Harmonic analysis of time-series NOAA/AVHRR images for hotspot detection and land features classification

In this paper, harmonic analysis of 10-year time series (1995-2005) NOAA/AVHRR yearly composite images is performed to develop an innovative technique for hotspot detection and land-features classification based on temporal changes in the NDVI and various AVHRR band values. NOAA/AVHRR images are used due to wide coverage, high frequency and free acquisition offered by NOAA/AVHRR sensors. Proposed algorithm consists of three steps: (1) preprocessing of NOAA/AVHRR images to correct geometric distortions and calibrate the data radiometrically (2) detection of cloud and water pixels in the preprocessed image and application of harmonic analysis on 10-years time series AVHRR images to produce phase and amplitude images, and (3) application of image processing techniques on the amplitude images of different bands to detect hotspots and classify the region of interest. The obtained results indicate that the proposed method can classify the region of interest successfully with through out greater than 91% classification accuracy.