Remote sensing image information mining applied to burnt forest detection in the Brazilian Amazon
نویسندگان
چکیده
Fire processes contribute to carbon dioxide emissions, main gas responsible for the Greenhouse Effect. Considering the importance of fire processes management for the detection of burnt areas in the Brazilian Amazon, the Linear Spectral Mixture Model is one of the main methods available. Nonetheless, some manual processes are required before its application, such as identifying adequate images in databases. In this manner, we have developed an approach for Remote Sensing Image Information Mining (ReSIIM), which was tested for burnt areas studies. ReSIIM stores information about well-known targets found in Remote Sensing imagery, such as cloud, cloud shadow, clear land, water, vegetation and bare soil.
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Contextual clustering for image labeling: an application to degraded forest assessment in Landsat TM images of the Brazilian Amazon
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