Assessment of Urban Sprawl, Land Use and Land Cover Changes in Voi Town, Kenya Using Remote Sensing and Landscape Metrics
Journal of Geography, Environment and Earth Science International,
Page 50-61
DOI:
10.9734/jgeesi/2022/v26i430347
Abstract
Rapid and uncontrolled urbanization is a major issue in both developing and developed countries. Uncontrolled urbanization has resulted to unplanned expansion of residential and commercial areas, informal settlements, housing shortages, and unplanned land use. Understanding and quantifying urban sprawl spatiotemporal patterns is critical for informing the development of appropriate policies for effective and sustainable land use management. Using image classification and spatial metrics, this study examines the changes in Voi town's urban land use/land cover (LULC) between 1999 and 2019. The LULC was mapped using Landsat Thematic Mapper (TM):Landsat Enhanced Thematic Mapper Plus (ETM+):and Landsat Operational Land Imager (OLI) datasets using supervised maximum likelihood classification. A post classification approach was used to detect and assess LULC changes in the study area, while selected spatial metric indices quantified urban sprawl. The results of the change detection analysis revealed that Voi town has been rapidly expanding, with an urban expansion of 187.96 percent from 1999 to 2011, 183.40 percent from 2011 to 2019, and 716.1 percent from 1999 to 2019. In 1999, the built-up area comprised 1.29 percent of the total study area, 3.72 percent in 2011, and 10.53 percent in 2019. Based on spatial metrics analysis, the number of built-up area patches in 1999, 2011, and 2019 was 154, 278, and 526, respectively. An increase in the number of patches indicated fragmentation and the emergence of new built-up areas.
As a result, city planners will need to plan ahead of time and implement additional measures to deal with the city's future rapid and unprecedented growth.
Keywords:
- Land use/ land cover
- supervised classification
- change detection
- spatial metrics
How to Cite
Nyongesa, S. K., Maghenda, M., & Siljander, M. (2022). Assessment of Urban Sprawl, Land Use and Land Cover Changes in Voi Town, Kenya Using Remote Sensing and Landscape Metrics. Journal of Geography, Environment and Earth Science International, 26(4), 50-61. https://doi.org/10.9734/jgeesi/2022/v26i430347
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Desa U. United Nations, Department of Economic and Social Affairs, Population Division. World Population Prospects 2018. Online Edition. Rev. 2018;1.
UNHABITAT. Urbanisation and Development: Emerging Futures. World Cities Report 2016: United Nations Human Settlements Programme; 2016.
KNBS Kenya National Bureau of Statistics: Kenya National Population and Housing Census 2019. Nairobi: KNBS; 2020
BenBella DE. An evaluation and analysis of urban expansion of Kampala from 1995 to 2015 (Doctoral dissertation, Southern Illinois University Carbondale); 2016.
Mosammam HM, Nia JT, Khani H, Teymouri A, Kazemi M. Monitoring land use change and measuring urban sprawl based on its spatial forms: The case of Qom city. The Egyptian Journal of Remote Sensing and Space Science. 2017; 20(1):103-116.
Saghir J, Santoro J. Urbanization in Sub-Saharan Africa. Meeting Challenges by Bridging Stakeholders. Center for Strategic & International Studies. 2018;(April):1–7.
United Nations U. The Millennium Development Goals Report 2015. Department of Economic and Social Affairs, Population Division, United Nations, New York; 2015.
Getu K, Bhat HG. Analysis of spatio-temporal dynamics of urban sprawl and growth pattern using geospatial technologies and landscape metrics in Bahir Dar, Northwest Ethiopia. Land Use Policy. 2021;109:105676.
Aithal BH, Ramachandra TV. Visualization of urban growth pattern in Chennai using geoinformatics and spatial metrics. Journal of the Indian Society of Remote Sensing. 2016; 44(4):617-633.
Chakraborti S, Das DN, Sannigrahi S, Banerjee A. Assessing dynamism of urban built-up growth and landuse change through spatial metrics: A study on Siliguri and its surroundings; 2018.
Abass K, Adanu SK, Gyasi RM. Urban sprawl and land use/land-cover transition probabilities in peri-urban Kumasi, Ghana. West African Journal of Applied Ecology. 2018;26:118-132.
Yiran GAB, Ablo AD, Asem FE, Owusu G. Urban sprawl in sub-Saharan Africa: A review of the literature in selected countries. Ghana Journal of Geography. 2020;12(1):1-28.
Shao Z, Sumari NS, Portnov A, Ujoh F, Musakwa W, Mandela PJ. Urban sprawl and its impact on sustainable urban development: a combination of remote sensing and social media data. Geo-spatial Information Science. 2021;24(2):241-255.
Jing Y, Liu Y, Cai E, Liu Y, Zhang Y. Quantifying the spatiality of urban leisure venues in Wuhan, Central China–GIS-based spatial pattern metrics. Sustainable Cities and Society. 2018;40:638-647.
Yılmaz M, Terzi F. Measuring the patterns of urban spatial growth of coastal cities in developing countries by geospatial metrics. Land Use Policy. 2021;107:105487.
Abedini A, Khalili A, Asadi N. Urban sprawl evaluation using landscape metrics and black-and-white hypothesis (Case Study: Urmia City). Journal of the Indian Society of Remote Sensing. 2020;48(7):1021-1034.
Magidi J, Ahmed F. Assessing urban sprawl using remote sensing and landscape metrics: A case study of City of Tshwane, South Africa (1984–2015). The Egyptian Journal of Remote Sensing and Space Science. 2019;22(3):335-346.
Mandal S, Kundu S, Halder S, Bhattacharya S, Paul S. Monitoring and measuring the urban forms using spatial metrics of Howrah City, India; 2020.
Terfa BK, Chen N, Liu D, Zhang X, Niyogi D. Urban expansion in Ethiopia from 1987 to 2017: Characteristics, spatial patterns, and driving forces. Sustainability. 2019; 11(10):2973.
Herold M, Couclelis H, Clarke KC. The role of spatial metrics in the analysis and modeling of urban land use change. Computers, Environment and Urban Systems. 2005;29(4):369-399.
Cengiz S, Görmüş S, Oğuz D. Analysis of the urban growth pattern through spatial metrics; Ankara City. Land Use Policy. 2022;112:105812.
Narmada K, Gogoi D, Bhaskaran G. Landscape metrics to analyze the forest fragmentation of Chitteri Hills in Eastern Ghats, Tamil Nadu. Journal of Civil Engineering and Environmental Sciences. 2021;7(1):001-007.
Angel S, Parent J, Civco D. Urban sprawl metrics: an analysis of global urban expansion using GIS. In Proceedings of ASPRS 2007 Annual Conference, Tampa, Florida May. Citeseer. 2007, May;7(11).
KNBS Kenya National Bureau of Statistics: Kenya National Population and Housing Census 2009. Nairobi: KNBS; 2010.
Republic of Kenya, 2001. 1999 Population and Housing Census Vol. 1 & II. Central Bureau of Statistics & Ministry of Finance and Planning; 2001.
Republic of Kenya, 1994. Kenya Population Census 1989 Vol. 1. Central Bureau of Statistics , Office of the Vice President & Ministry of Planning and National Development 1994.
Dimitrov P, Olofsson P, Jelev G, Kamenova I. Mapping of forest cover change by post-classification comparison and multitemporal classification of spot data–a Bulgarian case study. Aerospace Research in Bulgaria. 2018;30:42-62.
Liping C, Yujun S, Saeed S. Monitoring and predicting land use and land cover changes using remote sensing and GIS techniques—A case study of a hilly area, Jiangle, China. PLoS ONE. 2018;13(7). DOI:https://doi.org/10.1371/journal.pone.0200493
Moghadam NK, Delavar MR, Forati A. Vegetation monitoring of Mashhad using an object-oriented post classification comparison method. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives. 2017;42(4W4):123–131. DOI:https://doi.org/10.5194/isprs-archives-XLII-4-W4-123-2017
Tajbakhsh M, Memarian H, Shahrokhi Y. Analyzing and modeling urban sprawl and land use changes in a developing city using a CA-Markovian approach. Autumn 2016 Global J. Environ. Sci. Manage. 2016;2(4):397–410.
Almutairi A, Warner TA. Change detection accuracy and image properties : A study. 2010; 1508–1529. DOI:https://doi.org/10.3390/rs2061508
McGarigal, K, Cushman S.A, & Ene, E. (2012). FRAGSTATS v4: spatial pattern analysis program for categorical and continuous maps (University of Massachusetts, Amherst).
Foody GM. Harshness in image classification accuracy assessment. International Journal of Remote Sensing. 2008;29(11):3137-3158.
Cheruto MC, Kauti MK, Kisangau DP, Kariuki PC. Assessment of land use and land cover change using GIS and remote sensing techniques: A case study of Makueni County, Kenya; 2016.
Hegazy IR, Kaloop MR. Monitoring urban growth and land use change detection with GIS and remote sensing techniques in Daqahlia governorate Egypt. International Journal of Sustainable Built Environment. 2015;4(1):117-124.
Vivekananda GN, Swathi R, Sujith AVLN. Multi-temporal image analysis for LULC classification and change detection. European Journal of Remote Sensing. 2021;54(sup2):189-199.
Wan Y, Deng C, Wu T, Jin R, Chen P, Kou R. Quantifying the spatial integration patterns of urban agglomerations along an inter-city gradient. Sustainability (Switzerland). 2019;11(18):1–22. DOI:https://doi.org/10.3390/su11185000
Sinha SK. Spatial metrics : A tool for measurement of urban growth / sprawl spatial metrics. Jigyasa. 2018;11(3):974–7648.
Thapa RB, Murayama Y. Examining spatiotemporal urbanization patterns in Kathmandu Valley, Nepal: Remote sensing and spatial metrics approaches. Remote Sensing. 2009;1(3):534–556. DOI:https://doi.org/10.3390/rs1030534
Tian P, Cao L, Li J, Pu R, Shi X, Wang L, Shao S. Landscape grain effect in Yancheng coastal wetland and its response to landscape changes. International Journal of Environmental Research and Public Health. 2019; 16(12):2225.
Gezahegn Aweke Abebe. Quantifying urban growth pattern in developing countries using remote sensing and spatial metrics: A case study in Kampala, Uganda. Enschede. 2013; 108.
Talukdar S, Eibek KU, Akhter S, Ziaul SK, Islam ARMT, Mallick J. Modeling fragmentation probability of land-use and land-cover using the bagging, random forest and random subspace in the Teesta River Basin, Bangladesh. Ecological Indicators. 2021;126:107612.
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