Using ALOS PALSAR derived high - resolution DInSAR to detect slow - moving landslides in tropical forest: Cameron Highlands, Malaysia
Landslide is one of the natural hazards that pose maximum threat for human lives and property in mountainous regions. Mitigation and prediction of this phenomenon can be done through the detection of landslide-susceptible areas. Therefore, an appropriate landslide analysis is needed in order to map...
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my.upm.eprints.532102017-10-24T06:13:22Z http://psasir.upm.edu.my/id/eprint/53210/ Using ALOS PALSAR derived high - resolution DInSAR to detect slow - moving landslides in tropical forest: Cameron Highlands, Malaysia Jebur, Mustafa Neamah Pradhan, Biswajeet Tehrany, Mahyat Shafapour Landslide is one of the natural hazards that pose maximum threat for human lives and property in mountainous regions. Mitigation and prediction of this phenomenon can be done through the detection of landslide-susceptible areas. Therefore, an appropriate landslide analysis is needed in order to map and consequently understand the characteristic of this disaster. One of the recent popular remote sensing techniques in deformation analysis is the differential interferometric synthetic aperture radar which is popularly known as DInSAR. Due to the mass vegetation condition in Malaysia, a long-wavelength synthetic aperture radar (∼24 cm) is required in order to be able to penetrate through the forests and reach the bare land. For that reason, ALOS PALSAR HH imagery was used in this study to derive a deformation map of the Gunung Pass area located in the tropical forest of the Cameron Highlands, Malaysia. In this study, the ascending orbit ALOS PALSAR images were acquired in September 2008, January 2009 and December 2009. Subsequently the displacement measurements of the study site (Gunung Pass) were calculated. The accuracy of the result was evaluated through its comparison with ground truth data using the R2 and root mean square error (RMSE) methods. The resulted deformation map showed the landslide locations in the study area from interpretation of the results with 0.84 R2 and 0.151 RMSE. The DInSAR precision was 11.8 cm which proved the efficiency of the proposed method in detecting landslides in a tropical country like Malaysia. It is highly recommended to use the proposed method for any other deformation studies. Taylor & Francis 2016 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/53210/1/Using%20ALOS%20PALSAR%20derived%20high%20-%20resolution%20DInSAR%20to%20detect%20slow%20-%20moving%20landslides%20in%20tropical%20forest%20Cameron%20Highlands%2C%20Malaysia.pdf Jebur, Mustafa Neamah and Pradhan, Biswajeet and Tehrany, Mahyat Shafapour (2016) Using ALOS PALSAR derived high - resolution DInSAR to detect slow - moving landslides in tropical forest: Cameron Highlands, Malaysia. Geomatics, Natural Hazards and Risk, 6 (8). pp. 741-759. ISSN 1947-5705; ESSN: 1947-5713 http://www.tandfonline.com/loi/tgnh20 10.1080/19475705.2013.860407 |
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Landslide is one of the natural hazards that pose maximum threat for human lives and property in mountainous regions. Mitigation and prediction of this phenomenon can be done through the detection of landslide-susceptible areas. Therefore, an appropriate landslide analysis is needed in order to map and consequently understand the characteristic of this disaster. One of the recent popular remote sensing techniques in deformation analysis is the differential interferometric synthetic aperture radar which is popularly known as DInSAR. Due to the mass vegetation condition in Malaysia, a long-wavelength synthetic aperture radar (∼24 cm) is required in order to be able to penetrate through the forests and reach the bare land. For that reason, ALOS PALSAR HH imagery was used in this study to derive a deformation map of the Gunung Pass area located in the tropical forest of the Cameron Highlands, Malaysia. In this study, the ascending orbit ALOS PALSAR images were acquired in September 2008, January 2009 and December 2009. Subsequently the displacement measurements of the study site (Gunung Pass) were calculated. The accuracy of the result was evaluated through its comparison with ground truth data using the R2 and root mean square error (RMSE) methods. The resulted deformation map showed the landslide locations in the study area from interpretation of the results with 0.84 R2 and 0.151 RMSE. The DInSAR precision was 11.8 cm which proved the efficiency of the proposed method in detecting landslides in a tropical country like Malaysia. It is highly recommended to use the proposed method for any other deformation studies. |
format |
Article |
author |
Jebur, Mustafa Neamah Pradhan, Biswajeet Tehrany, Mahyat Shafapour |
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Jebur, Mustafa Neamah Pradhan, Biswajeet Tehrany, Mahyat Shafapour Using ALOS PALSAR derived high - resolution DInSAR to detect slow - moving landslides in tropical forest: Cameron Highlands, Malaysia |
author_facet |
Jebur, Mustafa Neamah Pradhan, Biswajeet Tehrany, Mahyat Shafapour |
author_sort |
Jebur, Mustafa Neamah |
title |
Using ALOS PALSAR derived high - resolution DInSAR to detect slow - moving landslides in tropical forest: Cameron Highlands, Malaysia |
title_short |
Using ALOS PALSAR derived high - resolution DInSAR to detect slow - moving landslides in tropical forest: Cameron Highlands, Malaysia |
title_full |
Using ALOS PALSAR derived high - resolution DInSAR to detect slow - moving landslides in tropical forest: Cameron Highlands, Malaysia |
title_fullStr |
Using ALOS PALSAR derived high - resolution DInSAR to detect slow - moving landslides in tropical forest: Cameron Highlands, Malaysia |
title_full_unstemmed |
Using ALOS PALSAR derived high - resolution DInSAR to detect slow - moving landslides in tropical forest: Cameron Highlands, Malaysia |
title_sort |
using alos palsar derived high - resolution dinsar to detect slow - moving landslides in tropical forest: cameron highlands, malaysia |
publisher |
Taylor & Francis |
publishDate |
2016 |
url |
http://psasir.upm.edu.my/id/eprint/53210/1/Using%20ALOS%20PALSAR%20derived%20high%20-%20resolution%20DInSAR%20to%20detect%20slow%20-%20moving%20landslides%20in%20tropical%20forest%20Cameron%20Highlands%2C%20Malaysia.pdf http://psasir.upm.edu.my/id/eprint/53210/ http://www.tandfonline.com/loi/tgnh20 |
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