Skip to main content

Advertisement

SpringerLink
Log in

Predicting the Effects of Urban Development on Land Transition and Spatial Patterns of Land Use in Western Peninsular Malaysia

  • Published:
Applied Spatial Analysis and Policy Aims and scope Submit manuscript

Abstract

Analyzing the effects of urban development on dynamic and spatial patterns of land use is vital to establish more efficient land management policies. However, in Malaysia, such effects are usually explained without quantitative metrics. This research quantified the future impact of urban expansion on the dynamic of land use by developing the area-independent dynamic metric. The metric was calculated based on summarizing the cross tabulation matrices of change in an urbanizing area at west coast of Peninsular Malaysia. Another two land use measures involving vulnerability to gain and vulnerability to loss were used to evaluate tendency of land classes to transition. The effects of urban development on spatial patterns of land use were quantified using two landscape metrics involving the Edge Density (ED) and Area-Weighted Mean Patch Fractal Dimension (AWMPFD). Analyses were carried out on a set of spatial land use data including observed 1997, 2002, and 2008, as well as a simulated near future land change for the year 2020 under a spatio-temporal land use model. Results showed that urban development practices would influence the dynamic of land transition in the near future. Urban growth would experience a fast-growing dynamic and high vulnerability to gain than loss while the dynamic and vulnerability of forest/wetland covers would decrease in terms of loss. Moreover, agriculture practices tend to be hindered by further urban development in the coming years. Another important finding was that urban development process would influence the spatial patterns of land use in the near future.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Abdullah, S. A., & Nakagoshi, N. (2006). Changes in landscape spatial pattern in the highly developing state of Selangor, peninsular Malaysia. Landscape and Urban Planning, 77, 263–275.

    Article  Google Scholar 

  • Abdullah, S. A., & Nakagoshi, N. (2007). Forest fragmentation and its correlation to human land use change in the state of Selangor, peninsular Malaysia. Forest Ecology and Management, 241, 39–48.

    Article  Google Scholar 

  • Abdullah, S. A., & Nakagoshi, N. (2008a). Changes in agricultural landscape pattern and its spatial relationship with forestland in the State of Selangor, peninsular Malaysia. Landscape and Urban Planning, 87, 147–155.

    Article  Google Scholar 

  • Abdullah, S. A., & Nakagoshi, N. (2008b). Landscape ecological approach in oil palm land use planning and management for forest conservation in Malaysia. In S.-K. Hong, N. Nakagoshi, B. J. Fu, & Y. Morimoto (Eds.), Landscape ecological applications in man-influenced areas: Linking man and nature systems (pp. 179–191). Dordrecht: Springer Science + Business Media B.V.

    Google Scholar 

  • Adhikari, S., & Southworth, J. (2012). Simulating forest cover changes of Bannerghatta national park based on a CA-Markov model: a remote sensing approach. Remote Sensing, 4(10), 3215–3243.

    Article  Google Scholar 

  • Ahmad, F., Mohd, I., Maidin, S. L., Zainol, R., & Noor, N. M. (2013). Malaysian development plan system: issues and problems, one decade after its reform (2001–2011). Planning Malaysia, XI, 1–20.

  • Ahmed, B., Kamruzzaman, M., Zhu, X., Rahman, M. S., & Choi, K. (2013). Simulating land cover changes and their impacts on land surface temperature in Dhaka, Bangladesh. Remote Sensing, 5(11), 5969–5998.

    Article  Google Scholar 

  • Alo, C. A., & Pontius, R. G. (2008). Identifying systematic land-cover transitions using remote sensing and GIS: the fate of forests inside and outside protected areas of Southwestern Ghana. Environment and Planning B: Planning and Design, 35(2), 280–295.

    Article  Google Scholar 

  • Araya, Y. H., & Cabral, P. (2010). Analysis and modeling of urban land cover change in Setúbal and Sesimbra, Portugal. Remote Sensing, 2(6), 1549–1563.

    Article  Google Scholar 

  • Boon-Thong, L. (2005). Urban Development in Malaysia: the Case for a More Holistic and Strategic Approach to Urbanisation. Paper presented at the Southeast Asian-German Summer School, University of Cologne, Koln, Germany.

  • Braimoh, A. K. (2006). Random and systematic land-cover transitions in northern Ghana. Agriculture, Ecosystems & Environment, 113(1), 254–263.

    Article  Google Scholar 

  • Carmona, A., & Nahuelhual, L. (2012). Combining land transitions and trajectories in assessing forest cover change. Applied Geography, 32(2), 904–915.

    Article  Google Scholar 

  • Chen, C.-F., Son, N.-T., Chang, N.-B., Chen, C.-R., Chang, L.-Y., Valdez, M., et al. (2013). Multi-decadal mangrove forest change detection and prediction in Honduras, Central America, with Landsat imagery and a Markov chain model. Remote Sensing, 5(12), 6408–6426.

    Article  Google Scholar 

  • Chow, T. E., & Sadler, R. (2010). The consensus of local stakeholders and outside experts in suitability modeling for future camp development. Landscape and Urban Planning, 94(1), 9–19.

    Article  Google Scholar 

  • Earth Observation Centre (2001). Land Use and Land Cover Change for Southeastern Asia, Malaysian Case Study. Asia Pacific Network for Global Change Research (APN) and Universiti Kebangsaan Malaysia (UKM).

  • Eastman, J. R. (2009). IDRISI taiga: Guide to GIS and image processing. Worcester: Clark Labs, Clark University.

    Google Scholar 

  • Economic Planning Unit (2013). Economic History. http://www.epu.gov.my/en/economic-history. Accessed 10 Sep 2014.

  • Federal Department of Town and Country Planning. (2010). National physical plan-2. Kuala Lumpur: Ministry of Housing and Local Government.

    Google Scholar 

  • Jaafar, O., Mastura, S. A. S., & Sood, A. M. (2009). Land use and deforestation modelling of river catchments in Klang Valley, Malaysia. Sains Malaysiana, 38(5), 655–664.

    Google Scholar 

  • Jankowski, P., Andrienko, N., & Andrienko, G. (2001). Map-centred exploratory approach to multiple criteria spatial decision making. International Journal of Geographical Information Science, 15(2), 101–127.

    Article  Google Scholar 

  • Jiang, H., & Eastman, J. R. (2000). Application of fuzzy measures in multi-criteria evaluation in GIS. International Journal of Geographical Information Science, 14(2), 173–184.

    Article  Google Scholar 

  • Jokar Arsanjani, J., Helbich, M., Kainz, W., & Darvishi Bloorani, A. (2012). Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion. International Journal of Applied Earth Observation and Geoinformation, 21, 265–275.

    Article  Google Scholar 

  • Kamusoko, C., Aniya, M., Adi, B., & Manjoro, M. (2009). Rural sustainability under threat in Zimbabwe – simulation of future land use/cover changes in the Bindura district based on the Markov-cellular automata model. Applied Geography, 29, 435–447.

    Article  Google Scholar 

  • Koomen, E., Rietveld, P., & Nijs, T. D. (2008). Modelling land-use change for spatial planning support. The Annals of Regional Science, 42, 1–10.

    Article  Google Scholar 

  • Logofet, D. O. (2008). Convexity in projection matrices: projection to a calibration problem. Ecological Modelling, 216(2), 217–228.

    Article  Google Scholar 

  • Malczewski, J. (2010). Multiple criteria decision analysis and geographic information systems. In M. Ehrgott, J. R. Figueira, & S. Greco (Eds.), Trends in multiple criteria decision analysis (International Series in Operations Research & Management Science 1st ed., Vol. 142, p. 462). New York: Springer.

    Google Scholar 

  • Malczewski, J. (2011). Local weighted linear combination. Transactions in GIS, 15(4), 439–455.

    Article  Google Scholar 

  • McGarigal, K., & Marks, B. J. (1994). FRAGSTATS: Spatial pattern analysis program for quantifying landscape structure. Portland: U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station.

    Google Scholar 

  • McGarigal, K., Cushman, S. A., & Ene, E. (2012). FRAGSTATS v4: Spatial pattern analysis program for categorical and continuous maps. Amherst: University of Massachusetts.

    Google Scholar 

  • Ménard, A., & Marceau, D. J. (2005). Exploration of spatial scale sensitivity in geographic cellular automata. Environment and Planning B: Planning and Design, 32(5), 693–714.

    Article  Google Scholar 

  • Ménard, A., & Marceau, D. J. (2007). Simulating the impact of forest management scenarios in an agricultural landscape of southern Quebec, Canada, using a geographic cellular automata. Landscape and Urban Planning, 79, 253–265.

    Article  Google Scholar 

  • Mhangara, P. (2011). Land use/cover change modelling and land degradation assessment in the Keiskamma catchment using remote sensing and GIS. Port Elizabeth: Nelson Mandela Metropolitan University.

    Google Scholar 

  • Mitsova, D., Shuster, W., & Wang, X. (2011). A cellular automata model of land cover change to integrate urban growth with open space conservation. Landscape and Urban Planning, 99, 141–153.

    Article  Google Scholar 

  • Nakakaawa, C. A., Vedeld, P. O., & Aune, J. B. (2011). Spatial and temporal land use and carbon stock changes in Uganda: implications for a future REDD strategy. Mitigation and Adaptation Strategies for Global Change, 16(1), 25–62.

    Article  Google Scholar 

  • Nourqolipour, R., Shariff, A. R. B. M., Balasundram, S. K., Ahmad, N. B., Sood, A. M., Buyong, T., et al. (2014). A GIS-based model to analyze the spatial and temporal development of oil palm land use in Kuala Langat district, Malaysia. Environmental Earth Sciences, 1–14, doi:10.1007/s12665-014-3521-1.

  • Ouedraogo, I., Savadogo, P., Tigabu, M., Dayamba, S. D., & Odén, P. C. (2011). Systematic and random transitions of land-cover types in Burkina Faso, West Africa. International Journal of Remote Sensing, 32(18), 5229–5245.

    Article  Google Scholar 

  • Pan, Y., Roth, A., Yu, Z., & Doluschitz, R. (2010). The impact of variation in scale on the behavior of a cellular automata used for land use change modeling. Computers, Environment and Urban Systems, 34(5), 400–408.

    Article  Google Scholar 

  • Papa, G. L., Palermo, V., & Dazzi, C. (2011). Is land-use change a cause of loss of pedodiversity? The case of the Mazzarrone study area, Sicily. Geomorphology, 135(3), 332–342.

    Article  Google Scholar 

  • Phua, M.-H., & Minowa, M. (2005). A GIS-based multi-criteria decision making approach to forest conservation planning at a landscape scale: a case study in the Kinabalu Area, Sabah, Malaysia. Landscape and Urban Planning, 71(2), 207–222.

    Article  Google Scholar 

  • Pontius, R. G., & Millones, M. (2011). Death to Kappa: birth of quantity disagreement and allocation disagreement for accuracy assessment. International Journal of Remote Sensing, 32(15), 4407–4429.

    Article  Google Scholar 

  • Pontius, R. G., Shusas, E., & McEachern, M. (2004). Detecting important categorical land changes while accounting for persistence. Agriculture, Ecosystems & Environment, 101(2), 251–268.

    Article  Google Scholar 

  • Rempel, R. S., Kaukinen, D., & Carr, A. P. (2012). Patch analyst and patch grid. Thunder Bay: Ontario Ministry of Natural Resources, Centre for Northern Forest Ecosystem Research.

    Google Scholar 

  • Saaty, T. L. (1977). A scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology, 15(3), 234–281.

    Article  Google Scholar 

  • Saaty, T. L. (1980). The analytic hierarchy process: Planning, priority setting, resource allocation. New York: McGraw-Hill International Book Co.

    Google Scholar 

  • Schmitt-Harsh, M. (2013). Landscape change in Guatemala: driving forces of forest and coffee agroforest expansion and contraction from 1990 to 2010. Applied Geography, 40, 40–50.

    Article  Google Scholar 

  • Seto, K. C., & Fragkias, M. (2005). Quantifying spatiotemporal patterns of urban land-use change in four cities of China with time series landscape metrics. Landscape Ecology, 20(7), 871–888.

    Article  Google Scholar 

  • Shoyama, K., & Braimoh, A. K. (2011). Analyzing about sixty years of land-cover change and associated landscape fragmentation in Shiretoko Peninsula, Northern Japan. Landscape and Urban Planning, 101(1), 22–29.

    Article  Google Scholar 

  • Syphard, A. D., Clarke, K. C., & Franklin, J. (2005). Using a cellular automaton model to forecast the effects of urban growth on habitat pattern in southern California. Ecological Complexity, 2(2), 185–203.

    Article  Google Scholar 

  • Verburg, P. H., & Overmars, K. P. (2007). Dynamic simulation of land-use change trajectories with the CLUE-s model. In E. Koomen, J. Stillwell, A. Bakema, & H. Scholten (Eds.), Modelling land-use change: Progress and applications (Vol. 90). Dordrecht: Springer.

    Google Scholar 

  • Wu, F. (1996). A linguistic cellular automata simulation approach for sustainable land development in a fast growing region. Computers, Environment and Urban Systems, 20(6), 367–387.

    Article  Google Scholar 

  • Yaakup, A., Bajuri, H., Bakar, S. Z. A., & Sulaiman, S. Integrated Land Use Assessment (ILA) 2007. For Sustainable Metropolitan Development. In 5th International Seminar on Sustainable Environment Architecture.

  • Zhang, Q., Ban, Y., Liu, J., & Hu, Y. (2011). Simulation and analysis of urban growth scenarios for the Greater Shanghai Area, China. Computers, Environment and Urban Systems, 35, 126–139.

    Article  Google Scholar 

Download references

Acknowledgments

We would like to acknowledge the following people for their strong support in the process of selecting the evaluation factors, categorizing suitability classes, and assigning the AHP weight to the selected criteria.

i Mr. Sallehi Kassim from the Department of Town and Urban Planning Malaysia

ii Ms. Faridah Bt. Ahmad and a group of professionals in the Department of Agriculture Malaysia

iii Mr. Wahid Bin Omar and a group of professionals in the Malaysian Palm Oil Board (MPOB)

Author information

Authors and Affiliations

  1. Geospatial Information Science Research Centre (GIS RC), Faculty of Engineering, Universiti Putra Malaysia, UPM Serdang, Selangor, 43400, Malaysia

    Ramin Nourqolipour & Abdul Rashid B. Mohamed Shariff

  2. Faculty of Agriculture, Universiti Putra Malaysia, UPM Serdang, Selangor, 43400, Malaysia

    Siva K. Balasundram

  3. National Space Agency of Malaysia (ANGKASA), Lot 2233, Kg. Sungai Lang, 42700, Banting, Selangor, Malaysia

    Noordin B. Ahmad

  4. Faculty of Forestry, Universiti Putra Malaysia, UPM Serdang, Selangor, 43400, Malaysia

    Alias M. Sood

  5. Geospatial Information Science Research Centre (GIS RC), Faculty of Engineering, Universiti Putra Malaysia, UPM Serdang, Selangor, 43400, Malaysia

    Taher Buyong

Authors
  1. Ramin Nourqolipour
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Abdul Rashid B. Mohamed Shariff
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Siva K. Balasundram
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Noordin B. Ahmad
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Alias M. Sood
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Taher Buyong
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Abdul Rashid B. Mohamed Shariff.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nourqolipour, R., Shariff, A.R.B.M., Balasundram, S.K. et al. Predicting the Effects of Urban Development on Land Transition and Spatial Patterns of Land Use in Western Peninsular Malaysia. Appl. Spatial Analysis 9, 1–19 (2016). https://doi.org/10.1007/s12061-014-9128-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12061-014-9128-9

Keywords

Search

Navigation