A fuzzy logic approach to detect hotspots with NOAA/AVHRR image using multi-channel information fusion technique

This paper proposes a novel approach to detect hotspots using NOAA advanced very high resolution radiometer (AVHRR) for the Jharia, Jharkhand (India) region. Jharia coalfield in Jharkhand is the richest coal bearing area in India that contains a large number of mine fires which have been burning for several decades. In this paper, a fuzzy based methodology has been applied for the determination of hotspots to Jharia AVHRR images based on a theoretical model that establishes relationship among AVHRR channel 4, channel 5 and different vegetation indices. The algorithm consists of four stages: data preprocessing, multi-channel information fusion, hotspot detection using fuzzy logic approach and validation of result. The most commonly used existing algorithms like contextual algorithms, multi-thresholding, entropy based thresholding, and genetic algorithms have limitation that they need some mathematical model for training in order to get the required result. The employed fuzzy logic approach overcomes this requirement and in addition, it is flexible, tolerant of imprecise data and is based on natural language. The results were compared with the results obtained by ground survey and a good agreement has been obtained between observed and predicted hotspots.

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