, utilizing The Land Use ...
Accurate, current, and cost-effective fire fuel data are required by management and fire science communities for use in reducing wildland fire hazards over large areas. In this paper we present resul...
Snow cover area is a very critical parameter for hydrologic cycle of the Earth. Furthermore, it will be a key factor for the effect of the climate change. An unbelievable situation in mapping snow cov...
Traditional land classification techniques for large areas that use LANDSAT TM imagery are typically limited to the fixed spatial resolution of the sensors. For modeling habitat characteristics is oft...
Extraction of urban land is one of the necessary process in the change detection of urban growth. This Paper build a unified conceptual model to make the extraction more effectively and accurately bas...

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