Classification of TiungSAT-1 MSEIS Data for Land Cover Mapping with Hyperspectral Analysis Approach
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 li...
Saved in:
| Main Authors: | , |
|---|---|
| Other Authors: | |
| Format: | Book Section |
| Language: | English |
| Published: |
Astronautic Technology (M) Sdn. Bhd.
2003
|
| Subjects: | |
| 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 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Universiti Teknologi Malaysia |
| Language: | English |
| Summary: | 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. |
|---|