Change detection assessment in a tropical forest using multispectral and hyperspectral images

Land cover changes over time due to natural and manmade phenomena. This paper evaluates different methods for change detection using multispectral and hyperspectral images. Change detection methods such as Euclidean distance and differentiation are applied to Landsat 7 and 8 multispectral images to detect changes over a tropical dry forest area. A change detection method that uses Tasseled Cap Transformation (TCT) and thresholding, is applied to both multispectral and hyperspectral images. Results show more changes over large periods of time such as 10 years. TCT detects changes in both multispectral and hyperspectral images. The level and detail of changes that can be obtained depends on the spatial, spectral and temporal resolution of the images.