| Abstrak/Abstract |
ALOS is a unique spaceborne sensor that contains three imaging instruments, AVNIR-2, PRISM, and
PALSAR. AVNIR-2 is a multispectral sensor which contains four multispectral bands with 10 m spatial
resolution and is a promising tool for natural resource mapping and also multitemporal analysis for
understanding the change and the dynamics in earth surface including vegetation cover. However, multitemporal vegetation analyses using digital image processing require the images being analyzed to be free from any additional reflectance caused by atmospherical constituent. Since the amount of additional reflectance by atmospheric constituent is varies with time, multitemporal images suffer from this effect. Identical vegetation located on the same place will produce different spectral signature due to the changes in the atmospheric condition on the corresponding image date of acquisition. Moreover, when directly analysed the multitemporal images on pixel basis such vegetation index, any changes in the images might due to change in the atmospheric condition rather than the change in the objects characteristic. Therefore, in order to optimally utilize remote sensing data for multitemporal analysis, this atmospheric disturbance should be minimized, and if possible is removed from both images. The purpose
of this study is to understand how much atmospheric constituent alter the spectral signature and vegetation index of similar vegetation cover recorded on different date of acquisition. Furthermore, we also evaluate how far the application of radiometric and atmospheric correction may minimize this effect. |
