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Unsupervised spatio-temporal data mining framework for burned area mapping
Unsupervised spatio-temporal data mining framework for burned area mapping
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机译:烧区映射的无监督时空数据挖掘框架
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摘要
A method reduces processing time required to identify locations burned by fire by receiving a feature value for each pixel in an image, each pixel representing a sub-area of a location. Pixels are then grouped based on similarities of the feature values to form candidate burn events. For each candidate burn event, a probability that the candidate burn event is a true burn event is determined based on at least one further feature value for each pixel in the candidate burn event. Candidate burn events that have a probability below a threshold are removed from further consideration as burn events to produce a set of remaining candidate burn events.
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