Understanding the spatiotemporal dynamics of urbanization and predicting future growth is now essential for sustainable urban planning and policy making. This study explores future urban expansion in the rapidly growing region of eastern lowland Nepal. We used the hybrid cellular automata-Markov (CA-Markov) model, which utilizes historical land use and land cover (LULC) maps and several biophysical change driver variables to predict urban expansion for the years 2026 and 2036. Transitional area matrices were generated based on historical LULC data from 1996 to 2006, from 2006 to 2016, and from 1996 to 2016. The approach was validated by cross comparing the actual and simulated maps for 2016. Evaluation gave satisfactory values of Kno (0.89), Kstandard (0.84), and Klocation (0.89) which verifies the accuracy of the model. Hence, the CA-Markov model was utilized to simulate the LULC map for the years 2026 and 2036. The study area experienced rapid peri/urban expansion and sharp decline in area of cultivated land during 1989–2016. Built-up area increased by 110.90 km2 over a period of 27 years at the loss of 87.59 km2 cultivated land. Simulation analysis indicates that urban expansion will continue with urban cover increasing to 230 km2 (8.95%) and 318.51 km2 (12.45%) by 2026 and 2036, respectively, with corresponding declines in cultivated land to 1453.83 km2 (56.86%) and 1374.93 km2 (53.77%) for the same years. The alarming increase in urban areas coupled with loss of cultivated land will have negative implications for food security and environmental equilibrium in the region.
This is a preview of subscription content, log in to check access.
Buy single article
Instant access to the full article PDF.
Price includes VAT for USA
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
This is the net price. Taxes to be calculated in checkout.
Al-Quraishi, A. (2013). Sand dunes monitoring using remote sensing and GIS techniques for some sites in Iraq (Vol. 8762). https://doi.org/10.1117/12.2019735.
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, 838. https://doi.org/10.3390/rs8100838.
Araya, Y. H., & Cabral, P. (2010). Analysis and modeling of urban land cover change in Setúbal and Sesimbra, Portugal. Remote Sensing, 2, 1549–1563. https://doi.org/10.3390/rs2061549.
Asma, G., Cyril De, R., & Herman, A. (2017). Urban development modelling: a survey. In F. Sami & M. Khaoula (Eds.), Handbook of research on geographic information systems applications and advancements (pp. 96–124). Hershey: IGI Global. https://doi.org/10.4018/978-1-5225-0937-0.ch004.
Batty, M. X. Y. (2005). Urban growth using cellular automata models (First ed.). New York Street Redlands: ESRI Press.
Bhattarai, K., & Conway, D. (2010). Urban vulnerabilities in the Kathmandu Valley, Nepal: visualizations of human/hazard interactions. Journal of Geographic Information System, 02(02), 20. https://doi.org/10.4236/jgis.2010.22012.
Campbell, J. B. (1996). Introduction to remote sensing. New York: The Guilford Press.
CBS. (2014). Population monograph of Nepal. Kathmandu: National Planning Commission Secretariat, Central Bureau of Statistics (CBS).
Cholhyok, K., Zhang, Y., Paudel, B., Liu, L., Wang, Z., & Li, R. (2018). Exploring the factors driving changes in farmland within the Tumen/Tuman River Basin (Vol. 7). https://doi.org/10.3390/ijgi7090352.
Clarke, K. C. (2018). Land use change modeling with SLEUTH: improving calibration with a genetic algorithm. In M. T. Camacho Olmedo, M. Paegelow, J.-F. Mas, & F. Escobar (Eds.), Geomatic approaches for modeling land change scenarios (pp. 139–161). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-60801-3_8.
Corner, R. J., Dewan, A. M., & Chakma, S. (2014). Monitoring and prediction of land-use and land-cover (LULC) change. In A. Dewan & R. Corner (Eds.), Dhaka megacity: geospatial perspectives on urbanisation, environment and health (pp. 75–97). Dordrecht: Springer Netherlands. https://doi.org/10.1007/978-94-007-6735-5_5.
Dewan AMCRJ (2013) Spatiotemporal analysis of urban growth, sprawl and structure. In Dhaka megacity, geospatial perspectives on urbanization, environment and health.
Dewan, A. M., & Yamaguchi, Y. (2009). Land use and land cover change in Greater Dhaka, Bangladesh: using remote sensing to promote sustainable urbanization. Applied Geography, 29, 390–401. https://doi.org/10.1016/j.apgeog.2008.12.005.
Dewan, A. M., Kabir, M. H., Nahar, K., & Rahman, M. Z. (2012). Urbanisation and environmental degradation in Dhaka Metropolitan Area of Bangladesh. International Journal of Environment and Sustainable Development, 11, 118–147. https://doi.org/10.1504/ijesd.2012.049178.
FAO. (2018). The state of food security and nutrition in the world 2018.building climate resilience for food security and nutrition. Rome: Food and Agriculture Organization (FAO) of the United Nations.
Feng, Y., Lu, D., Moran, E., Dutra, L., Calvi, M., & de Oliveira, M. (2017). Examining spatial distribution and dynamic change of urban land covers in the Brazilian Amazon using multitemporal multisensor high spatial resolution satellite imagery. Remote Sensing, 9, 381.
Fisk, D. (2012). The urban challenge. Science, 336, 1396–1397. https://doi.org/10.1126/science.1223952.
GoN. (2017). Administrative map of Nepal. Government of Nepal (GoN). Kathmandu: Srvey Department, Min Bhawan.
Güneralp, B., & Seto, K. C. (2013). Futures of global urban expansion: uncertainties and implications for biodiversity conservation. Environmental Research Letters, 8, 014025. https://doi.org/10.1088/1748-9326/8/1/014025.
Han, Y., & Jia, H. (2017). Simulating the spatial dynamics of urban growth with an integrated modeling approach: a case study of Foshan, China. Ecological Modelling, 353, 107–116. https://doi.org/10.1016/j.ecolmodel.2016.04.005.
Han, J., Hayashi, Y., Cao, X., & Imura, H. (2009). Application of an integrated system dynamics and cellular automata model for urban growth assessment: a case study of Shanghai, China. Landscape and Urban Planning, 91, 133–141. https://doi.org/10.1016/j.landurbplan.2008.12.002.
Jacoby, K. (2001). World ecological degradation: accumulation, urbanization, and deforestation, 3000 B.C–2000 A.D History: reviews of new books (Vol. 30, pp. 38–38). https://doi.org/10.1080/03612759.2001.10525983.
Jiao, L. (2015). Urban land density function: a new method to characterize urban expansion. Landscape and Urban Planning, 139, 26–39. https://doi.org/10.1016/j.landurbplan.2015.02.017.
Jokar Arsanjani, J., Helbich, M., Kainz, W., & Darvishi Boloorani, A. (2013). 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. https://doi.org/10.1016/j.jag.2011.12.014.
Julius Oluranti, O. (2018). Geospatial analysis of land cover change and urban sprawl trend in Akure Region, Nigeria (Vol. 3). https://doi.org/10.15406/mojes.2018.03.00062.
Kaplan, D. H., Wheeler, J. O., Holloway, S. R., & Hodler, T. W. (2004). Urban geography. Wiley.
Keshtkar, H., & Voigt, W. (2015). A spatiotemporal analysis of landscape change using an integrated Markov chain and cellular automata models. Modeling Earth Systems and Environment, 2. https://doi.org/10.1007/s40808-015-0068-4.
Keshtkar, H., & Voigt, W. (2016). Potential impacts of climate and landscape fragmentation changes on plant distributions: coupling multi-temporal satellite imagery with GIS-based cellular automata model. Ecological Informatics, 32, 145–155. https://doi.org/10.1016/j.ecoinf.2016.02.002.
Keshtkar, H., Voigt, W., & Alizadeh, E. (2017). Land-cover classification and analysis of change using machine-learning classifiers and multi-temporal remote sensing imagery. Arabian Journal of Geosciences, 10, 1–15. https://doi.org/10.1007/s12517-017-2899-y.
Khudair, B., Sameer Sadeq, N., & Sameer mahmoud, R. (2018). Determining and predicting the water demand dynamic system model mapping urban crawling and monitoring using remote sensing techniques and GIS (Vol. 24). https://doi.org/10.31026/j.eng.2018.06.08.
Li, S., & Ma, Y. (2014). Urbanization, economic development and environmental change. sustainability, 6, 5143–5161. https://doi.org/10.3390/su6085143.
Li, X., Zhou, W., & Ouyang, Z. (2013). Forty years of urban expansion in Beijing: what is the relative importance of physical, socioeconomic, and neighborhood factors? Applied Geography, 38, 1–10. https://doi.org/10.1016/j.apgeog.2012.11.004.
Liu Z, He C, Wu J (2016) General spatiotemporal patterns of urbanization: an examination of 16 world cities sustainability 8:41 https://doi.org/10.3390/su8010041.
Markus, S. (2017). Spatial and spatiotemporal data types as a foundation for representing space-time data in GIS. In F. Sami & M. Khaoula (Eds.), Handbook of research on geographic information systems applications and advancements (pp. 1–28). Hershey: IGI Global. https://doi.org/10.4018/978-1-5225-0937-0.ch001.
Meiyappan, P., Roy, P. S., Sharma, Y., Ramachandran, R. M., Joshi, P. K., DeFries, R. S., & Jain, A. K. (2017). Dynamics and determinants of land change in India: integrating satellite data with village socioeconomics. Regional Environmental Change, 17, 753–766. https://doi.org/10.1007/s10113-016-1068-2.
MoFALD. (2017). Local level reconstruction report. Kathmandu: Ministry of Federal Affairs and Local Development (MoFALD), Nepal Government.
MOUD. (2015). National urban development strategy (NUDS) 2015. Kathmandu: Government of Nepal, Ministry of Urban Development.
Mountjoy, A. B. (1978). Urbanisation in the third world. In A. B. Mountjoy (Ed.), The third world: problems and perspectives (pp. 102–111). London: Macmillan Education UK. https://doi.org/10.1007/978-1-349-16030-3_10.
Muzzini, E., & Gabriela, A. (2013). Urban growth and spatial transition in Nepal (p. 20433). Washington DC: The World Bank, 1818 H Street NW.
Nagendra, H., Bai, X., Brondizio, E. S., & Lwasa, S. (2018). The urban south and the predicament of global sustainability. Nature Sustainability, 1, 341–349. https://doi.org/10.1038/s41893-018-0101-5.
Ouyang, Z., Fan, P., & Chen, J. (2016). Urban built-up areas in transitional economies of Southeast Asia: spatial extent and dynamics. Remote Sensing, 8, 819. https://doi.org/10.3390/rs8100819.
Paudel, B., Gao, J., Zhang, Y., Wu, X., Li, S., & Yan, J. (2016). Changes in cropland status and their driving factors in the Koshi River basin of the Central Himalayas, Nepal. Sustainability, 8, 933.
Pires, N. L., Muniz, D. H., Kisaka, T. B., Simplicio Nde, C., Bortoluzzi, L., Lima, J. E., & Oliveira-Filho, E. C. (2015). Impacts of the urbanization process on water quality of Brazilian savanna rivers: the case of Preto River in Formosa, Goias State, Brazil. International Journal of Environmental Research and Public Health, 12, 10671–10686. https://doi.org/10.3390/ijerph120910671.
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, 4407–4429. https://doi.org/10.1080/01431161.2011.552923.
Pradhan, P., & Perera, R. (2005). Urban growth and its impact on the livelihoods of Kathmandu Valley. In Nepal.
Rahman, M. (2016). Detection of land use/land cover changes and urban sprawl in Al-Khobar, Saudi Arabia: an analysis of multi-temporal remote sensing data. ISPRS International Journal of Geo-Information, 5, 15. https://doi.org/10.3390/ijgi5020015.
Rai, R., Zhang, Y., Paudel, B., Acharya, B., & Basnet, L. (2018). Land use and land cover dynamics and assessing the ecosystem service values in the trans-boundary Gandaki River Basin. Central Himalayas Sustainability, 10, 3052.
Rijal, S., Rimal, B., & Sloan, S. (2018). Flood hazard mapping of a rapidly urbanizing city in the foothills (Birendranagar, Surkhet) of Nepal. Land, 7, 60. https://doi.org/10.3390/land7020060.
Rimal, B., Zhang, L., Fu, D., Kunwar, R., & Zhai, Y. (2017a). Monitoring urban growth and the Nepal earthquake 2015 for sustainability of Kathmandu Valley, Nepal. Land, 6, 1-23. https://doi.org/10.3390/land6020042.
Rimal, B., Zhang, L., Keshtkar, H., Wang, N., & Lin, Y. (2017b). 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, 1–21. https://doi.org/10.3390/ijgi6090288.
Rimal, B., Zhang, L., Keshtkar, H., Haack, B., Rijal, S., & Zhang, P. (2018a). Land use/land cover dynamics and modeling of urban land expansion by the integration of cellular automata and Markov chain. ISPRS International Journal of Geo-Information, 7, 154. https://doi.org/10.3390/ijgi7040154.
Rimal, B., Zhang, L., Keshtkar, H., Sun, X., & Rijal, S. (2018b). Quantifying the spatiotemporal pattern of urban expansion and hazard and risk area identification in the Kaski District of Nepal. Land, 7, 37. https://doi.org/10.3390/land7010037.
Rimal, B., Zhang, L., & Rijal, S. (2018c). Crop cycles and crop land classification in Nepal using MODIS NDVI. Remote Sensing in Earth Systems Sciences, 1, 14–28. https://doi.org/10.1007/s41976-018-0002-4.
Rimal, B., Zhang, L., Stork, N., Sloan, S., & Rijal, S. (2018d). Urban expansion occurred at the expense of agricultural lands in the Tarai region of Nepal from 1989 to 2016. Sustainability, 10, 1341. https://doi.org/10.3390/su10051341.
Rodrigues, H., & Soares-Filho, B. (2018). A short presentation of Dinamica EGO. In M. T. Camacho Olmedo, M. Paegelow, J.-F. Mas, & F. Escobar (Eds.), Geomatic approaches for modeling land change scenarios (pp. 493–498). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-60801-3_35.
Sahana, M., Hong, H., & Sajjad, H. (2018). Analyzing urban spatial patterns and trend of urban growth using urban sprawl matrix: a study on Kolkata urban agglomeration, India. Science of the Total Environment, 628-629, 1557–1566. https://doi.org/10.1016/j.scitotenv.2018.02.170.
Seto, K. C., Fragkias, M., Guneralp. B., & Reilly, M. K. (2011). A meta-analysis of global urban land expansion. PLoS One, 6, e23777. https://doi.org/10.1371/journal.pone.0023777.g001.
Seto, K. C., Guneralp, B., & Hutyra, L. R. (2012). Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools. Proceedings of the National Academy of Sciences of the United States of America, 109, 16083–16088. https://doi.org/10.1073/pnas.1211658109.
Sexton, J. O., Song, X.-P., Huang, C., Channan, S., Baker, M. E., & Townshend, J. R. (2013). Urban growth of the Washington, D.C.–Baltimore, MD metropolitan region from 1984 to 2010 by annual, Landsat-based estimates of impervious cover. Remote Sensing of Environment, 129, 42–53. https://doi.org/10.1016/j.rse.2012.10.025.
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.
Sharma, R., Rimal, B., Stork, N., Baral, H., & Dhakal, M. (2018). Spatial assessment of the potential impact of infrastructure development on biodiversity conservation in lowland Nepal. ISPRS International Journal of Geo-Information, 7, 1-13. https://doi.org/10.3390/ijgi7090365.
Sharma R, Rimal B, Paudyal K, Baral H, Acharya RP, Ranpal S, Kandel P (2019) Impact of land cover change on ecosystem services in a tropical forested landscape Resources, 8, 1-13. https://doi.org/10.3390/resources8010018.
Shi, M., Xie, Y., & Cao, Q. (2016). Spatiotemporal changes in rural settlement land and rural population in the Middle Basin of the Heihe River, China. Sustainability, 8, 614. https://doi.org/10.3390/su8070614.
Sleeter, B. M., Wood, N. J., Soulard, C. E., & Wilson, T. S. (2017). Projecting community changes in hazard exposure to support long-term risk reduction: a case study of tsunami hazards in the U.S. Pacific Northwest. International Journal of Disaster Risk Reduction, 22, 10–22. https://doi.org/10.1016/j.ijdrr.2017.02.015.
Thapa, R. B., & Murayama, Y. (2010). Drivers of urban growth in the Kathmandu valley, Nepal: examining the efficacy of the analytic hierarchy process. Applied Geography, 30, 70–83. https://doi.org/10.1016/j.apgeog.2009.10.002.
Thapa, R. B., & Murayama, Y. (2012). Scenario based urban growth allocation in Kathmandu Valley, Nepal. Landscape and Urban Planning, 105, 140–148. https://doi.org/10.1016/j.landurbplan.2011.12.007.
Theobald, D. (2005). Landscape patterns of exurban growth in the USA from 1980 to 2020. Ecology and Society, 10.
Traore, A., Mawenda, J., & Komba, A. (2018). Land-cover change analysis and simulation in Conakry (Guinea), using hybrid cellular-automata and Markov model (Vol. 2). https://doi.org/10.3390/urbansci2020039.
Umar, B., & Indo, B. (2018). Revisiting urban theories: their impacts on the developing world’s urbanization. In B. Umar & B. Indo (Eds.), Urbanization and its impact on socio-economic growth in developing regions (pp. 1–22). Hershey, PA, USA: IGI Global. https://doi.org/10.4018/978-1-5225-2659-9.ch001.
UNESCAP. (2015). The state of Asian and Pacific Cities 2015. Urban transformations shifting from quantity to quality. United Nations Economic and Social Commission for Asia and the Pacific.
UNDESA. (2014). World urbanization prospects, the 2014 revision. New York: United Nation, United Nations, Department of Economic and Social Affairs, Population Division.
UNDESA. (2017). World population prospects the 2017 revision. New York: United Nations,, United Nations, Department of Economic and Social Affairs, Population Division.
UNDESA. (2018). World urbanization prospects: the 2018 revision. United Nation Development of Economic and Social Affairs, United Nation.
Verburg, P. H. V. A. (2004). Projecting land use transitions at forest fringes in the Philippines at two spatial scales. Landscape Ecology, 19, 77–98.
Verburg, P. H., Ritsema van Eck, J. R., Nijs, d T C M., Dijst, M. J., & Schot, P. (2004). Determinants of land-use change patterns in the Netherlands. Environment and Planning B - Planning and Design, 31, 125–150.
Verburg, P. H., Crossman, N., Ellis, E. C., Heinimann, A., Hostert, P., Mertz, O., Nagendra, H., Sikor, T., Erb, K. H., Golubiewski, N., Grau, R., Grove, M., Konaté, S., Meyfroidt, P., Parker, D. C., Chowdhury, R. R., Shibata, H., Thomson, A., & Zhen, L. (2015). Land system science and sustainable development of the earth system: a global land project perspective. Anthropocene, 12, 29–41. https://doi.org/10.1016/j.ancene.2015.09.004.
Wang, R., Derdouri, A., & Murayama, Y. (2018a). Spatiotemporal simulation of future land use/cover change scenarios in the Tokyo metropolitan area. Sustainability, 10, 2056.
Wang, R., Hou, H., & Murayama, Y. (2018b). Scenario-based simulation of Tianjin City using a cellular automata–Markov model (Vol. 10). https://doi.org/10.3390/su10082633.
Wu, J., Jenerette, G. D., Buyantuyev, A., & Redman, C. L. (2011). Quantifying spatiotemporal patterns of urbanization: the case of the two fastest growing metropolitan regions in the United States. Ecological Complexity, 8, 1–8. https://doi.org/10.1016/j.ecocom.2010.03.002.
Wu, H., Sun, Y., Shi, W., Chen, X., & Fu, D. (2013). Examining the satellite-detected urban land use spatial patterns using multidimensional fractal dimension indices. Remote Sensing, 5, 5152–5172. https://doi.org/10.3390/rs5105152.
Yadav SK, Borana SL, S.K. Parihara (2018) Mapping and assessment of LU-LC features of the Jodhpur city using geoinformatic techniques.
Yan, Y., Zhang, C., Hu, Y., & Kuang, W. (2015). Urban land-cover change and its impact on the ecosystem carbon storage in a dryland City. Remote Sensing, 8, 6. https://doi.org/10.3390/rs8010006.
Yin, J., Yin, Z., Zhong, H., Xu, S., Hu, X., Wang, J., & Wu, J. (2011). Monitoring urban expansion and land use/land cover changes of Shanghai metropolitan area during the transitional economy (1979-2009) in China. Environmental Monitoring and Assessment, 177, 609–621. https://doi.org/10.1007/s10661-010-1660-8.
Zeba, A. N., Yameogo, M. T., Tougouma, S. J., Kassie, D., & Fournet, F. (2017). Can urbanization, social and spatial disparities help to understand the rise of cardiometabolic risk factors in Bobo-Dioulasso? A study in a secondary city of Burkina Faso, West Africa. International Journal of Environmental Research and Public Health, 14. https://doi.org/10.3390/ijerph14040378.
Zhang, X. Q. (2016). The trends, promises and challenges of urbanisation in the world. Habitat International, 54, 241–252. https://doi.org/10.1016/j.habitatint.2015.11.018.
Zhang, Z., Li, N., Wang, X., Liu, F., & Yang, L. (2016). A comparative study of urban expansion in Beijing, Tianjin and Tangshan from the 1970s to 2013. Remote Sensing, 8, 496.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Rimal, B., Keshtkar, H., Sharma, R. et al. Simulating urban expansion in a rapidly changing landscape in eastern Tarai, Nepal. Environ Monit Assess 191, 255 (2019). https://doi.org/10.1007/s10661-019-7389-0
- Urban expansion
- Spatial models
- Developing countries
- Food security