{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T03:58:22Z","timestamp":1768276702458,"version":"3.49.0"},"reference-count":74,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2022,4,23]],"date-time":"2022-04-23T00:00:00Z","timestamp":1650672000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In recent years, socioeconomic transformation and social modernisation in the Gulf Cooperation Council (GCC) states have led to tremendous changes in lifestyle and, subsequently, expansion of urban settlements. This accelerated growth is pronounced not only across vegetated coasts, plains, and mountains, but also in desert cities. Nevertheless, spatial simulation and prediction of desert urban patterns has received little attention, including in Oman. While most urban settlements in Oman are located in desert environments, research exploring and monitoring this type of urban growth is rare in the scientific literature. This research focuses on analysing and predicting land use\u2013land cover (LULC) changes across the desert city of Ibri in Oman. A methodology was employed involving integrating the multilayer perceptron (MLP) and Markov chain (MC) techniques to forecast spatiotemporal LULC dynamics and map urban growth patterns. The inputs were three Landsat images from 2010 and 2020, and a series of covariate layers based on transforms of elevation, slope, population settlements, urban centres, and points of interest that proxy the driving forces of change. The findings indicated that the observed LULC changes were predominantly rapid across the city during 2010 to 2020, transforming desert, bare land, and vegetation into built-up areas. The forecast showed that area of land conversion from desert to urban would be 5666 ha during the next two decades and 7751 ha by 2050. Similarly, vacant land is expected to contribute large areas to urban expansion (2370 ha by 2040, and 3266 ha by 2050), although desert cities confront numerous environmental challenges, including water scarcity, shrinking vegetation cover, and being converted into residential land. Massive urban expansion has consequences for biodiversity and natural ecosystems\u2014particularly in green areas, which are expected to decline by approximately 107 ha by 2040 (i.e., 10%) and 166 ha by 2050. The outcomes of this research provide fundamental guidance for decision-makers and planners in Oman and elsewhere to effectively monitor and manage desert urban dynamics and sustainable desert cities.<\/jats:p>","DOI":"10.3390\/rs14092037","type":"journal-article","created":{"date-parts":[[2022,4,24]],"date-time":"2022-04-24T00:45:21Z","timestamp":1650761121000},"page":"2037","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":40,"title":["Forecasting of Built-Up Land Expansion in a Desert Urban Environment"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6969-9188","authenticated-orcid":false,"given":"Shawky","family":"Mansour","sequence":"first","affiliation":[{"name":"Geography Department, College of Arts and Social Sciences, Sultan Qaboos University, Al-Khoud P.C., Muscat 123, Oman"},{"name":"Department of Geography and GIS, Faculty of Arts, Alexandria University, Al Shatby, Alexandria 21526, Egypt"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4739-4855","authenticated-orcid":false,"given":"Mohammed","family":"Alahmadi","sequence":"additional","affiliation":[{"name":"National Center for Remote Sensing Technology, Space and Aeronautics Research Institute, King Abdulaziz City for Science and Technology, P.O. Box 6086, Riyadh 11442, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5489-6880","authenticated-orcid":false,"given":"Peter M.","family":"Atkinson","sequence":"additional","affiliation":[{"name":"The Faculty of Science and Technology, Lancaster University, Lancaster LA1 4YR, UK"},{"name":"Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Beijing 100101, China"},{"name":"Geography and Environment, University of Southampton, Southampton SO17 1BJ, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5594-5464","authenticated-orcid":false,"given":"Ashraf","family":"Dewan","sequence":"additional","affiliation":[{"name":"School of Earth and Planetary Sciences, Curtin University, Perth, WA 6102, Australia"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,23]]},"reference":[{"key":"ref_1","unstructured":"UN (2021, June 25). World Urbanization Prospects: The 2018 Revision. Available online: https:\/\/population.un.org\/wup\/Publications\/Files\/WUP2018-Report.pdf."},{"key":"ref_2","unstructured":"UN (2021, June 24). United Nation Decade for Desert and Fight against Desertification. Available online: https:\/\/www.un.org\/en\/events\/desertification_decade\/whynow.shtml."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.compenvurbsys.2014.02.005","article-title":"Developing the desert: The pace and process of urban growth in Dubai","volume":"45","author":"Nassar","year":"2014","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"104414","DOI":"10.1016\/j.landusepol.2019.104414","article-title":"Monitoring land use and land cover changes in the mountainous cities of Oman using GIS and CA-Markov modelling techniques","volume":"91","author":"Mansour","year":"2020","journal-title":"Land Use Policy"},{"key":"ref_5","first-page":"1845","article-title":"Social\u2013spatial analyses of attitudes toward the desert in a Southwestern US city","volume":"109","author":"Andrade","year":"2019","journal-title":"Ann. Am. Assoc. Geogr."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"611","DOI":"10.1023\/A:1013170528551","article-title":"Analysis and simulation of land-use change in the central Arizona\u2013Phoenix region, USA","volume":"16","author":"Jenerette","year":"2001","journal-title":"Landsc. Ecol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.apgeog.2015.06.015","article-title":"Land use\/land cover change detection and prediction in the north-western coastal desert of Egypt using Markov-CA","volume":"63","author":"Halmy","year":"2015","journal-title":"Appl. Geogr."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"489","DOI":"10.5194\/isprs-archives-XLII-4-W18-489-2019","article-title":"Assessment of land use and land cover change detection by using remote sensing and gis techniques in the coastal deserts, South of Iran","volume":"42","author":"Hosseini","year":"2019","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"592","DOI":"10.1080\/1747423X.2020.1765425","article-title":"Land use\/land cover change detection and urban sprawl in the peri-urban area of greater Cairo since the Egyptian revolution of 2011","volume":"15","author":"Salem","year":"2020","journal-title":"J. Land Use Sci."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.iswcr.2018.10.001","article-title":"Prediction of spatial land use changes based on LCM in a GIS environment for Desert Wetlands\u2014A case study: Meighan Wetland, Iran","volume":"7","author":"Ansari","year":"2019","journal-title":"Int. Soil Water Conserv. Res."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1016\/j.jaridenv.2015.04.006","article-title":"Assessing desertification risk in the semi-arid highlands of central Mexico","volume":"120","year":"2015","journal-title":"J. Arid. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.jaridenv.2012.10.014","article-title":"The case of urban sprawl in Spain as an active and irreversible driving force for desertification","volume":"90","author":"Marques","year":"2013","journal-title":"J. Arid. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Maconachie, R. (2016). Urban Growth and Land Degradation in Developing Cities: Change and Challenges in Kano Nigeria, Routledge.","DOI":"10.4324\/9781315548821"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.cities.2019.01.021","article-title":"Monitoring and modelling spatio-temporal urban growth of Delhi using Cellular Automata and geoinformatics","volume":"90","author":"Tripathy","year":"2019","journal-title":"Cities"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1007\/s11442-010-0483-4","article-title":"Spatial patterns and driving forces of land use change in China during the early 21st century","volume":"20","author":"Liu","year":"2010","journal-title":"J. Geogr. Sci."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Msofe, N.K., Sheng, L., and Lyimo, J. (2019). Land use change trends and their driving forces in the Kilombero Valley Floodplain, Southeastern Tanzania. Sustainability, 11.","DOI":"10.3390\/su11020505"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"753","DOI":"10.1080\/15481603.2020.1794395","article-title":"Driving forces of grassland vegetation changes in Chen Barag Banner, Inner Mongolia","volume":"57","author":"Yan","year":"2020","journal-title":"GIScience Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"758","DOI":"10.1007\/s00267-020-01276-7","article-title":"Dynamic changes of net primary productivity and associated urban growth driving forces in Guangzhou City, China","volume":"65","author":"Wu","year":"2020","journal-title":"Environ. Manag."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1068\/b31135","article-title":"What is land cover?","volume":"32","author":"Comber","year":"2005","journal-title":"Environ. Plan. B Plan. Des."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1146\/annurev.energy.28.050302.105459","article-title":"Dynamics of land-use and land-cover change in tropical regions","volume":"28","author":"Lambin","year":"2003","journal-title":"Annu. Rev. Environ. Resour."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1016\/j.landusepol.2014.11.019","article-title":"Definition of landscape character areas and types in Side region, Antalya-Turkey with regard to land use planning","volume":"44","author":"Atik","year":"2015","journal-title":"Land Use Policy"},{"key":"ref_22","first-page":"1","article-title":"Land-use and land-cover change","volume":"1","author":"Ellis","year":"2007","journal-title":"Encycl. Earth"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1016\/j.ecolind.2009.07.007","article-title":"Suitability criteria for measures of urban sprawl","volume":"10","author":"Jaeger","year":"2010","journal-title":"Ecol. Indic."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Bhatta, B. (2010). Urban growth and sprawl. Analysis of Urban Growth and Sprawl from Remote Sensing Data, Springer.","DOI":"10.1007\/978-3-642-05299-6"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1016\/j.landusepol.2015.08.001","article-title":"Multi-scale analysis of urban sprawl in Europe: Towards a European de-sprawling strategy","volume":"49","author":"Hennig","year":"2015","journal-title":"Land Use Policy"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1594","DOI":"10.1177\/0042098015577773","article-title":"Determinants of urban sprawl in European cities","volume":"52","author":"Oueslati","year":"2015","journal-title":"Urban Stud."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"755","DOI":"10.1111\/ddi.12301","article-title":"Corridors for aliens but not for natives: Effects of marine urban sprawl at a regional scale","volume":"21","author":"Airoldi","year":"2015","journal-title":"Divers. Distrib."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Bae, C.-H.C. (2017). Urban Sprawl in Western Europe and the United States, Routledge.","DOI":"10.4324\/9781315235226"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1660","DOI":"10.1177\/0042098019841540","article-title":"Urban sprawl and the emergence of food deserts in the USA","volume":"57","author":"Hamidi","year":"2020","journal-title":"Urban Stud."},{"key":"ref_30","unstructured":"Squires, G.D. (2002). Urban sprawl and the uneven development of metropolitan America. Urban Sprawl: Causes, Consequences, and Policy Responses, Urban Institute."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1016\/j.habitatint.2009.09.008","article-title":"Sustainable urban expansion and transportation in a growing megacity: Consequences of urban sprawl for mobility on the urban fringe of Beijing","volume":"34","author":"Zhao","year":"2010","journal-title":"Habitat Int."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1016\/j.proeng.2011.11.1996","article-title":"Causes, results and methods of controlling urban sprawl","volume":"21","author":"Habibi","year":"2011","journal-title":"Procedia Eng."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1016\/j.ecolind.2019.05.059","article-title":"Measurement of the eco-environmental effects of urban sprawl: Theoretical mechanism and spatiotemporal differentiation","volume":"105","author":"Chen","year":"2019","journal-title":"Ecol. Indic."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2307\/3144884","article-title":"The nature and economics of urban sprawl","volume":"41","author":"Harvey","year":"1965","journal-title":"Land Econ."},{"key":"ref_35","unstructured":"Chin, N. (2002). Unearthing the Roots of Urban Sprawl: A Critical Analysis of Form, Function and Methodology, Centre for Advanced Spatial Analysis (UCL)."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"635","DOI":"10.1080\/00420980120035268","article-title":"Polynucleated urban landscapes","volume":"38","author":"Batty","year":"2001","journal-title":"Urban Stud."},{"key":"ref_37","unstructured":"Arbury, J. (2005). From Urban Sprawl to Compact City: An Analysis of Urban Growth Management in Auckland, Academia."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Nagendra, H., Sudhira, H., Katti, M., and Schewenius, M. (2013). Sub-regional assessment of India: Effects of urbanization on land use, biodiversity and ecosystem services. Urbanization, Biodiversity and Ecosystem Services: Challenges and Opportunities, Springer.","DOI":"10.1007\/978-94-007-7088-1_6"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1080\/1573062X.2010.484497","article-title":"Effect of urban sprawl on a traditional water system (Qanat) in the City of Mashhad, NE Iran","volume":"7","author":"Hosseini","year":"2010","journal-title":"Urban Water J."},{"key":"ref_40","unstructured":"Lang, R.E., and Simmons, P.A. (2001). Boomburbs\u201d: The Emergence of Large, Fast-Growing Suburban Cities in the United States, Fannie Mae Foundation."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1080\/13563470701486372","article-title":"Brand Dubai: The instant city; or the instantly recognizable city","volume":"12","author":"Bagaeen","year":"2007","journal-title":"Int. Plan. Stud."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1177\/0956247819900468","article-title":"Urban water security: A comparative study of cities in the arid Americas","volume":"32","author":"Bernabeu","year":"2020","journal-title":"Environ. Urban."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Dewan, A.M., and Corner, R.J. (2012, January 22\u201327). The impact of land use and land cover changes on land surface temperature in a rapidly urbanizing megacity. Proceedings of the 2012 IEEE International Geoscience and Remote Sensing Symposium, Munich, Germany.","DOI":"10.1109\/IGARSS.2012.6352709"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1006\/jema.2000.0369","article-title":"Modeling the relationships between land use and land cover on private lands in the Upper Midwest, USA","volume":"59","author":"Brown","year":"2000","journal-title":"J. Environ. Manag."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1080\/13658810310001620906","article-title":"Spatial simulation for translating from land use to land cover","volume":"18","author":"Brown","year":"2004","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1167","DOI":"10.1007\/s10980-009-9355-7","article-title":"Combining top-down and bottom-up dynamics in land use modeling: Exploring the future of abandoned farmlands in Europe with the Dyna-CLUE model","volume":"24","author":"Verburg","year":"2009","journal-title":"Landsc. Ecol."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1007\/s40710-015-0062-x","article-title":"Predicting spatial and decadal LULC changes through cellular automata Markov chain models using earth observation datasets and geo-information","volume":"2","author":"Singh","year":"2015","journal-title":"Environ. Processes"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1007\/s10661-015-4298-8","article-title":"Modeling land use and land cover changes in a vulnerable coastal region using artificial neural networks and cellular automata","volume":"187","author":"Qiang","year":"2015","journal-title":"Environ. Monit. Assess."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Garc\u00eda-\u00c1lvarez, D. (2018). The influence of scale in LULC modeling. A comparison between two different LULC maps (SIOSE and CORINE). Geomatic Approaches for Modeling Land Change Scenarios, Springer.","DOI":"10.1007\/978-3-319-60801-3_10"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"494","DOI":"10.1007\/s10661-018-6877-y","article-title":"Modeling land use\/land cover change using remote sensing and geographic information systems: Case study of the Seyhan Basin, Turkey","volume":"190","author":"Adbagher","year":"2018","journal-title":"Environ. Monit. Assess."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Jiang, H., Xu, X., Guan, M., Wang, L., Huang, Y., and Liu, Y. (2019). Simulation of spatiotemporal land use changes for integrated model of socioeconomic and ecological processes in China. Sustainability, 11.","DOI":"10.3390\/su11133627"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"398","DOI":"10.1016\/j.earscirev.2019.01.001","article-title":"Spatially explicit simulation of land use\/land cover changes: Current coverage and future prospects","volume":"190","author":"Ren","year":"2019","journal-title":"Earth-Sci. Rev."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"5863164","DOI":"10.1155\/2020\/5863164","article-title":"RS and GIS supported urban LULC and UHI change simulation and assessment","volume":"2020","author":"Liu","year":"2020","journal-title":"J. Sens."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Talukdar, S., Singha, P., Mahato, S., Pal, S., Liou, Y.-A., and Rahman, A. (2020). Land-use land-cover classification by machine learning classifiers for satellite observations\u2014A review. Remote Sens., 12.","DOI":"10.3390\/rs12071135"},{"key":"ref_55","first-page":"100463","article-title":"Remote sensing approach to simulate the land use\/land cover and seasonal land surface temperature change using machine learning algorithms in a fastest-growing megacity of Bangladesh","volume":"21","author":"Kafy","year":"2021","journal-title":"Remote Sens. Appl. Soc. Environ."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1007\/978-981-33-4114-2_3","article-title":"Spatial Distribution of Socioeconomic Factors and Its Impact on Urban Land Use Dynamics: An Agent Based Modeling Approach","volume":"Volume 121","author":"Singh","year":"2021","journal-title":"Urban Science and Engineering: Proceedings of ICUSE 2020"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"414","DOI":"10.1111\/j.1365-2664.2007.01281.x","article-title":"Evaluating sampling strategies and logistic regression methods for modelling complex land cover changes","volume":"44","author":"Rutherford","year":"2007","journal-title":"J. Appl. Ecol."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Schubert, H., Caballero Calvo, A., Rauchecker, M., Rojas-Zamora, O., Brokamp, G., and Sch\u00fctt, B. (2018). Assessment of Land Cover Changes in the Hinterland of Barranquilla (Colombia) Using Landsat Imagery and Logistic Regression. Land, 7.","DOI":"10.3390\/land7040152"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"012003","DOI":"10.1088\/1755-1315\/500\/1\/012003","article-title":"Driving-factors identification of land-cover change in west java using binary logistic regression based on geospatial data","volume":"500","author":"Virtriana","year":"2020","journal-title":"Proc. IOP Conf. Ser. Earth Environ. Sci."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1068\/b240247","article-title":"A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area","volume":"24","author":"Clarke","year":"1997","journal-title":"Environ. Plan. B Plan. Des."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Nath, B., Wang, Z., Ge, Y., Islam, K., Singh, R.P., and Niu, Z. (2020). Land use and land cover change modeling and future potential landscape risk assessment using Markov-Ca model and analytical hierarchy process. ISPRS Int. J. Geo-Inf., 9.","DOI":"10.3390\/ijgi9020134"},{"key":"ref_62","first-page":"1","article-title":"Synergistic use of particle swarm optimization, artificial neural network, and extreme gradient boosting algorithms for urban LULC mapping from WorldView-3 images","volume":"37","author":"Hamedianfar","year":"2020","journal-title":"Geocarto Int."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"2063","DOI":"10.12928\/telkomnika.v16i5.9309","article-title":"Land Use Growth Simulation and Optimization for Achieving a Sustainable Urban Form","volume":"16","author":"Handayanto","year":"2018","journal-title":"Telkomnika"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1111\/1467-8306.9302004","article-title":"Multi-agent systems for the simulation of land-use and land-cover change: A review","volume":"93","author":"Parker","year":"2003","journal-title":"Ann. Assoc. Am. Geogr."},{"key":"ref_65","unstructured":"(2021, April 20). Al-Dhahra Spatial Strategy. Available online: https:\/\/www.aldahra.com\/img\/multimedia\/Al-Dahra-Sustainability-Report-2020-V26.pdf."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"100167","DOI":"10.1016\/j.envc.2021.100167","article-title":"Assessment of land surface temperature and land cover variability during winter: A spatio-temporal analysis of Pabna municipality in Bangladesh","volume":"4","author":"Abir","year":"2021","journal-title":"Environ. Chall."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"759","DOI":"10.1080\/10106049.2016.1178812","article-title":"Developing detailed age-specific thematic maps for coffee (Coffea arabica L.) in heterogeneous agricultural landscapes using random forests applied on Landsat 8 multispectral sensor","volume":"32","author":"Chemura","year":"2017","journal-title":"Geocarto Int."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/S0034-4257(01)00295-4","article-title":"Status of land cover classification accuracy assessment","volume":"80","author":"Foody","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"611","DOI":"10.4236\/ijg.2017.84033","article-title":"Accuracy assessment of land use\/land cover classification using remote sensing and GIS","volume":"8","author":"Rwanga","year":"2017","journal-title":"Int. J. Geosci."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"4407","DOI":"10.1080\/01431161.2011.552923","article-title":"Death to Kappa: Birth of quantity disagreement and allocation disagreement for accuracy assessment","volume":"32","author":"Pontius","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Bratley, K., and Ghoneim, E. (2018). Modeling urban encroachment on the agricultural land of the eastern Nile Delta using remote sensing and a GIS-based Markov chain model. Land, 7.","DOI":"10.3390\/land7040114"},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"553","DOI":"10.1016\/S0198-9715(01)00015-1","article-title":"Using neural networks and GIS to forecast land use changes: A land transformation model","volume":"26","author":"Pijanowski","year":"2002","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_73","first-page":"29","article-title":"Multi-layer perceptron neural network and Markov chain based geospatial analysis of land use and land cover change","volume":"3","author":"Shen","year":"2020","journal-title":"J. Environ. Inform. Lett."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1007\/s100219900011","article-title":"Quantifying landscape spatial pattern: What is the state of the art?","volume":"1","author":"Gustafson","year":"1998","journal-title":"Ecosystems"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/9\/2037\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:59:31Z","timestamp":1760137171000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/9\/2037"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,23]]},"references-count":74,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2022,5]]}},"alternative-id":["rs14092037"],"URL":"https:\/\/doi.org\/10.3390\/rs14092037","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,4,23]]}}}