Classification of TiungSAT-1 MSEIS Data for Land Cover Mapping with Hyperspectral Analysis Approach

• Main Authors: Lau, Alvin Meng Shin, Hashim, Mazlan
• Other Authors: Arshad, Ahmad Sabirin
• Format: Book Section
• Language: English
• Published: Astronautic Technology (M) Sdn. Bhd. 2003
• Subjects: Q Science (General); GE Environmental Sciences
• Online Access: http://eprints.utm.my/id/eprint/2126/1/Classification-2003-alvin.pdf; http://eprints.utm.my/id/eprint/2126/; https://core.ac.uk/display/11778687

The low to medium spatial resolution satellite data can still be utilized to meet the requirement for a certain level of land cover mapping. However, the land cover classifications of assigning pixel-by-pixel basic to specific land cover classes have been known to be a problematic phenomenon that limits the accuracy of classification. This paper examines the result of utilizing the hyperspectral approach as a recent alternative solution to the above problem to investigate whether or not the sensitivity allowed in the latter can increase the classification accuracy. Using TiungSAT-1 MSEIS data as input, comparative analysis were also performed with classical Maximum Likelihood classification. The results of this study clearly indicate that hyperspectral analysis can improve classification accuracy of multi-spectral data, especially when the mixed pixels are of great concern.