Mapping Malaysian urban environment from airborne hyperspectral sensor system in the VIS-NIR (0.4-1.1 μm) spectrum
Airborne hyperspectral remote sensing is a relatively new technology in Malaysia that needs to be tested for its feasibility. Various applications can benefit from the enormous potential offered such as in urban mapping in which rapid development in Malaysia can be accurately monitored. However, the...
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| Format: | Article |
| Language: | English |
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Academic Journals
2011
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| Online Access: | http://psasir.upm.edu.my/id/eprint/23070/ http://psasir.upm.edu.my/id/eprint/23070/1/Mapping%20Malaysian%20Urban%20Environment%20from%20Airborne%20Hyperspectral%20Sensor%20System%20in%20the%20VIS-NIR%20%280.4-1.1%20%CE%BCm%29%20Spectrum.pdf |
| _version_ | 1848844655839412224 |
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| author | Mohd Shafri, Helmi Zulhaidi Md Zeen, Redzuan |
| author_facet | Mohd Shafri, Helmi Zulhaidi Md Zeen, Redzuan |
| author_sort | Mohd Shafri, Helmi Zulhaidi |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Airborne hyperspectral remote sensing is a relatively new technology in Malaysia that needs to be tested for its feasibility. Various applications can benefit from the enormous potential offered such as in urban mapping in which rapid development in Malaysia can be accurately monitored. However, the use of hyperspectral data will also depend critically on the selection of suitable classifiers in order to extract the information. Hence, in this study, image classification was performed using various classifiers such as Parallelepiped, Minimum Distance, Mahalanobis Distance, Maximum Likelihood (ML), Spectral Information Divergence (SID), Spectral Angle Mapper (SAM), Binary Encoding (BE), Neural Network (NN) and Support Vector Machine (SVM). The accuracy of the classifiers was measured based on comparisons with ground truth data. SVM classifier shows the highest overall accuracy (87.98%) followed by ML with 83.17% and BE achieved the lowest accuracy with 39.28%. The findings indicate the feasibility of hyperspectral remote sensing for mapping urban environment in Malaysia with SVM as the most effective classifier for that purpose. |
| first_indexed | 2025-11-15T08:34:23Z |
| format | Article |
| id | upm-23070 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T08:34:23Z |
| publishDate | 2011 |
| publisher | Academic Journals |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-230702015-11-30T08:42:54Z http://psasir.upm.edu.my/id/eprint/23070/ Mapping Malaysian urban environment from airborne hyperspectral sensor system in the VIS-NIR (0.4-1.1 μm) spectrum Mohd Shafri, Helmi Zulhaidi Md Zeen, Redzuan Airborne hyperspectral remote sensing is a relatively new technology in Malaysia that needs to be tested for its feasibility. Various applications can benefit from the enormous potential offered such as in urban mapping in which rapid development in Malaysia can be accurately monitored. However, the use of hyperspectral data will also depend critically on the selection of suitable classifiers in order to extract the information. Hence, in this study, image classification was performed using various classifiers such as Parallelepiped, Minimum Distance, Mahalanobis Distance, Maximum Likelihood (ML), Spectral Information Divergence (SID), Spectral Angle Mapper (SAM), Binary Encoding (BE), Neural Network (NN) and Support Vector Machine (SVM). The accuracy of the classifiers was measured based on comparisons with ground truth data. SVM classifier shows the highest overall accuracy (87.98%) followed by ML with 83.17% and BE achieved the lowest accuracy with 39.28%. The findings indicate the feasibility of hyperspectral remote sensing for mapping urban environment in Malaysia with SVM as the most effective classifier for that purpose. Academic Journals 2011 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/23070/1/Mapping%20Malaysian%20Urban%20Environment%20from%20Airborne%20Hyperspectral%20Sensor%20System%20in%20the%20VIS-NIR%20%280.4-1.1%20%CE%BCm%29%20Spectrum.pdf Mohd Shafri, Helmi Zulhaidi and Md Zeen, Redzuan (2011) Mapping Malaysian urban environment from airborne hyperspectral sensor system in the VIS-NIR (0.4-1.1 μm) spectrum. Research Journal of Environmental Sciences, 5 (6). pp. 587-594. ISSN 1819-3412; ESSN: 2151-8238 http://scialert.net/abstract/?doi=rjes.2011.587.594 10.3923/rjes.2011.587.594 |
| spellingShingle | Mohd Shafri, Helmi Zulhaidi Md Zeen, Redzuan Mapping Malaysian urban environment from airborne hyperspectral sensor system in the VIS-NIR (0.4-1.1 μm) spectrum |
| title | Mapping Malaysian urban environment from airborne hyperspectral sensor system in the VIS-NIR (0.4-1.1 μm) spectrum |
| title_full | Mapping Malaysian urban environment from airborne hyperspectral sensor system in the VIS-NIR (0.4-1.1 μm) spectrum |
| title_fullStr | Mapping Malaysian urban environment from airborne hyperspectral sensor system in the VIS-NIR (0.4-1.1 μm) spectrum |
| title_full_unstemmed | Mapping Malaysian urban environment from airborne hyperspectral sensor system in the VIS-NIR (0.4-1.1 μm) spectrum |
| title_short | Mapping Malaysian urban environment from airborne hyperspectral sensor system in the VIS-NIR (0.4-1.1 μm) spectrum |
| title_sort | mapping malaysian urban environment from airborne hyperspectral sensor system in the vis-nir (0.4-1.1 μm) spectrum |
| url | http://psasir.upm.edu.my/id/eprint/23070/ http://psasir.upm.edu.my/id/eprint/23070/ http://psasir.upm.edu.my/id/eprint/23070/ http://psasir.upm.edu.my/id/eprint/23070/1/Mapping%20Malaysian%20Urban%20Environment%20from%20Airborne%20Hyperspectral%20Sensor%20System%20in%20the%20VIS-NIR%20%280.4-1.1%20%CE%BCm%29%20Spectrum.pdf |