Direction of urban expansion in the Bangkok Metropolitan Area, Thailand under the impacts of a national strategy
Author affiliations
DOI:
https://doi.org/10.15625/2615-9783/16313Keywords:
Bangkok Metropolitan Area, Eastern Economic Corridor, urbanization dynamics, spatial analysis, urban expansionAbstract
The Eastern Economic Corridor project (EEC), which spans over three coastal provinces east of the Bangkok Metropolitan Area (BMA), aims to transform Thailand into a developed country progressively. The EEC project promises to influence its territory and surrounding areas. We aimed to monitor the urbanized directions at the BMA during 2015-2017 and explore whether the BMA’s urban expansion trend is related to the EEC. The results revealed that the built-up areas increased by 24,033 hectares (22.8%). The urban districts with high urban density slowly developed, while the rural districts tended to urbanize with a high urbanization rate, approximately 6.8% per year. The BMA urban areas mainly expanded to the east (14.9% per year) and southeast (21.6% per year) under partial impacts from the EEC infrastructure projects. The research findings represent a concept for assessing urban expansion and pointing to the regions of concern, which will be meaningful for urban planning and policymaking.
Downloads
References
Aboelnour M., Engel B.A., 2018. Application of Remote Sensing Techniques and Geographic Information Systems to Analyze Land Surface Temperature in Response to Land Use/Land Cover Change in Greater Cairo Region, Egypt. J. Geogr. Inf. Syst., 10, 57-88. https://doi.org/10.4236/jgis.2018.101003.
Ahmad F., Goparaju L., 2016. Analysis of Urban Sprawl Dynamics Using Geospatial Technology in Ranchi City, Jharkhand, India. J. Environ. Geogr., 9, 7-13. https://doi.org/10.1515/jengeo-2016-0002.
Alananzeh O., Maaiah B., Al-Badarneh M., Al-Shorman A., 2018. The geographic distribution of conferences in Jordan from 2014 to 2016 using predictive GIS modeling. J. Conv. Event Tour., 19, 167-185. https://doi.org/10.1080/15470148.2017.1406832.
Aman N., Manomaiphiboon K., Pengchai P., Suwanathada P., Srichawana J., Assareh N., 2019. Long-term observed visibility in eastern Thailand: temporal variation, association with air pollutants and meteorological factors, and trends. Atmosphere (Basel), 10. https://doi.org/10.3390/atmos10030122.
Andrefouet S., Bindschadler R., Brown De Colstoun E.C., Choate M., Chomentowski W., Christopherson J., Doorn B., Hall D.K., Holifield C., Howard S., Kranenburg C., Lee S., Masek J.B., Moran M., Mueller-Karger F., Ohlen D., Palandro D., Price J., Qi J., Reed B., Samek J., Scaramuzza P., Skole D., Schott J., Storey J., Thome K., Torres-Pulliza D., Vogelmann J., Williams D.L., Woodcock C., Wylie B., 2003. Preliminary Assessment of the Value of Landsat 7 ETM+ Data following Scan Line Corrector Malfunction.
Bhrammanachote W., 2019. The Review of Thailand’s Eastern Economic Corridor: Potential and Opportunity. Local Adm. J., 12, 73-86.
Bouhennache R., Bouden T., Taleb A.A., Chaddad A., 2015. Extraction of urban land features from TM Landsat image using the land features index and Tasseled cap transformation [WWW Document]. Recent Adv. Electroscience Comput. URL http://www.inase.org/library/2015/barcelona/bypaper/ELECTR/ELECTR-22.pdf.
Can N.T., Diep N.T.H., Iabchoon S., Varnakovida P., Minh V.Q., 2019. Analysis of Factors Affecting Urban Heat Island Phenomenon in Bangkok Metropolitan Area, Thailand. VNU J. Sci. Earth Environ. Sci., 35, 53-62. https://doi.org/10.25073/2588-1094/vnuees.4355.
Congalton R.G., 1991. A review of assessing the accuracy of classifications of remotely sensed data. Remote Sens. Environ., 37, 35-46. https://doi.org/10.1016/0034-4257(91)90048-B.
Congalton R.G., Green K., 2009. Assessing the Accuracy of Remotely Sensed Data: Principles and Practices, Second edi. ed, The Photogrammetric Record. Taylor & Francis Group. https://doi.org/10.1111/j.1477-9730.2010.00574_2.x.
Deuskar C., Baker J.L., Mason D., 2015. East Asia’s Changing Urban Landscape: Measuring a decade of spatial growth. World Bank Publications, Washington DC.
Diep N.T.H., Korsem T., Can N.T., Phonphan W., Vo Quang Minh, 2019. Determination of aquaculture distribution by using remote sensing technology in Thanh Phu district, Ben Tre province, Vietnam. Vietnam J. Sci. Technol. Eng., 61, 35-41. https://doi.org/10.31276/VJSTE.61(2).35-41.
Duan P. Van, Thin V.T., Huy N.Q., 2016. Estimated value of the object-oriented optimal segmentation parameters within ecognition software: Experiments in satellite images SPOT6. J. For. Sci. Technol., 6, 18-30.
EECO, 2018. Eastern Economic Corridor Office Website [WWW Document]. URL https://www.eeco.or.th/en (accessed 9.9.19).
El-borsh S.H., El-mewafi M., Zarzoura F., 2017. Studying and Evaluating the Development axis in Damietta Governorate based on Geographic Information System (GIS). Int. J. Sci. Eng. Res., 8, 1726-1736.
ESRI, 2016. How Directional Distribution (Standard Deviational Ellipse) works [WWW Document]. Environ. Syst. Res. Institute, Inc. URL http://desktop.arcgis.com/en/arcmap/10.3/tools/spatial-statistics-toolbox/h-how-directional-distribution-standard-deviationa.htm (accessed 5.7.18).
Falkowski M.J., Gessler P.E., Morgan P., Hudak A.T., Smith A.M.., 2005. Characterizing and mapping forest fire fuels using ASTER imagery and gradient modeling. For. Ecol. Manage., 217, 129-146. https://doi.org/10.1016/j.foreco.2005.06.013.
Gautam V.K., Gaurav P.K., Murugan P., Annadurai M., 2015. Assessment of Surface Water Dynamicsin Bangalore Using WRI, NDWI, MNDWI, Supervised Classification and K-T Transformation. Aquat. Procedia Int. Conf. water Resour. Coast. Ocean Eng. (ICWRCOE 2015), 4, 739-746. https://doi.org/10.1016/j.aqpro.2015.02.095.
Guangjin T., Xinliang X., Xiaojuan L., Lingqiang K., 2016. The Comparison and Modeling of the Driving Factors of Urban Expansion for Thirty-Five Big Cities in the Three Regions in China. Adv. Meteorol. https://doi.org/10.1155/2016/3109396.
Ha L.T.T., Trung N. Van, Lan P.T., Ai T.T.H., Hien L.P., 2021. Impacts of urban land cover change on land surface temperature distribution in Ho Chi Minh city, vietnam. J. Korean Soc. Surv. Geod. Photogramm. Cartogr., 39, 113–122. https://doi.org/10.7848/ksgpc.2021.39.2.113.
Hara Y., Takeuchi K., Okubo S., 2005. Urbanization linked with past agricultural landuse patterns in the urban fringe of a deltaic Asian mega-city: A case study in Bangkok. Landsc. Urban Plan., 73, 16-28. https://doi.org/10.1016/j.landurbplan.2004.07.002.
Hara Y., Thaitakoo D., Takeuchi K., 2008. Landform transformation on the urban fringe of Bangkok : The need to review land-use planning processes with consideration of the flow of fill materials to developing areas. Landsc. Urban Plan., 84, 74-91. https://doi.org/10.1016/j.landurbplan.2007.06.009.
Hegazy I.R., Kaloop M.R., 2015. Monitoring urban growth and land use change detection with GIS and remote sensing techniques in Daqahlia governorate Egypt. Int. J. Sustain. Built Environ., 4, 117-124. https://doi.org/10.1016/j.ijsbe.2015.02.005.
Heurlin C., 2019. Unemployment among land-losing farmers in China: Evidence from the 2010 census. J. Contemp. China, 28, 434-452. https://doi.org/10.1080/10670564.2018.1542223.
Hofmann A., Wan G., 2013. Determinants of urbanization, ADB Economics Working Paper Series. Manila, Philippines. https://doi.org/10.2139/ssrn.2295736.
Hu T., Yang J., Li X., Gong P., 2016. Mapping urban land use by using landsat images and open social data. Remote Sens., 8. https://doi.org/10.3390/rs8020151.
Jacquin A., Misakova L., Gay M., 2008. A hybrid object-based classification approach for mapping urban sprawl in periurban environment. Landsc. Urban Plan., 84, 152-165. https://doi.org/10.1016/j.landurbplan.2007.07.006.
Jongkroy P., 2009. Urbanization and changing settlement patterns in Peri-urban Bangkok. Kasetsart J. - Soc. Sci., 30, 303-312.
Kazmier L., 2003. Schaum’s Outline of Business Statistics.
Keawko W., Thanasing T., Suwanmanee A., 2018. Thailand Economic with Eastern Economic Corridor Development. J. MCU Alumni Assoc., 7, 35-42.
Keivani R., 2010. A review of the main challenges to urban sustainability. Int. J. Urban Sustain. Dev., 1, 5-16. https://doi.org/10.1080/19463131003704213.
Koen V., Asada H., Rizwan M., Rahuman H., 2018. Boosting productivity and living standards in Thailand. OECD Econ. Dep. Work. Pap. https://doi.org/10.1787/e525c875-en.
Korpilo S., Virtanen T., Saukkonen T., Lehvävirta S., 2018. More than A to B: Understanding and managing visitor spatial behaviour in urban forests using public participation GIS. J. Environ. Manage., 207, 124-133. https://doi.org/10.1016/j.jenvman.2017.11.020.
Kuang W., Chi W., Lu D., Dou Y., 2014. A comparative analysis of megacity expansions in China and the U.S.: Patterns, rates and driving forces. Landsc. Urban Plan., 132, 121-135. https://doi.org/10.1016/j.landurbplan.2014.08.015.
Kumar M., 2004. Digital image processing, in: Sivakumar M.V.K., Roy P.S., Harmsen K., Saha S.K. (Eds.), Satellite Remote Sensing and GIS Applications in Agricultural Meteorology. World Meteorological Organisation, Switzerland, 81-102.
Lee M., 2015. Create Ring Maps.
Manotham P., 2010. Bangkok Urban Dynamics and Housing Market. Stockholm Royal Institute of Technology.
MEA, 2016. Sustainability Report 2016. Move forward to Smart Metro. Bangkok metropolis.
Miller R.L., Liu C.C., Buonassissi C.J., Wu A.M., 2011. A multi-sensor approach to examining the distribution of total suspended matter (TSM) in the Albemarle-Pamlico Estuarine System, NC, USA. Remote Sens., 3, 962-974. https://doi.org/10.3390/rs3050962.
Minh V.Q., 2010. Remote sensing Technology. Can Tho Univeristy Publishing House.
MLIT, 2013. An overview of Spatial policy in Asian and European Countries [WWW Document]. Minist. Land, Infrastructure, Transp. Tour. (MLIT), Japan. URL http://www.mlit.go.jp/kokudokeikaku/international/spw/general/thailand/index_e.html (accessed 10.2.18).
Molnar G., 2016. Analysis of land surface temperature and ndvi distribution for budapest using Landsat 7 ETM+ data. Acta Climatol. Chorol., 49-50, 49-61.
Motohka T., Nasahara K.N., Oguma H., Tsuchida S., 2010. Applicability of Green-Red Vegetation Index for remote sensing of vegetation phenology. Remote Sens., 2, 2369-2387. https://doi.org/10.3390/rs2102369.
Mukherjee F., Singh D., 2020. Assessing Land Use-Land Cover Change and Its Impact on Land Surface Temperature Using LANDSAT Data: A Comparison of Two Urban Areas in India. Earth Syst. Environ., 4, 385-407. https://doi.org/10.1007/s41748-020-00155-9.
Murakamia A., Zain A.M., Takeuchi K., Tsunekawa A., Yokota S., 2005. Trends in urbanization and patterns of land use in the Asian mega cities Jakarta, Bangkok, and Metro Manila. Landsc. Urban Plan., 70, 251-259. https://doi.org/10.1016/j.landurbplan.2003.10.021.
Nakagawa S., 2004. Changing distribution of gender in the Extended Bangkok Region under globalization. GeoJournal, 61, 255-262. https://doi.org/10.1007/s10708-004-3683-6.
Nguyen C.T., Chidthaisong A., Diem P.K., Huo L., 2021a. A Modified Bare Soil Index to Identify Bare Land Features during Agricultural Fallow-Period in Southeast Asia Using Landsat 8. Land, 10, 1-17. https://doi.org/10.3390/land10030231.
Nguyen C.T., Nguyen D.T.H., Phan D.K., 2021b. Factors affecting urban electricity consumption: a case study in the Bangkok Metropolitan Area using an integrated approach of earth observation data and data analysis. Environ. Sci. Pollut. Res., 28, 12056-12066. https://doi.org/10.1007/s11356-020-09157-6.
Nitivattananon V., Srinonil S., 2019. Enhancing coastal areas governance for sustainable tourism in the context of urbanization and climate change in eastern Thailand. Adv. Clim. Chang. Res., 10, 47-58. https://doi.org/10.1016/j.accre.2019.03.003.
Pansuwan A., Routray J.K., 2011. Policies and pattern of industrial development in Thailand. GeoJournal, 76, 25-46. https://doi.org/10.1007/s10708-010-9400-8.
Peng X., Chen X., Cheng Y., 2010. Urbanization and Its Conesequences, in: Zheng, Y. (Ed.), Demography. Encyloedia of Life Support Systems. Encyclopedia of Life Support Systems (EOLSS), UK, 210-235.
Pruksanubal B., 2016. Land Use Transformation Process in Chachoengsao Province, Thailand. Procedia-Soc. Behav. Sci., 222, 772-781. https://doi.org/10.1016/j.sbspro.2016.05.159.
Qiao K., Zhu W., Hu D., Hao M., Chen S., Cao S., 2017. Examining the distribution and dynamics of impervious surface in different functional zones of Beijing. Dili Xuebao/Acta Geogr. Sin., 72, 2018-2031. https://doi.org/10.11821/dlxb201711008
Ramachandra T.V., Bharath A.H., Sowmyashree M.V., 2015. Monitoring urbanization and its implications in a mega city from space: Spatiotemporal patterns and its indicators. J. Environ. Manage., 148, 67-81. https://doi.org/10.1016/j.jenvman.2014.02.015.
Rawat J.S., Kumar M., 2015. Monitoring land use/cover change using remote sensing and GIS techniques: A case study of Hawalbagh block, district Almora, Uttarakhand, India. Egypt. J. Remote Sens. Sp. Sci., 18, 77-84. https://doi.org/10.1016/j.ejrs.2015.02.002.
Rubiera Morollón F., González Marroquín V.M., Pérez Rivero J.L., 2017. Urban sprawl in Madrid?: An analysis of the urban growth of Madrid during the last quarter of the twentieth century. Lett. Spat. Resour. Sci., 10, 205-214. https://doi.org/10.1007/s12076-016-0181-7
Shen W., Wu J., Grimm N.B., Hope D., 2008. Effects of urbanization-induced environmental changes on ecosystem functioning in the Phoenix metropolitan region, USA. Ecosystems, 11, 138-155. https://doi.org/10.1007/s10021-007-9085-0.
Shouhai D., 2015. Employment in Township Urbanization in China. Soc. Sci. China, 36, 152-167. https://doi.org/10.1080/02529203.2015.1029675.
Singh A., Kumar U., Seitz F., 2015. Remote sensing of storage fluctuations of poorly gauged reservoirs and state space model (SSM)-based estimation. Remote Sens., 8, 17113-17134. https://doi.org/10.3390/rs8110960.
Son N.T., Chen C.F., Chen C.R., 2020. Urban expansion and its impacts on local temperature in San Salvador, El Salvador. Urban Clim., 32, 100617. https://doi.org/10.1016/j.uclim.2020.100617.
Son N.T., Chen C.F., Chen C.R., Thanh B.X., Vuong T.H., 2017. Assessment of urbanization and urban heat islands in Ho Chi Minh City, Vietnam using Landsat data. Sustain. Cities Soc., 30, 150-161. https://doi.org/10.1016/j.scs.2017.01.009.
Son N.T., Thanh B.X., 2018. Decadal assessment of urban sprawl and its effects on local temperature using Landsat data in Cantho city, Vietnam. Sustain. Cities Soc., 36, 81-91. https://doi.org/10.1016/j.scs.2017.10.010.
Song Y., Aryal J., Tan L., Jin L., Gao Z., Wang Y., 2021. Comparison of changes in vegetation and land cover types between Shenzhen and Bangkok. L. Degrad. Dev., 32, 1192-1204. https://doi.org/10.1002/ldr.3788.
Stewart J.E., Battersby S.E., Lopez-De Fede A., Remington K.C., Hardin J.W., Mayfield-Smith K., 2011. Diabetes and the socioeconomic and built environment: Geovisualization of disease prevalence and potential contextual associations using ring maps. Int. J. Health Geogr., 10, 1-10. https://doi.org/10.1186/1476-072X-10-18.
Sun W., Chen B., Messinger D.W., 2014. Nearest-neighbor diffusion-based pan-sharpening algorithm for spectral images. Opt. Eng., 53, 013107-1-11. https://doi.org/10.1117/1.OE.53.1.013107.
Thanh L. Van, 2007. Economic development, urbanization and environmental changes in Ho Chi Minh city, Vietnam: Relations and policies, in: PRIPODE Workshop on Urban Population, Development and Environment Dynamics in Developing Countries. Nairobi, Kenya.
Tolessa T., Senbeta F., Kidane M., 2017. The impact of land use/land cover change on ecosystem services in the central highlands of Ethiopia. Ecosyst. Serv., 23, 47-54. https://doi.org/10.1016/j.ecoser.2016.11.010.
Tontisirin N., Phoomikiattisak D., Anantsuksomsri S., 2017. Land Use Change in the Eastern Economic Corridor of Thailand: An Application of Cellular Automata-Makov Model, in: The 54th Annual Meeting of the Japan Section of the RSAI, 1-7.
Tran D.X., Pla F., Latorre-Carmona P., Myint S.W., Caetano M., Kieu H.V., 2017. Characterizing the relationship between land use land cover change and land surface temperature. ISPRS J. Photogramm. Remote Sens., 124, 119-132. https://doi.org/10.1016/j.isprsjprs.2017.01.001.
Tsuchiya K., Hara Y., Thaitakoo D., 2015. Linking food and land systems for sustainable peri-urban agriculture in Bangkok Metropolitan Region. Landsc. Urban Plan., 143, 192-204. https://doi.org/10.1016/j.landurbplan.2015.07.008.
Tucker C.J., 1979. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens. Environ., 8, 127-150. https://doi.org/10.1016/0034-4257(79)90013-0.
United Nations, 2018. The World’s Cities in 2018: Data Booklet. Population Division, Department of Economic and Social Affairs, United Nations, New York.
Viera A.J., Garrett J.M., 2005. Understanding Interobserver Agreement: The Kappa Statistic. Fam. Med., 37, 360-363.
Viet P.B., Thi T. Lan H., Phung H.P., 2014. Performance of Landsat 7 ETM+ Image in SLC-Off Mode for land cover classification, in: International Symposium on Geoinformatics for Spatial Infrastructure Development in Earth and Allied Sciences, 3-8.
Watson D.F., 1992. Contouring. A guide to the analysis and display of spatial data. Oxford: Elsevier.
Wulder M.A., Ortlepp S.M., White J.C., Maxwell S., 2008. Evaluation of Landsat-7 SLC-off image products for forest change detection. Can. J. Remote Sens., 34, 93-99. https://doi.org/10.5589/m08-020.
Xinmin Z., Estoque R.C., Murayama Y., 2017. An urban heat island study in Nanchang City, China based on land surface temperature and social-ecological variables. Sustain. Cities Soc., 32, 557-568. https://doi.org/10.1016/j.scs.2017.05.005.
Yamashita A., 2017. Bangkok Metropolitan Area, in: Murayama Y., Kamusoko C., Yamashita A., Estoque R.C. (Eds.), Urban Development in Asia and Africa. The Urban Book Series. Springe, Singapore, 151-169. https://doi.org/10.1007/978-981-10-3241-7.
Zha Y., Gao J., Ni S., 2003. Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. Int. J. Remote Sens., 24, 583-594. https://doi.org/10.1080/01431160304987.