A review of the application and implications of cellular automata-based urban growth model in Africa

References

• Aburas, M. M., Ho, Y. M., Ramli, M. F., & Ash’aari, Z. H. (2016). The simulation and prediction of spatio-temporal urban growth trends using cellular automata models: A review. International Journal of Applied Earth Observation and Geoinformation, 52, 380–389. https://doi.org/10.1016/j.jag.2016.07.007
   Web of Science ®Google Scholar
• Aburas, M. M., Ho, Y. M., Ramli, M. F., & Ash’aari, Z. H. (2017). Improving the capability of an integrated CA-Markov model to simulate spatio-temporal urban growth trends using an analytical hierarchy process and frequency ratio. International Journal of Applied Earth Observation and Geoinformation, 59, 65–78. https://doi.org/10.1016/j.jag.2017.03.006
   Web of Science ®Google Scholar
• Abutaleb, K., & Ahmed, F. (2016). Modeling of urban change using remote sensing data and cellular automata technique. Arabian Journal of Geosciences, 9(15), 1–10. https://doi.org/10.1007/s12517-016-2696-z
   Web of Science ®Google Scholar
• Alqurashi, A., Kumar, L., & Sinha, P. (2016). Urban land cover change modelling using time-series satellite images: A case study of urban growth in five cities of Saudi Arabia. Remote Sensing, 8(10), 838. https://doi.org/10.3390/rs8100838
   Web of Science ®Google Scholar
• Al-Sharif, A. A. A. A., & Pradhan, B. (2014). Monitoring and predicting land use change in Tripoli Metropolitan City using an integrated Markov chain and cellular automata models in GIS. Arabian Journal of Geosciences, 7(10), 4291–4301. https://doi.org/10.1007/s12517-013-1119-7
   Web of Science ®Google Scholar
• Al-Sharif, A. A. A. A., & Pradhan, B. (2015). A novel approach for predicting the spatial patterns of urban expansion by combining the chi-squared automatic integration detection decision tree, Markov chain and cellular automata models in GIS. Geocarto International, 30(8), 858–881. https://doi.org/10.1080/10106049.2014.997308
   Web of Science ®Google Scholar
• Ansong, D., Ansong, E. K., Ampomah, A. O., & Adjabeng, B. K. (2015). Factors contributing to spatial inequality in academic achievement in Ghana: Analysis of district-level factors using geographically weighted regression. Applied Geography, 62, 136–146. https://doi.org/10.1016/j.apgeog.2015.04.017
   Web of Science ®Google Scholar
• Appiah, D., Forkuo, E., Bugri, J., & Apreku, T. (2017). Geospatial analysis of land use and land cover transitions from 1986–2014 in a peri-urban Ghana. Geosciences, 7(4), 125. https://doi.org/10.3390/geosciences7040125
   Google Scholar
• Arsanjani, J. J. Fibæk, C. S., & Vaz, E. (2018). Development of a cellular automata model using open source technologies for monitoring urbanisation in the global south: The case of Maputo, Mozambique.Habitat International, 71(), 38–48. https://doi.org/10.1016/j.habitatint.2017.11.003
   Web of Science ®Google Scholar
• Awotwi, A., Anornu, G. K., Quaye-Ballard, J. A., & Annor, T. (2018). Monitoring land use and land cover changes due to extensive gold mining, urban expansion, and agriculture in the Pra River Basin of Ghana, 1986–2025. Land Degradation and Development, 29(10), 3331–3343. https://doi.org/10.1002/ldr.3093
   Web of Science ®Google Scholar
• Badwi, I. M., El_barmelgy, M. M., & El_din Ouf, A. S. (2022). Modeling and prediction of expected informal growth in the Greater Cairo Region, Egypt. Environment and Planning B: Urban Analytics and City Science, 49(2), 427–446. https://doi.org/10.1177/23998083211002207
   Google Scholar
• Barredo, J. I., Demicheli, L., Lavalle, C., Kasanko, M., & McCormick, N. (2004). Modelling future urban scenarios in developing countries: An application case study in Lagos, Nigeria. Environment and Planning B: Planning and Design, 31(1), 65–84. https://doi.org/10.1068/b29103
   Web of Science ®Google Scholar
• Batty, M. (2008). The size, scale, and shape of cities. Science, 319(5864), 769–771. https://doi.org/10.1126/science.1151419
   PubMed Web of Science ®Google Scholar
• Batty, M. (2012). Managing complexity, reworking prediction. Environment and Planning B: Planning and Design, 39(4), 607–608. https://doi.org/10.1068/b3904ed
   Google Scholar
• Becker, C. M., & Morrison, A. R. (2005). The determinants of urban population growth in Sub-Saharan Africa. Economic Development and Cultural Change, 36(2), 259–278. https://doi.org/10.1086/451651
   Google Scholar
• Bisello, A., Vettorato, D., Stephens, R., & Elisei, P. (2017). Smart and sustainable planning for cities and regions: Smart and sustainable planning for cities and regions. November. Springer Nature. https://doi.org/10.1007/978-3-319-44899-2.
   Google Scholar
• Boudet, F., MacDonald, G. K., Robinson, B. E., & Samberg, L. H. (2020). Rural-urban connectivity and agricultural land management across the global south. Global Environmental Change, 60, 101982. January 2020. https://doi.org/10.1016/j.gloenvcha.2019.101982.
   Web of Science ®Google Scholar
• Braimoh, A. K., & Onishi, T. (2007). Spatial determinants of urban land use change in Lagos, Nigeria. Land Use Policy, 24(2), 502–515. https://doi.org/10.1016/j.landusepol.2006.09.001
   Web of Science ®Google Scholar
• Bununu, Y. A. (2017). Integration of Markov chain analysis and similarity-weighted instance-based machine learning algorithm (SimWeight) to simulate urban expansion. International Journal of Urban Sciences, 21(2), 217–237. https://doi.org/10.1080/12265934.2017.1284607
   Web of Science ®Google Scholar
• Chakraborty, A., Wilson, B., & Kashem, S. B. (2015). The pitfalls of regional delineations in land use modeling: Implications for Mumbai region and its planners. Cities, 45, 91–103. https://doi.org/10.1016/j.cities.2015.03.008
   Web of Science ®Google Scholar
• Chaudhuri, G., & Clarke, K. C. (2013). The SLEUTH land use change Model: A review. The International Journal of Environmental Resources Research, 1(1), 88–104.
   Google Scholar
• Cobbinah, P. B., Erdiaw-Kwasie, M. O., & Amoateng, P. (2015). Africa’s urbanisation: Implications for sustainable development. Cities, 47, 62–72. https://doi.org/10.1016/j.cities.2015.03.013
   Web of Science ®Google Scholar
• D’Amour, C. B., Reitsma, F., Baiocchi, G., Barthel, S., Güneralp, B., Erb, K. H., Haberl, H., Creutzig, F., & Seto, K. C. (2017). Future urban land expansion and implications for global croplands. Proceedings of the National Academy of Sciences of the United States of America, 114(34), 8939–8944. https://doi.org/10.1073/pnas.1606036114
   PubMed Web of Science ®Google Scholar
• Dodman, D., Leck, H., Rusca, M., & Colenbrander, S. (2017). African Urbanisation and Urbanism: Implications for risk accumulation and reduction. International Journal of Disaster Risk Reduction, 26(June), 7–15. https://doi.org/10.1016/j.ijdrr.2017.06.029
   Google Scholar
• Effiong, E. L. (2018). On the urbanization-pollution nexus in Africa: A semiparametric analysis. Quality and Quantity, 52(1), 445–456. https://doi.org/10.1007/s11135-017-0477-8
   Google Scholar
• Feng, Y., & Tong, X. (2017). Calibrating nonparametric cellular automata with a generalized additive model to simulate dynamic urban growth. Environmental Earth Sciences, 76(14). https://doi.org/10.1007/s12665-017-6828-x
   PubMed Web of Science ®Google Scholar
• Fitawok, M. B., Derudder, B., Minale, A. S., Passel, Adgo, E., Nyssen, J., & Van Passel, S. (2020). Modeling the impact of urbanization on land-use change in Bahir Dar City, Ethiopia: An Integrated Cellular Automata–Markov chain approach. Land, 9(4), 115. https://doi.org/10.3390/land9040115
   Web of Science ®Google Scholar
• Fitawok, M. B., Derudder, B., Minale, A. S., Van, S., Adgo, E., & Nyssen, J. (2023). Stakeholder perspectives on farmers ’ resistance towards urban land-use changes in Bahir Dar, Ethiopia. Journal of Land Use Science, 18(1), 25–38. https://doi.org/10.1080/1747423X.2023.2181416
   Web of Science ®Google Scholar
• Fitawok, M. B., Derudder, B., Minale, A. S., Van Passel, S., Adgo, E., & Nyssen, J. (2022). Analyzing the impact of land expropriation program on farmers’ livelihood in urban fringes of Bahir Dar, Ethiopia. Habitat International, 129, 102674. https://doi.org/10.1016/J.HABITATINT.2022.102674
   Web of Science ®Google Scholar
• Gashaw, T., Tulu, T., Argaw, M., & Worqlul, A. W. (2018). Modeling the hydrological impacts of land use/land cover changes in the andassa watershed, Blue Nile Basin, Ethiopia. Science of the Total Environment, 619-620, 1394–1408. https://doi.org/10.1016/j.scitotenv.2017.11.191
   PubMed Web of Science ®Google Scholar
• Ghosh, P., Mukhopadhyay, A., Chanda, A., Mondal, P., Akhand, A., Mukherjee, S., Nayak, S. K. K., Ghosh, S., Mitra, D., Ghosh, T., & Hazra, S. (2017). Application of cellular automata and Markov-chain model in geospatial environmental modeling- a review. Remote Sensing Applications: Society & Environment, 5(January), 64–77. https://doi.org/10.1016/j.rsase.2017.01.005
   Google Scholar
• Guerrero, L. A., Maas, G., Hogland, W., Abarca, L., Maas, G., & Hogland, W. (2013). Solid waste management challenges for cities in developing countries. Waste Management, 33(1), 220–232. https://doi.org/10.1016/j.wasman.2012.09.008
   PubMed Web of Science ®Google Scholar
• Güneralp, B., Lwasa, S., Masundire, H., Parnell, S., Seto, K. C., Parnell, S., Masundire, H., Güneralp, B., & Lwasa, S. (2017). Urbanization in Africa: Challenges and opportunities for conservation. Environmental Research Letters, 13(1), 015002. https://doi.org/10.1088/1748-9326/aa94fe
   Web of Science ®Google Scholar
• Halmy, M. W. A., Gessler, P. E., Hicke, J. A., & Salem, B. B. (2015). Land use/land cover change detection and prediction in the north-western coastal desert of Egypt using Markov-CA. Applied Geography, 63, 101–112. September 2015. https://doi.org/10.1016/j.apgeog.2015.06.015.
   Web of Science ®Google Scholar
• Huang, S. L., Wang, S. H., & Budd, W. W. (2009). Sprawl in Taipei’s peri-urban zone: Responses to spatial planning and implications for adapting global environmental change. Landscape and Urban Planning, 90(1–2), 20–32. https://doi.org/10.1016/j.landurbplan.2008.10.010
   Web of Science ®Google Scholar
• Hyandye, C., & Martz, L. W. (2017). A markovian and cellular automata land-use change predictive model of the usangu catchment. International Journal of Remote Sensing, 38(1), 64–81. https://doi.org/10.1080/01431161.2016.1259675
   Web of Science ®Google Scholar
• Jagarnath, M., Thambiran, T., Gebreslasie, M., & Jagarnath, M. (2019). Modelling urban land change processes and patterns for climate change planning in the Durban metropolitan area, South Africa. Journal of Land Use Science, 14(1), 81–109. https://doi.org/10.1080/1747423X.2019.1610809
   Web of Science ®Google Scholar
• Jat, M. K., Choudhary, M., & Saxena, A. (2017). Application of geo-spatial techniques and cellular automata for modelling urban growth of a heterogeneous urban fringe. The Egyptian Journal of Remote Sensing & Space Science, 20(2), 223–241. https://doi.org/10.1016/j.ejrs.2017.02.002
   Web of Science ®Google Scholar
• Jokar Arsanjani, J., Fibæk, C. S., & Vaz, E. (2018). Development of a cellular automata model using open source technologies for monitoring urbanisation in the global south: The case of Maputo, Mozambique. Habitat International, 71(November 2017), 38–48. https://doi.org/10.1016/j.habitatint.2017.11.003
   Google Scholar
• Kabaria, C. W., Molteni, F., Mandike, R., Chacky, F., Noor, A. M., Snow, R. W., & Linard, C. (2016). Mapping intra-urban malaria risk using high resolution satellite imagery: A case study of Dar es salaam. International Journal of Health Geographics, 15(1), 1–12. https://doi.org/10.1186/s12942-016-0051-y
   PubMedGoogle 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(3), 435–447. https://doi.org/10.1016/j.apgeog.2008.10.002
   Web of Science ®Google Scholar
• Kamusoko, C., & Gamba, J. (2015). Simulating urban growth using a random forest-cellular automata (RF-CA) model. ISPRS International Journal of Geo-Information, 4(2), 447–470. https://doi.org/10.3390/ijgi4020447
   Web of Science ®Google Scholar
• Kniveton, D., Smith, C., & Wood, S. (2011). Agent-based model simulations of future changes in migration flows for Burkina Faso. Global Environmental Change, 21(SUPPL. 1), S34–S40. https://doi.org/10.1016/j.gloenvcha.2011.09.006
   Google Scholar
• Lambin, E. F., & Meyfroidt, P. (2011). Global land use change, economic globalization, and the looming land scarcity. Proceedings of the National Academy of Sciences of the United States of America, 108(9), 3465–3472. https://doi.org/10.1073/pnas.1100480108
   PubMed Web of Science ®Google Scholar
• Lang, D. J., Wiek, A., Bergmann, M., Stauffacher, M., Martens, P., Moll, P., Swilling, M., & Thomas, C. J. (2012). Transdisciplinary research in sustainability science: Practice, principles, and challenges. Sustainability Science, 7(SUPPL. 1), 25–43. https://doi.org/10.1007/s11625-011-0149-x
   Web of Science ®Google Scholar
• Li, X., & Gong, P. (2016). Urban growth models: Progress and perspective. Science Bulletin, 61(21), 1637–1650. https://doi.org/10.1007/s11434-016-1111-1
   Web of Science ®Google Scholar
• Linard, C., Tatem, A. J., & Gilbert, M. (2013). Modelling spatial patterns of urban growth in africa. Applied Geography, 44, 23–32. https://doi.org/10.1016/j.apgeog.2013.07.009
   PubMed Web of Science ®Google Scholar
• Liu, Y., Batty, M., Wang, S., & Corcoran, J. (2019). Modelling urban change with cellular automata: Contemporary issues and future research directions. Progress in Human Geography, 45(1), 3–24. https://doi.org/10.1177/0309132519895305
   Web of Science ®Google Scholar
• Liu, Y., Li, L., Chen, L., Cheng, L., Zhou, X., Cui, Y., Li, H., Liu, W., & Chen, M. (2019). Urban growth simulation in different scenarios using the SLEUTH model: A case study of Hefei, East China. PloS ONE, 14(11), 1–22. https://doi.org/10.1371/journal.pone.0224998
   Web of Science ®Google Scholar
• Li, X., Zhou, Y., Eom, J., Yu, S., & Asrar, G. R. (2019). Projecting global urban area growth through 2100 based on Historical Time Series Data and future shared socioeconomic pathways. Earth’s Future, 7(4), 351–362. https://doi.org/10.1029/2019EF001152
   Web of Science ®Google Scholar
• Lusugga Kironde, J. M. (2006). The regulatory framework, unplanned development and urban poverty: Findings from Dar es Salaam, Tanzania. Land Use Policy, 23(4), 460–472. https://doi.org/10.1016/j.landusepol.2005.07.004
   Web of Science ®Google Scholar
• Lüthi, C., McConville, J., & Kvarnström, E. (2010). Community-based approaches for addressing the urban sanitation challenges. International Journal of Urban Sustainable Development, 1(1–2), 49–63. https://doi.org/10.1080/19463131003654764
   Google Scholar
• Mahmoud, M. I., Duker, A., Conrad, C., Thiel, M., & Ahmad, H. S. (2016). Analysis of settlement expansion and urban growth modelling using geoinformation for assessing potential impacts of urbanization on climate in Abuja City, Nigeria. Remote Sensing, 8(3). https://doi.org/10.3390/rs8030220
   Web of Science ®Google Scholar
• Marondedze, A. K., & Schütt, B. (2019). Dynamics of land use and land cover changes in Harare, Zimbabwe: A case study on the linkage between drivers and the axis of urban expansion. Land, 8(10), 155. https://doi.org/10.3390/land8100155
   Web of Science ®Google Scholar
• Mauck, B. A., & Warburton, M. (2014). Mapping areas of future urban growth in the mgeni catchment. Journal of Environmental Planning and Management, 57(6), 920–936. https://doi.org/10.1080/09640568.2013.775062
   Web of Science ®Google Scholar
• Mauck, B. A., Warburton, M., Mubea, K., Goetzke, R., Menz, G., Chaudhuri, G., & Clarke, K. C. (2013). Simulating urban growth in Nakuru (Kenya) using java-based modelling platform XULU. Proceedings - UKSim-AMSS 7th European Modelling Symposium on Computer Modelling and Simulation, EMS 2013, 57(6), 103–108. https://doi.org/10.1109/EMS.2013.18
   Google Scholar
• Moein, M., Asgarian, A., Sakieh, Y., Soffianian, A., So, A., & Soffianian, A. (2018). Scenario-based analysis of land-use competition in central Iran: Finding the trade-off between urban growth patterns and agricultural productivity. Sustainable Cities and Society, 39(September 2017), 557–567. https://doi.org/10.1016/j.scs.2018.03.014
   Google Scholar
• Mohamed, A., & Worku, H. (2020). Simulating urban land use and cover dynamics using cellular automata and Markov chain approach in Addis Ababa and the surrounding. Urban Climate, 31, 100545. October 2019. https://doi.org/10.1016/j.uclim.2019.100545.
   Web of Science ®Google Scholar
• Mundia, C. N., & Murayama, Y. (2010). Modeling spatial processes of urban growth in African cities: A case study of Nairobi City. Urban Geography, 31(2), 259–272. https://doi.org/10.2747/0272-3638.31.2.259
   Web of Science ®Google Scholar
• Musa, S. I., Hashim, M., & Reba, M. N. M. (2017). A review of geospatial-based urban growth models and modelling initiatives. Geocarto International, 32(8), 813–833. https://doi.org/10.1080/10106049.2016.1213891
   Web of Science ®Google Scholar
• Musa, S. I., Hashim, M., & Reba, M. N. M. (2019). Geospatial modelling of urban growth for sustainable development in the Niger Delta Region, Nigeria. International Journal of Remote Sensing, 40(8), 3076–3104. https://doi.org/10.1080/01431161.2018.1539271
   Web of Science ®Google Scholar
• Mushore, T. D., Odindi, J., Dube, T., &, and Mutanga, O. (2017). Prediction of future urban surface temperatures using medium resolution satellite data in Harare metropolitan city, Zimbabwe. Building and Environment, 122, 397–410. https://doi.org/10.1016/j.buildenv.2017.06.033
   Web of Science ®Google Scholar
• Nagendra, H., Bai, X., Brondizio, E. S., & Lwasa, S. (2018). The urban south and the predicament of global sustainability. Nature Sustainability, 1(July), 341–349. https://doi.org/10.1038/s41893-018-0101-5
   Web of Science ®Google Scholar
• Naghibi, F., Delavar, M. R., & Pijanowski, B. (2016). Urban growth modeling using cellular automata with multi-temporal remote sensing images calibrated by the artificial bee colony optimization algorithm. Sensors (Switzerland), 16(12), 2122. https://doi.org/10.3390/s16122122
   PubMed Web of Science ®Google Scholar
• Osman, T., Shaw, D., & Kenawy, E. (2018). An integrated land use change model to simulate and predict the future of Greater Cairo metropolitan region. Journal of Land Use Science, 13(6), 565–584. https://doi.org/10.1080/1747423X.2019.1581849
   Web of Science ®Google Scholar
• Pontius, G. R., & Malanson, J. (2005). Comparison of the structure and accuracy of two land change models. International Journal of Geographical Information Science, 19(2), 243–265. https://doi.org/10.1080/13658810410001713434
   Web of Science ®Google Scholar
• Rabehi, W., Guerfi, M., Mahi, H., & Rojas-Garcia, E. (2019). Spatiotemporal monitoring of coastal urbanization dynamics: Case study of Algiers’ bay, Algeria. The Journal of the Indian Society of Remote Sensing, 47(11), 1917–1936. https://doi.org/10.1007/s12524-019-01037-y
   Web of Science ®Google Scholar
• Radwan, T. M., Blackburn, G. A., Whyatt, J. D., & Atkinson, P. M. (2019). Dramatic loss of agricultural land due to urban expansion Threatens Food Security in the Nile Delta, Egypt. Remote Sensing, 11(3), 332. https://doi.org/10.3390/rs11030332
   Web of Science ®Google Scholar
• Rimal, B., Zhang, L., Keshtkar, H., Wang, N., & Lin, Y. (2017). Monitoring and Modeling of Spatiotemporal Urban Expansion and land-Use/Land-cover change using integrated Markov chain cellular automata Model. ISPRS International Journal of Geo-Information, 6(9), 288. https://doi.org/10.3390/ijgi6090288
   Web of Science ®Google Scholar
• Robson, J. S., Ayad, H. M., Wasfi, R. A., & El-Geneidy, A. M. (2012). Spatial disintegration and arable land security in Egypt: A study of small- and moderate-sized urban areas. Habitat International, 36(2), 253–260. https://doi.org/10.1016/j.habitatint.2011.10.001
   Web of Science ®Google Scholar
• Saghir, J., & Santoro, J. (2018). Urbanization in Sub-Saharan Africa. Meeting challenges by bridging stakeholders. Center for Strategic and International Studies.
   Google Scholar
• Santé, I., García, A. M., Miranda, D., & Crecente, R. (2010). Cellular automata models for the simulation of real-world urban processes: A review and analysis. Landscape and Urban Planning, 96(2), 108–122. https://doi.org/10.1016/j.landurbplan.2010.03.001
   Web of Science ®Google Scholar
• Schwarz, N., Flacke, J., & Sliuzas, R. (2016). Modelling the impacts of urban upgrading on population dynamics. Environmental Modelling and Software, 78(2), 150–162. https://doi.org/10.1016/j.envsoft.2015.12.009
   Google Scholar
• Schweitzer, F. (2006). A growing urban problem. Nature, 441(7095), 815–815. https://doi.org/10.1038/441815a
   Google Scholar
• Shade, C., & Kremer, P. (2019). Predicting land use changes in Philadelphia following green infrastructure policies. Land, 8(2), 28. https://doi.org/10.3390/land8020028
   Web of Science ®Google Scholar
• Shafizadeh Moghadam, H., & Helbich, M. (2013). Spatiotemporal urbanization processes in the megacity of Mumbai, India: A Markov chains-cellular automata urban growth model. Applied Geography, 40, 140–149. https://doi.org/10.1016/j.apgeog.2013.01.009
   Web of Science ®Google Scholar
• Shimoni, M., Lopez, J., Forget, Y., Wolff, E., Michellier, C., Grippa, T., Linard, C., & Gilbert, M. (2015). An urban expansion model for African cities using fused multi temporal optical and SAR data. International Geoscience and Remote Sensing Symposium (IGARSS) 2015-Novem, 1159–1162. https://doi.org/10.1109/IGARSS.2015.7325977
   Google Scholar
• Shoko, M., & Smit, J. (2013). Use of Agent Based Modelling in the Dynamics of Slum Growth. South African Journal of Geomatics, 2(1), 54–67.
   Google Scholar
• Simwanda, M., & Murayama, Y. (2018). Spatiotemporal patterns of urban land use change in the rapidly growing city of Lusaka, Zambia: Implications for sustainable urban development. Sustainable Cities and Society, 39(February), 262–274. https://doi.org/10.1016/j.scs.2018.01.039
   Google Scholar
• Singh, S. K., Mustak, S., Srivastava, P. K., Szabó, S., & Islam, T. (2015). Predicting spatial and decadal LULC changes through cellular automata Markov chain models using earth observation datasets and geo-information. Environmental Processes, 2(1), 61–78. https://doi.org/10.1007/s40710-015-0062-x
   Google Scholar
• Tarawally, M., Wenbo, X., Weiming, H., Mushore, T. D., & Kursah, M. B. (2019). Land use/land cover change evaluation using land change modeller: A comparative analysis between two main cities in Sierra Leone. Remote Sensing Applications: Society & Environment, 16(September), 100262. https://doi.org/10.1016/j.rsase.2019.100262
   Google Scholar
• Tewolde, M. G., & Cabral, P. (2011). Urban sprawl analysis and modeling in Asmara, Eritrea. Remote Sensing, 3(10), 2148–2165. https://doi.org/10.3390/rs3102148
   Web of Science ®Google Scholar
• Thite, M. (2011). Smart cities: Implications of urban planning for human resource development. Human Resource Development International, 14(5), 623–631. https://doi.org/10.1080/13678868.2011.618349
   Google Scholar
• Torrens, P. M. (2003). Automata-based models of urban systems. Advanced Spatial Analysis, 61–79.
   Google Scholar
• Triantakonstantis, D., & Mountrakis, G. (2012). Urban growth prediction: A review of computational models and human perceptions. Journal of Geographic Information System, 04(6), 555–587. https://doi.org/10.4236/jgis.2012.46060
   Google Scholar
• Turok, I., & McGranahan, G. (2013). Urbanization and economic growth: The arguments and evidence for Africa and Asia. Environment and Urbanization, 25(2), 465–482. https://doi.org/10.1177/0956247813490908
   Web of Science ®Google Scholar
• UN-Habitat. (2016). Urbanization and Development: Emerging Futures. In UN Habitat World Cities Report 2016.
   Google Scholar
• United Nations. (2016). The World’s Cities in 2016: Data booklet (Report No. ST/ESA/ SER. A/392). Department of Economic and Social Affairs, Population Division.
   Google Scholar
• United Nations. (2018). World urbanization prospects: The 2018 revision. Department of Economic and Social Affairs.
   Google Scholar
• Vermeiren, K., Adiyia, B., Loopmans, M., Tumwine, F. R., & Van Rompaey, A. (2013). Will urban farming survive the growth of African cities: A case-study in Kampala (Uganda)? Land Use Policy, 35, 40–49. https://doi.org/10.1016/j.landusepol.2013.04.012
   Web of Science ®Google Scholar
• Vermeiren, K., Vanmaercke, M., Beckers, J., & Van Rompaey, A. (2016). ASSURE: A model for the simulation of urban expansion and intra-urban social segregation. International Journal of Geographical Information Science, 30(12), 2377–2400. https://doi.org/10.1080/13658816.2016.1177641
   Web of Science ®Google Scholar
• Wahyudi, A., & Liu, Y. (2016). Cellular automata for urban growth modelling. International Review for Spatial Planning and Sustainable Development, 4(2), 60–75. https://doi.org/10.14246/irspsd.4.2_60
   Google Scholar
• Wang, X., Van Dam, K. H., Triantafyllidis, C., Koppelaar, R. H. E. M., & Shah, N. (2017). Water and Energy Systems in sustainable city development: A case of Sub-saharan Africa. Procedia Engineering, 198(September 2016), 948–957. https://doi.org/10.1016/j.proeng.2017.07.140
   Google Scholar
• White, R., & Engelen, G. (1993). Cellular automata and fractal urban form: A cellular modelling approach to the evolution of urban land-use patterns. Environment & Planning A: Economy & Space, 25(8), 1175–1199. https://doi.org/10.1068/a251175
   Web of Science ®Google Scholar
• Xu, G., Dong, T., Cobbinah, P. B., Jiao, L., Sumari, N. S., Chai, B., & Liu, Y. (2019). Urban expansion and form changes across African cities with a global outlook: Spatiotemporal analysis of urban land densities. Journal of Cleaner Production, 224(June), 802–810. https://doi.org/10.1016/j.jclepro.2019.03.276
   Google Scholar