Application of fused quickbird data to identify benthic habitat

Abstract

Image fusion is a very important tool in remote sensing, as many Earth observation satellites provide both high-resolution panchromatic and low-resolution multispectral images (Yun Zhang et al., 2005). In this study, one of the image fusion technique is being used, which named pan-sharpening. Generally, pan-sharpening is the process of fusing a low resolution multispectral image with a high resolution panchromatic image to obtain a high resolution multispectral image (Moeller et al., 2008). Nowadays, many image fusion techniques have been developed to improve the spatial resolution, improve the geometric precision, enhanced the capabilities of features display, improve classification accuracy, enhance the capability of the change detection and replace or repair the defect of image data (Zhao, 2003 ). However, the available algorithms can hardly produce a satisfactory fusion result for QuickBird images. This study introduces the basic concepts and theory of image fusion method for benthic habitat mapping purpose. Indeed, this study discussed 3 types of pansharpening method (local regression transformation, colour space transformation and principal component transformation) by applying images into Idrisi Andes software. Doing mapping and geospatial analysis of benthic environments are particularly important because the subtidal seafloor environment is not readily viewed directly by eye. In other words, the complex relationships that exist among physical, biological, and chemical seafloor components require advanced, integrated analysis techniques to enable others to visualize patterns about benthic processes. In short, research in benthic environments relies heavily on remote sensing to collect effective data meanwhile fusion technique act as a very vital step to enhance the visual quality of data in remote sensing field. According to the study result, all the methods are found to improve resolution and the features present in the rnultispectral image. Local regression transformation is very efficient in presenting the dead coral compound ,;vhile the color space transfonnation are expert in showing the mixture area of sand and dead coral in the water. As for principal component transformation, it is better in performing coral compound and the mixture area of sand and coral in the water.