Pan Sharpening Fusion for Spectral Change Vector

Change detection is one of the most important applications in the remote sensing society. In change detection, pan sharpening fusion plays an important role to create a high-resolution dataset. A pansharpening method for enhancing satellite imagery is used as building a relatively high accuracy and low cost approach for image-based analyses. In this work, Pan sharpening Gram Schmidt technique is applied for enhancing certain features which are not visible in either of the single data alone. To perform the fusion, a low spatial resolution multi-spectral image of MODIS is fused with higher resolution single band image of AWiFS of same date using different method of pan-sharpening and evaluated that Gram Schmidt method is best method. Both images are fused for same geographical area and have almost same time acquisition of lower and middle Himalaya, Himachal Pradesh, India. Then improved change vector analysis is used as change detection technique. This method performed in two stages: in first stage double- window flexible pace search (DFPS), which aims at determining the threshold of change magnitude, and in second stage, the direction cosines of change vectors for determining.