Tracking Urban Sprawl: A Systematic Review and Bibliometric Analysis of Spatio-Temporal Patterns Using Remote Sensing and GIS
Published 2024-09-07
Keywords
- bibliometric,
- geographic information system,
- landsat,
- remote sensing,
- urban sprawl
- systematic literature review ...More
How to Cite
Copyright (c) 2024 Mohammad Raditia Pradana, Muhammad Dimyati
This work is licensed under a Creative Commons Attribution 4.0 International License.
Accepted 2024-09-06
Published 2024-09-07
Abstract
The urban sprawl phenomenon refers to the expansion of urban areas driven by high population growth and migration. A spatio-temporal approach is indispensable in urban sprawl research. Monitoring and evaluating urban sprawl in a region is crucial for controlling drastic environmental changes. Integrated Remote Sensing (RS) and Geographic Information System (GIS) technologies can serve as essential tools for this purpose. The aim of this systematic literature review paper is to gather information on the latest data, methods, and findings to be considered in future urban sprawl research. The PRISMA method was employed, involving filtering from the Scopus database, resulting in 30 papers selected for an in-depth review to address the objectives of this paper. Landsat data remains the preferred choice for monitoring changes due to its extensive historical archive compared to other data sources. Landscape metrics represent a more advanced method com-pared to conventional change detection in quantifying urban sprawl. Other indices and quantifiers are also used to support the quantification of urban sprawl. Two perspectives exist in selecting the study's temporal intervals: consistent and inconsistent, which are adjusted based on the natural characteristics of "change," namely "abrupt" and "gradual." Suggestions for future research include using data with detailed spatial resolution and narrow study intervals while considering the patterns of urban sprawl formation.
Highlights:
- Spatio-temporal approach: Vital for understanding urban sprawl dynamics.
- Remote Sensing and GIS integration: Key for monitoring and controlling sprawl.
- Indices and landscape metrics: Crucial tools for quantifying sprawl change.
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References
- Ahmed, S. (2018). Assessment of urban heat islands and impact of climate change on socioeconomic over Suez Governorate using remote sens-ing and GIS techniques. Egyptian Journal of Remote Sensing and Space Science, 21(1), 15–25. https://doi.org/10.1016/j.ejrs.2017.08.001
- Akubia, J. E. K., & Bruns, A. (2019). Unravelling the frontiers of urban growth: Spatio-Temporal dynamics of land-use change and urban expan-sion in greater Accra metropolitan area, Ghana. Land, 8(9), 1–23. https://doi.org/10.3390/land8090131
- Al-Dousari, A. E., Mishra, A., & Singh, S. (2023). Land use land cover change detection and urban sprawl prediction for Kuwait metropolitan region, using multi-layer perceptron neural networks (MLPNN). Egyptian Journal of Remote Sensing and Space Science, 26(2), 381–392. https://doi.org/10.1016/j.ejrs.2023.05.003
- Al-shalabi, M., Billa, L., Pradhan, B., Mansor, S., & Al-Sharif, A. A. A. (2013). Modelling urban growth evolution and land-use changes using GIS based cellular automata and SLEUTH models: the case of Sana’a metropolitan city, Yemen. Environmental Earth Sciences, 70(1), 425–437. https://doi.org/10.1007/s12665-012-2137-6
- Alsharif, A. A. A., & Pradhan, B. (2014). Urban Sprawl Analysis of Tripoli Metropolitan City (Libya) Using Remote Sensing Data and Multivariate Logistic Regression Model. Journal of the Indian Society of Remote Sensing, 42(1), 149–163. https://doi.org/10.1007/s12524-013-0299-7
- Alzahrani, A., Aldossary, N., & Alghamdi, J. (2024). Observing the dynamics of urban growth of Al-Baha City using GIS (2006–2021). Alexandria Engineering Journal, 95, 114–131. https://doi.org/10.1016/j.aej.2024.03.096
- Anand, A., & Deb, C. (2024). The potential of remote sensing and GIS in urban building energy modelling. Energy and Built Environment, 5(6), 957–969. https://doi.org/10.1016/j.enbenv.2023.07.008
- Aslam, R. W., Shu, H., & Yaseen, A. (2023). Monitoring the population change and urban growth of four major Pakistan cities through spatial analysis of open source data. Annals of GIS, 29(3), 355–367. https://doi.org/10.1080/19475683.2023.2166989
- Aurora, R. M., & Furuya, K. (2023). Spatiotemporal Analysis of Urban Sprawl and Ecological Quality Study Case: Chiba Prefecture, Japan. Land, 12(11). https://doi.org/10.3390/land12112013
- Balandi, J. B., To Hulu, J. P. P. M., Sambieni, K. R., Sikuzani, Y. U., Bastin, J. F., Musavandalo, C. M., Nguba, T. B., Molo, J. E. L., Selemani, T. M., Mweru, J. P. M., & Bogaert, J. (2023). Urban Sprawl and Changes in Landscape Patterns: The Case of Kisangani City and Its Periphery (DR Congo). Land, 12(11), 1–14. https://doi.org/10.3390/land12112066
- Baqa, M. F., Chen, F., Lu, L., Qureshi, S., Tariq, A., Wang, S., Jing, L., Hamza, S., & Li, Q. (2021). Monitoring and modeling the patterns and trends of urban growth using urban sprawl matrix and CA-Markov model: A case study of Karachi, Pakistan. Land, 10(7). https://doi.org/10.3390/land10070700
- Behnisch, M., Krüger, T., & Jaeger, J. A. G. (2022). Rapid rise in urban sprawl: Global hotspots and trends since 1990. PLOS Sustainability and Transformation, 1(11), e0000034. https://doi.org/10.1371/journal.pstr.0000034
- Berila, A., & Isufi, F. (2021). Two Decades (2000–2020) Measuring Urban Sprawl Using GIS, RS and Landscape Metrics: a Case Study of Municipali-ty of Prishtina (Kosovo). Journal of Ecological Engineering, 22(6), 114–125. https://doi.org/10.12911/22998993/137078
- Bhatta, B. (2010). Mapping and Monitoring Urban Growth BT - Analysis of Urban Growth and Sprawl from Remote Sensing Data (B. Bhatta, Ed.; pp. 65–83). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-05299-6_5
- Boori, M. S., Netzband, M., Choudhary, K., & Voženílek, V. (2015). Monitoring and modeling of urban sprawl through remote sensing and GIS in Kuala Lumpur, Malaysia. Ecological Processes, 4(1), 1–10. https://doi.org/10.1186/s13717-015-0040-2
- Bozkurt, S. G., & Basaraner, M. (2024). Spatio-temporal investigation of urbanization and its impact on habitat fragmentation in natural ecosys-tems of Istanbul using Shannon’s entropy and landscape metrics in GIS. Environment, Development and Sustainability, 0123456789. https://doi.org/10.1007/s10668-023-04410-7
- Brueckner, J. K. (2000). Urban Sprawl: Diagnosis and Remedies. International Regional Science Review, 23(2), 160–171. https://doi.org/10.1177/016001700761012710
- Chen, J., Chen, J., Liao, A., Cao, X., Chen, L., Chen, X., He, C., Han, G., Peng, S., Lu, M., Zhang, W., Tong, X., & Mills, J. (2015). Global land cover mapping at 30 m resolution: A POK-based operational approach. ISPRS Journal of Photogrammetry and Remote Sensing, 103, 7–27. https://doi.org/10.1016/j.isprsjprs.2014.09.002
- Copernicus. (2020). CORINE Land Cover. https://land.copernicus.eu/en/products/corine-land-cover?tab=main
- Coppin, P., Jonckheere, I., Nackaerts, K., Muys, B., & Lambin, E. (2004). Digital change detection methods in ecosystem monitoring: A review. International Journal of Remote Sensing, 25(9), 1565–1596. https://doi.org/10.1080/0143116031000101675
- Cramer-Greenbaum, S. (2023). Quantifying displacement: Using turnover data to measure physical and psychological neighborhood change. European Journal of Geography, 14(1), 35–46. https://doi.org/10.48088/ejg.s.cra.14.1.35.46
- D’Agata, A., Nosova, B., Vardopoulos, I., Rontos, K., Clemente, M., Colombo, M. C., Sateriano, A., & Salvati, L. (2024). Urban decline, economic crisis and fringe landscapes: The mediterranean experience. In Urban Crisis: Social and Economic Implications for Southern Europe.
- Dai, E., Wu, Z., & Du, X. (2018). A gradient analysis on urban sprawl and urban landscape pattern between 1985 and 2000 in the Pearl River Delta, China. Frontiers of Earth Science, 12(4), 791–807. https://doi.org/10.1007/s11707-017-0637-0
- Dai, X., Jin, J., Chen, Q., & Fang, X. (2022). On Physical Urban Boundaries, Urban Sprawl, and Compactness Measurement: A Case Study of the Wen-Tai Region, China. Land, 11(10). https://doi.org/10.3390/land11101637
- Deng, J. S., Qiu, L. F., Wang, K., Yang, H., & Shi, Y. Y. (2011). An integrated analysis of urbanization-triggered cropland loss trajectory and implica-tions for sustainable land management. Cities, 28(2), 127–137. https://doi.org/10.1016/j.cities.2010.09.005
- Deng, J. S., Wang, K., Hong, Y., & Qi, J. G. (2009). Spatio-temporal dynamics and evolution of land use change and landscape pattern in response to rapid urbanization. Landscape and Urban Planning, 92(3–4), 187–198. https://doi.org/10.1016/j.landurbplan.2009.05.001
- Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070
- Downs, A. (1999). Some realities about sprawl and urban decline. Housing Policy Debate, 10(4), 955–974. https://doi.org/10.1080/10511482.1999.9521356
- Dutta, I., & Das, A. (2019). Application of geo-spatial indices for detection of growth dynamics and forms of expansion in English Bazar Urban Agglomeration, West Bengal. Journal of Urban Management, 8(2), 288–302. https://doi.org/10.1016/j.jum.2019.03.007
- El Garouani, A., Mulla, D. J., El Garouani, S., & Knight, J. (2017). Analysis of urban growth and sprawl from remote sensing data: Case of Fez, Mo-rocco. International Journal of Sustainable Built Environment, 6(1), 160–169. https://doi.org/10.1016/j.ijsbe.2017.02.003
- European Environment Agency. (2008). Urban Sprawl in Europe, the Ignored Challenge. In Urban Sprawl in Europe: Landscapes, Land-Use Change & Policy (Issue 10). https://doi.org/10.1002/9780470692066
- Frenkel, A., & Ashkenazi, M. (2008). Measuring urban sprawl : how can we deal with it ? 35, 56–80. https://doi.org/10.1068/b32155
- Fuladlu, K., Riza, M., & Ilkan, M. (2021). Monitoring Urban Sprawl Using Time-Series Data: Famagusta Region of Northern Cyprus. SAGE Open, 11(2). https://doi.org/10.1177/21582440211007465
- Fulton, W., Pendall, R., Nguyen, M., & Harrison, A. (2001). Who Sprawls Most? How Growth Patterns Differ Across the U.S. July, 1–24.
- Galster, G., Hanson, R., Ratcliffe, M. R., Wolman, H., Coleman, S., & Freihage, J. (2001). Wrestling sprawl to the ground: Defining and measuring an elusive concept. Housing Policy Debate, 12(4), 681–717. https://doi.org/10.1080/10511482.2001.9521426
- Gao, B.-C. (1996). NDWI?A Normalized Difference Water Index for Remote Sensing of Vegetation Liquid Water from Space. Remote Sensing of Environment, 58, 257–266. https://doi.org/10.1016/S0034-4257(96)00067-3
- Gilbert, K. M., & Shi, Y. (2023). Nighttime Lights and Urban Expansion: Illuminating the Correlation between Built-Up Areas of Lagos City and Changes in Climate Parameters. Buildings, 13(12). https://doi.org/10.3390/buildings13122999
- Glaeser, E. L., & Kahn, M. E. (2003). Sprawl and Urban Growth, Discussion paper no 2004. Handbook of Urban and Regional Economics, IV. http://www.econ.brown.edu/Faculty/henderson/sprawl.pdf
- Gogoi, D., Bhaskaran, G., & Gogoi, A. (2023). An analysis of land dynamics in relation to urban sprawl in the Guwahati city of Assam, India. Ecocy-cles, 9(1), 49–60. https://doi.org/10.19040/ecocycles.v9i1.258
- Gordon, P., & Richardson, H. W. (2000). Critiquing Sprawl’ s Critics. Policy Analysis, 368(365), 1–18.
- Habibi, S., & Asadi, N. (2011). Causes, results and methods of controlling urban sprawl. Procedia Engineering, 21, 133–141. https://doi.org/10.1016/j.proeng.2011.11.1996
- Hall, R. E., & Jones, C. I. (1999). Why Do Some Countries Produce So Much More Output Per Worker Than Others? The Quarterly Journal of Eco-nomics, 114(1), 83–116. http://www.jstor.org/stable/2586948
- Hamidi, S., Ewing, R., Preuss, I., & Dodds, A. (2015). Measuring Sprawl and Its Impacts: An Update. https://doi.org/10.1177/0739456X14565247
- He, T., Zhou, R., Ma, Q., Li, C., Liu, D., Fang, X., Hu, Y., & Gao, J. (2023). Quantifying the effects of urban development intensity on the surface urban heat island across building climate zones. Applied Geography, 158(June), 103052. https://doi.org/10.1016/j.apgeog.2023.103052
- Huete, A. R. (1988). A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment, 25(3), 295–309. https://doi.org/10.1016/0034-4257(88)90106-X
- Hysa, A., Löwe, R., & Geist, J. (2024). Ecosystem services potential is declining across European capital metropolitan areas. Scientific Reports, 14(1), 1–19. https://doi.org/10.1038/s41598-024-59333-8
- Irwin, E. G., & Bockstael, N. E. (2007). The evolution of urban sprawl: Evidence of spatial heterogeneity and increasing land fragmentation. Pro-ceedings of the National Academy of Sciences of the United States of America, 104(52), 20672–20677. https://doi.org/10.1073/pnas.0705527105
- Jain, M., Dimri, A. P., & Niyogi, D. (2016). Urban sprawl patterns and processes in delhi from 1977 to 2014 based on remote sensing and spatial metrics approaches. Earth Interactions, 20(14), 1–29. https://doi.org/10.1175/EI-D-15-0040.1
- Jiao, L., Liu, J., Xu, G., Dong, T., Gu, Y., Zhang, B., Liu, Y., & Liu, X. (2018). Proximity Expansion Index: An improved approach to characterize evolu-tion process of urban expansion. Computers, Environment and Urban Systems, 70, 102–112. https://doi.org/10.1016/j.compenvurbsys.2018.02.005
- Jiao, L., Mao, L., & Liu, Y. (2015). Multi-order Landscape Expansion Index: Characterizing urban expansion dynamics. Landscape and Urban Plan-ning, 137, 30–39. https://doi.org/10.1016/j.landurbplan.2014.10.023
- Kadhim, N., Mourshed, M., & Bray, M. (2016). Advances in remote sensing applications for urban sustainability. Euro-Mediterranean Journal for Environmental Integration, 1(1), 1–22. https://doi.org/10.1007/s41207-016-0007-4
- Kar, R., Obi Reddy, G. P., Kumar, N., & Singh, S. K. (2018). Monitoring spatio-temporal dynamics of urban and peri-urban landscape using remote sensing and GIS – A case study from Central India. Egyptian Journal of Remote Sensing and Space Science, 21(3), 401–411. https://doi.org/10.1016/j.ejrs.2017.12.006
- Kawamura, M., Jayamanna, S., & Tsujiko, Y. (1997). Quantitative Evaluation of Urbanization in Developing Countries Using Satellite Data. Doboku Gakkai Ronbunshu, 1997(580), 45–54. https://doi.org/10.2208/jscej.1997.580_45
- Kulwant, M., & Patel, D. (2024). Application of remote sensing, GIS, and AI techniques in the agricultural sector. In Agri-Tech Approaches for Nutrients and Irrigation Water Management. https://doi.org/10.1201/9781003441175-15
- Kumar, J. A. V, Pathan, S. K., & Bhanderi, R. J. (2007). Spatio-temporal analysis for monitoring urban growth - a case study of Indore City. Journal of the Indian Society of Remote Sensing, 35(1), 11–20. https://doi.org/10.1007/BF02991829
- Liu, L., Peng, Z., Wu, H., Jiao, H., Yu, Y., & Zhao, J. (2018). Fast identification of urban sprawl based on K-means clustering with population density and local spatial entropy. Sustainability (Switzerland), 10(8). https://doi.org/10.3390/su10082683
- Liu, L., & Zhang, Y. (2011). Urban heat island analysis using the landsat TM data and ASTER Data: A case study in Hong Kong. Remote Sensing, 3(7), 1535–1552. https://doi.org/10.3390/rs3071535
- Liu, X., Li, X., Chen, Y., Tan, Z., Li, S., & Ai, B. (2010). A new landscape index for quantifying urban expansion using multi-temporal remotely sensed data. Landscape Ecology, 25(5), 671–682. https://doi.org/10.1007/s10980-010-9454-5
- Mdari, Y. E., Daoud, M. A., Namir, A., & Hakdaoui, M. (2022). Casablanca Smart City Project: Urbanization, Urban Growth, and Sprawl Challenges Using Remote Sensing and Spatial Analysis. Lecture Notes in Networks and Systems, 216, 209–217. https://doi.org/10.1007/978-981-16-1781-2_20
- Medayese, S., Magidimisha-Chipungu, H. H., & Chipungu, L. (2023). Spatial Matrices of Urban Expansion in Lafia, North-Central Nigeria. Forum Geografi, 37(1), 66–79. https://doi.org/10.23917/forgeo.v37i1.18068
- Miller, L., Pelletier, C., & Webb, G. I. (2024). Deep Learning for Satellite Image Time-Series Analysis: A review. IEEE Geoscience and Remote Sensing Magazine, 2–45. https://doi.org/10.1109/MGRS.2024.3393010
- Mun, J., Lee, J. S., & Kim, S. (2024). Effects of urban sprawl on regional disparity and quality of life: A case of South Korea. Cities, 151, 105125. https://doi.org/10.1016/j.cities.2024.105125
- Nolè, G., Lasaponara, R., Lanorte, A., & Murgante, B. (2014). Quantifying urban sprawl with spatial autocorrelation techniques using multi-temporal satellite data. International Journal of Agricultural and Environmental Information Systems, 5(2), 20–38. https://doi.org/10.4018/IJAEIS.2014040102
- Page, M. J., McKenzie, J. E., Bossuyt, P., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The pris-ma 2020 statement: An updated guideline for reporting systematic reviews. Medicina Fluminensis, 57(4), 444–465. https://doi.org/10.21860/medflum2021_264903
- Patra, S., Sahoo, S., Mishra, P., & Mahapatra, S. C. (2018). Impacts of urbanization on land use /cover changes and its probable implications on local climate and groundwater level. Journal of Urban Management, 7(2), 70–84. https://doi.org/10.1016/j.jum.2018.04.006
- Pokhariya, H. S., Singh, D. P., & Prakash, R. (2021). Investigating the impacts of urbanization on different land cover classes and land surface temperature using GIS and RS techniques. International Journal of Systems Assurance Engineering and Management. https://doi.org/10.1007/s13198-021-01512-1
- Pranckutė, R. (2021). Web of Science (WoS) and Scopus: the titans of bibliographic information in today’s academic world. Publications, 9(1). https://doi.org/10.3390/publications9010012
- Rahman, M. N., Akter, K. S., & Faridatul, M. I. (2024). Assessing the impact of urban expansion on carbon emission. Environmental and Sustaina-bility Indicators, 23, 100416. https://doi.org/10.1016/j.indic.2024.100416
- Rana, B., Bandyopadhyay, J., & Halder, B. (2024). Investigating the relationship between urban sprawl and urban heat island using remote sens-ing and machine learning approaches. Theoretical and Applied Climatology, 0123456789. https://doi.org/10.1007/s00704-024-04874-1
- Rasul, A., Balzter, H., Ibrahim, G. R. F., Hameed, H. M., Wheeler, J., Adamu, B., Ibrahim, S., & Najmaddin, P. M. (2018). Applying built-up and bare-soil indices from Landsat 8 to cities in dry climates. Land, 7(3). https://doi.org/10.3390/land7030081
- Raza, A., Syed, N. R., Fahmeed, R., Acharki, S., Aljohani, T. H., Hussain, S., Zubair, M., Zahra, S. M., Islam, A. R. M. T., Almohamad, H., & Abdo, H. G. (2024). Investigation of changes in land use/land cover using principal component analysis and supervised classification from operational land imager satellite data: a case study of under developed regions, Pakistan. Discover Sustainability, 5(1). https://doi.org/10.1007/s43621-024-00263-w
- Roelfsema, C. (2010). Integrating field data with high spatial resolution multispectral satellite imagery for calibration and validation of coral reef benthic community maps. Journal of Applied Remote Sensing, 4(1), 043527. https://doi.org/10.1117/1.3430107
- Rouse, J. W., Jr., Haas, R. H., Schell, J. A., & Deering, D. W. (1974). Monitoring vegetation systems in the Great Plains with ERTS. NASA. Goddard Space Flight Center 3d ERTS-1 Symp., 1. https://doi.org/10.1021/jf60203a024
- Salvati, L., Munafo, M., Morelli, V. G., & Sabbi, A. (2012). Low-density settlements and land use changes in a Mediterranean urban region. Land-scape and Urban Planning, 105(1–2), 43–52. https://doi.org/10.1016/j.landurbplan.2011.11.020
- Selmy, S. A. H., Kucher, D. E., Mozgeris, G., Moursy, A. R. A., Jimenez-Ballesta, R., Kucher, O. D., Fadl, M. E., & Mustafa, A. rahman A. (2023). Detecting, Analyzing, and Predicting Land Use/Land Cover (LULC) Changes in Arid Regions Using Landsat Images, CA-Markov Hybrid Model, and GIS Techniques. Remote Sensing, 15(23). https://doi.org/10.3390/rs15235522
- Shaw, R., & Das, A. (2018). Identifying peri-urban growth in small and medium towns using GIS and remote sensing technique: A case study of English Bazar Urban Agglomeration, West Bengal, India. Egyptian Journal of Remote Sensing and Space Science, 21(2), 159–172. https://doi.org/10.1016/j.ejrs.2017.01.002
- Smith, D. (2020). Population and Urbanization. The State of the Middle East, 1(1), 120–121. https://doi.org/10.4324/9781315065977-35
- Sohn, J., Choi, S., Lewis, R., & Knaap, G. (2012). Characterising urban sprawl on a local scale with accessibility measures. Geographical Journal, 178(3), 230–241. https://doi.org/10.1111/j.1475-4959.2012.00468.x
- Sudhira, H. S., Ramachandra, T. V., & Jagadish, K. S. (2004). Urban sprawl: Metrics, dynamics and modelling using GIS. International Journal of Applied Earth Observation and Geoinformation, 5(1), 29–39. https://doi.org/10.1016/j.jag.2003.08.002
- Sultana, S., & Weber, J. (2014). The Nature of Urban Growth and the Commuting Transition: Endless Sprawl or a Growth Wave? Urban Studies, 51(3), 544–576. https://doi.org/10.1177/0042098013498284
- Sun, C., Wu, Z. F., Lv, Z. Q., Yao, N., & Wei, J. B. (2013). Quantifying different types of urban growth and the change dynamic in Guangzhou using multi-temporal remote sensing data. International Journal of Applied Earth Observation and Geoinformation, 21(1), 409–417. https://doi.org/10.1016/j.jag.2011.12.012
- Taubenböck, H., Wegmann, M., Roth, A., Mehl, H., & Dech, S. (2009). Urbanization in India - Spatiotemporal analysis using remote sensing data. Computers, Environment and Urban Systems, 33(3), 179–188. https://doi.org/10.1016/j.compenvurbsys.2008.09.003
- Torrens, P. M. (2008). A Toolkit for Measuring Sprawl. May 2007, 5–36. https://doi.org/10.1007/s12061-008-9000-x
- Triantakonstantis, D., & Stathakis, D. (2015). Examining urban sprawl in Europe using spatial metrics. Geocarto International, 30(10), 1092–1112. https://doi.org/10.1080/10106049.2015.1027289
- UN Department of Economic and Social Affairs. (2018). World Urbanization Prospects. In Demographic Research (Vol. 12). https://population.un.org/wup/Publications/Files/WUP2018-Report.pdf
- van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. https://doi.org/10.1007/s11192-009-0146-3
- Vogelmann, J. E., Gallant, A. L., Shi, H., & Zhu, Z. (2016). Perspectives on monitoring gradual change across the continuity of Landsat sensors using time-series data. Remote Sensing of Environment, 185, 258–270. https://doi.org/10.1016/j.rse.2016.02.060
- Waleed, M., Sajjad, M., & Shazil, M. S. (2024). Urbanization-led land cover change impacts terrestrial carbon storage capacity: A high-resolution remote sensing-based nation-wide assessment in Pakistan (1990–2020). Environmental Impact Assessment Review, 105(July 2023), 107396. https://doi.org/10.1016/j.eiar.2023.107396
- Wang, G., Peng, W., Zhang, L., Xiang, J., Shi, J., & Wang, L. (2023). Quantifying urban expansion and its driving forces in Chengdu, western China. Egyptian Journal of Remote Sensing and Space Science, 26(4), 1057–1070. https://doi.org/10.1016/j.ejrs.2023.11.010
- Woodcock, C. E., Loveland, T. R., Herold, M., & Bauer, M. E. (2020). Transitioning from change detection to monitoring with remote sensing: A paradigm shift. Remote Sensing of Environment, 238, 111558. https://doi.org/10.1016/j.rse.2019.111558
- World Bank. (2024). Urban population growth (annual %). https://data.worldbank.org/indicator/SP.URB.GROW?end=2023&locations=CN-IN&most_recent_value_desc=false&start=2023&view=bar
- Wu, Y., Li, S., & Yu, S. (2016). Monitoring urban expansion and its effects on land use and land cover changes in Guangzhou city, China. Environ-mental Monitoring and Assessment, 188(1), 1–15. https://doi.org/10.1007/s10661-015-5069-2
- Xu, C., Liu, M., Zhang, C., An, S., Yu, W., & Chen, J. M. (2007). The spatiotemporal dynamics of rapid urban growth in the Nanjing metropolitan region of China. Landscape Ecology, 22(6), 925–937. https://doi.org/10.1007/s10980-007-9079-5
- Xu, G., Zhou, Z., Jiao, L., & Zhao, R. (2020). Compact Urban Form and Expansion Pattern Slow Down the Decline in Urban Densities: A Global Perspective. Land Use Policy, 94, 104563. https://doi.org/10.1016/j.landusepol.2020.104563
- Xu, H. (2005). Study on extracting water body information using improved normalized difference water index (MNDWI). National Remote Sensing Bulletin, 5, 589–595. https://doi.org/10.11834/jrs.20050586
- Y. Zha, J. G., & Ni, S. (2003). Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. International Journal of Remote Sensing, 24(3), 583–594. https://doi.org/10.1080/01431160304987
- Yan, Y., Yang, Y., & Yang, M. (2024). Unravelling the non-linear response of ecosystem services to urban-rural transformation in the Beijing-Tianjin-Hebei region, China. Ecological Informatics, 81, 102633. https://doi.org/10.1016/j.ecoinf.2024.102633
- Yulianto, F., Fitriana, H. L., & Sukowati, K. A. D. (2020). Integration of remote sensing, GIS, and Shannon’s entropy approach to conduct trend analysis of the dynamics change in urban/built-up areas in the Upper Citarum River Basin, West Java, Indonesia. Modeling Earth Systems and Environment, 6(1), 383–395. https://doi.org/10.1007/s40808-019-00686-9
- Zeng, C., Liub, Y., Steind, A., & Jiao, L. (2015). Characterization and spatial modeling of urban sprawl in the Wuhan Metropolitan Area, China. International Journal of Applied Earth Observation and Geoinformation, 34(1), 10–24. https://doi.org/10.1016/j.jag.2014.06.012
- Zhang, L., Zhang, J., Li, X., Zhou, K., & Ye, J. (2023). The Impact of Urban Sprawl on Carbon Emissions from the Perspective of Nighttime Light Remote Sensing: A Case Study in Eastern China. Sustainability (Switzerland), 15(15). https://doi.org/10.3390/su151511940
- Zhang, N., Hong, Y., Qin, Q., & Zhu, L. (2013). Evaluation of the visible and shortwave infrared drought index in China. International Journal of Disaster Risk Science, 4(2), 68–76. https://doi.org/10.1007/s13753-013-0008-8