GIS based probabilistic method in sinkhole susceptibility hazard zones
In this era of globalization, natural phenomena often invade the human population. Natural phenomena such as sinkholes often occur in countries whose topology lies in active limestone areas. Malaysia is one of the countries with active limestone areas, especially in the Klang Valley and its surround...
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| Main Authors: | , , , |
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| Format: | EJournal Article |
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Institute of Advanced Engineering and Science,
2019-12-01.
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| LEADER | 02810 am a22003253u 4500 | ||
|---|---|---|---|
| 001 | ijeecs20244_13190 | ||
| 042 | |a dc | ||
| 100 | 1 | 0 | |a Mohd Rosdi, Mohd Asri Hakim |e author |
| 100 | 1 | 0 | |e contributor |
| 700 | 1 | 0 | |a Othman, Ainon Nisa |e author |
| 700 | 1 | 0 | |a Latif, Zulkiflee Abd |e author |
| 700 | 1 | 0 | |a Yusoff, Zaharah Mohd |e author |
| 245 | 0 | 0 | |a GIS based probabilistic method in sinkhole susceptibility hazard zones |
| 260 | |b Institute of Advanced Engineering and Science, |c 2019-12-01. | ||
| 500 | |a https://ijeecs.iaescore.com/index.php/IJEECS/article/view/20244 | ||
| 520 | |a In this era of globalization, natural phenomena often invade the human population. Natural phenomena such as sinkholes often occur in countries whose topology lies in active limestone areas. Malaysia is one of the countries with active limestone areas, especially in the Klang Valley and its surrounding areas. Since 1968, the increase in sinkhole cases in Malaysia has been reported frequently. This has caused many building infrastructures to be destroyed, loss of life and destruction of property. So, one of the steps to overcome this problem is to do an in-depth study of the sinkhole. Therefore, Sinkhole Hazard Model (SHM) has been created with a combination of GIS integration by using probability techniques. There are five criteria suitable for Malaysian topography namely Lithology (LT), Soil Types (ST), Landuse (LU), Groundwater Level Decline (GLD) and Proximity to Groundwater Wells (PGW). Based on probability calculations, GLD and LU have shown a high impact on sinkhole formation. A hazard zonation map has been produced where it has been classified into five parts namely none, low, medium, high and very high. The results were validated with previous inventory data comprising 33 data. Based on the results obtained, 36.37% and 39.39% of the sinkhole formation has fallen into high and very high areas respectively. Based on these final results, the integration between GIS and probability techniques is useful in natural phenomena such as sinkhole formation. | ||
| 540 | |a Copyright (c) 2019 Institute of Advanced Engineering and Science | ||
| 540 | |a http://creativecommons.org/licenses/by-nc/4.0 | ||
| 546 | |a eng | ||
| 690 | |||
| 690 | |a GIS; MCDM; Sinkholes; hazard; probabilistic method | ||
| 655 | 7 | |a info:eu-repo/semantics/article |2 local | |
| 655 | 7 | |a info:eu-repo/semantics/publishedVersion |2 local | |
| 655 | 7 | |2 local | |
| 786 | 0 | |n Indonesian Journal of Electrical Engineering and Computer Science; Vol 16, No 3: December 2019; 1539-1546 | |
| 786 | 0 | |n 2502-4760 | |
| 786 | 0 | |n 2502-4752 | |
| 786 | 0 | |n 10.11591/ijeecs.v16.i3 | |
| 787 | 0 | |n https://ijeecs.iaescore.com/index.php/IJEECS/article/view/20244/13190 | |
| 856 | 4 | 1 | |u https://ijeecs.iaescore.com/index.php/IJEECS/article/view/20244/13190 |z Get fulltext |