Predicting Seberang Perai housing land pattern in 2017
Land use decision making is a complex process involving trade-offs among various land stakeholders due to the resource’s scarcity. Pulau Pinang is the second most densely populated and also the fourth most urbanised state in Malaysia. Urbanisation is Penang state is partially translated as escala...
| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2015
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| Subjects: | |
| Online Access: | http://eprints.usm.my/35129/1/PPIK30.pdf |
| _version_ | 1797009358528184320 |
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| author | Hasni, Rosmiyati Samat, Narimah |
| author_facet | Hasni, Rosmiyati Samat, Narimah |
| author_sort | Hasni, Rosmiyati |
| collection | USM |
| description | Land use decision making is a complex process involving trade-offs among various
land stakeholders due to the resource’s scarcity. Pulau Pinang is the second most densely populated
and also the fourth most urbanised state in Malaysia. Urbanisation is Penang state is partially
translated as escalating housing land demand that poses threats to agricultural land especially around
the peri urban areas. At present, Malaysia is still lacking in scientific tools to assist planners simulate
current and future land use developmental patterns. Existing planning guidelines could not anticipate
future development scenarios. Hence the need for a scientific tool based on dynamic spatial model to
simulated development pattern using scenario approach. This study aims to develop a GIS-based, CA
Markov Model that predicts housing land development in Seberang Perai region of Penang State up to
2017 using 2005 and 2011 land use data. The study first demarcated Seberang Perai based on the
degree of suitability to accommodate all land use classifications. The degree of suitability is ranked
according to development criteria scores, weightings and constraints, with the latter two quantified
using Analytical Hierarchy Process (AHP) technique. CA Markov Model then simulates the dynamic
interactions between cells under specific transition rules to predict land pattern in 2017. The study
provides information on the potential locations and direction/pattern of growth in 2017. The
simulation outcomes show that new or expanded housing lands are located in close proximity with the
predicted growth centres and settlements identified in the Penang Structure Plan 2020 hence endorses
compact urban development pattern. The CA Markov Model can assist relevant authorities in
allocating suitable housing land sites sustainably. |
| first_indexed | 2024-03-06T15:04:32Z |
| format | Conference or Workshop Item |
| id | usm.eprints-35129 |
| institution | Universiti Sains Malaysia |
| language | English |
| last_indexed | 2024-03-06T15:04:32Z |
| publishDate | 2015 |
| record_format | dspace |
| spelling | usm.eprints-351292017-06-14T06:14:30Z http://eprints.usm.my/35129/ Predicting Seberang Perai housing land pattern in 2017 Hasni, Rosmiyati Samat, Narimah H Social Sciences (General) Land use decision making is a complex process involving trade-offs among various land stakeholders due to the resource’s scarcity. Pulau Pinang is the second most densely populated and also the fourth most urbanised state in Malaysia. Urbanisation is Penang state is partially translated as escalating housing land demand that poses threats to agricultural land especially around the peri urban areas. At present, Malaysia is still lacking in scientific tools to assist planners simulate current and future land use developmental patterns. Existing planning guidelines could not anticipate future development scenarios. Hence the need for a scientific tool based on dynamic spatial model to simulated development pattern using scenario approach. This study aims to develop a GIS-based, CA Markov Model that predicts housing land development in Seberang Perai region of Penang State up to 2017 using 2005 and 2011 land use data. The study first demarcated Seberang Perai based on the degree of suitability to accommodate all land use classifications. The degree of suitability is ranked according to development criteria scores, weightings and constraints, with the latter two quantified using Analytical Hierarchy Process (AHP) technique. CA Markov Model then simulates the dynamic interactions between cells under specific transition rules to predict land pattern in 2017. The study provides information on the potential locations and direction/pattern of growth in 2017. The simulation outcomes show that new or expanded housing lands are located in close proximity with the predicted growth centres and settlements identified in the Penang Structure Plan 2020 hence endorses compact urban development pattern. The CA Markov Model can assist relevant authorities in allocating suitable housing land sites sustainably. 2015-08 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.usm.my/35129/1/PPIK30.pdf Hasni, Rosmiyati and Samat, Narimah (2015) Predicting Seberang Perai housing land pattern in 2017. In: International Conference on Development and Socio Spatial Inequalities 2015, 19 – 20 August 2015, Pulau Pinang, Malaysia. |
| spellingShingle | H Social Sciences (General) Hasni, Rosmiyati Samat, Narimah Predicting Seberang Perai housing land pattern in 2017 |
| title | Predicting Seberang Perai housing land pattern in 2017 |
| title_full | Predicting Seberang Perai housing land pattern in 2017 |
| title_fullStr | Predicting Seberang Perai housing land pattern in 2017 |
| title_full_unstemmed | Predicting Seberang Perai housing land pattern in 2017 |
| title_short | Predicting Seberang Perai housing land pattern in 2017 |
| title_sort | predicting seberang perai housing land pattern in 2017 |
| topic | H Social Sciences (General) |
| url | http://eprints.usm.my/35129/1/PPIK30.pdf |
| work_keys_str_mv | AT hasnirosmiyati predictingseberangperaihousinglandpatternin2017 AT samatnarimah predictingseberangperaihousinglandpatternin2017 |