Dynamic threshholds for land surface change detection using image differencing

Change detection using satellite imagery has been increasing the need for effective land management, land environmental changes. Utilizing remote sensing data analysis is high application possibility about management in the field of environmental changes, because relatively wide area in a short-term is to get the visual information. The principal objective of this study was to provide that statistic approaches to determine dynamic thresholds for detection of significant change using image differencing of NDVI (Normalized Difference Vegetation Index). Dynamic threshold look-up-table obtained from statistics (per-pixel standard deviations over 10 years) of 10-year wide-swath satellite data (SPOT/VEGETATION) was used to apply Landsat-based change detection. Two areas is utilized in research using Landsat 7 ETM+ images that have resolution 30×30 m. When achieve changed detection taking advantage of image differencing technique which is one of the changed detection technique, it choose more dynamic critical value taking advantage of middle and low resolution satellite data. As a result, it is effective that takes advantage of NDVI value more than reflection value and method to decide change standard is effective that take advantage of statistics.