Spatio-temporal analysis of land use and land cover change: a systematic model inter-comparison driven by integrated modelling techniques

References

• Adhikari, S., T. Fik, and P. Dwivedi. 2017. “Proximate Causes of Land-Use and Land-Cover Change in Bannerghatta National Park: A Spatial Statistical Model.” Forests 8 (9): 1–23. doi:10.3390/f8090342.
   Web of Science ®Google Scholar
• Agarwal, C., G. M. Green, J. M. Grove, T. P. Evans, C. M. Schweik, and C. M. Schweik. 2010. “A Review and Assessment of Land-Use Change Models: Dynamics of Space, Time, and Human Choice.” General Technical Report NE-297 1: 1–61. doi:10.1289/ehp.6514.
   Web of Science ®Google Scholar
• Aguejdad, R., T. Houet, and L. Hubert-Moy. 2017. “Spatial Validation of Land Use Change Models Using Multiple Assessment Techniques: A Case Study of Transition Potential Models.” Environmental Modeling and Assessment 22 (6): 591–606. doi:10.1007/s10666-017-9564-4.
   Web of Science ®Google Scholar
• Arsanjani, J. J., M. Helbich, W. Kainz, and A. D. Boloorani. 2013. “Integration of Logistic Regression, Markov Chain and Cellular Automata Models to Simulate Urban Expansion.” International Journal of Applied Earth Observation and Geoinformation 21 (1): 265–275. doi:10.1016/j.jag.2011.12.014.
   Web of Science ®Google Scholar
• Basnyat, B. 2009. “Impacts of Demographic Changes on Forests and Forestry in Asia and the Pacific.” Agriculture: Food and Agriculture Organization of the United Nations Regional Office for Asia and the Pacific, Bangkok: 1–82.
   Google Scholar
• Behera, M. D., S. N. Borate, S. N. Panda, P. R. Behera, and P. S. Roy. 2012. “Modelling and Analyzing the Watershed Dynamics Using Cellular Automata (Ca)-markov Model - A Geo-Information Based Approach.” Journal of Earth System Science 121 (4): 1011–1024. doi:10.1007/s12040-012-0207-5.
   Web of Science ®Google Scholar
• Birhane, E., H. Ashfare, A. A. Fenta, H. Hishe, M. A. Gebremedhin, H. G. Wahed, and N. Solomon. 2019. “Land Use Land Cover Changes along Topographic Gradients in Hugumburda National Forest Priority Area, Northern Ethiopia.” Remote Sensing Applications: Society and Environment 13: 61–68. doi:10.1016/j.rsase.2018.10.017.
   Google Scholar
• Chavez, P. S. 1996. “Image-Based Atmospheric Corrections - Revisited and Improved.” Photogrammetric Engineering and Remote Sensing 62 (9): 1025–1036.
   Web of Science ®Google Scholar
• Chorley, R. J., and P. Haggett. 1965. “In Geographical Trend-Surface Mapping.” Transactions of the Institute of British Geographers 37 (37): 47–67. doi:10.2307/621689.
   Google Scholar
• DeFries, R., and K. N. Eshleman. 2004. “Land-Use Change and Hydrologic Processes: A Major Focus for the Future.” Hydrological Processes 18 (11): 2183–2186. doi:10.1002/hyp.5584.
   Web of Science ®Google Scholar
• Eastman, J. R. 2012. “IDRISI Selva.” Version 17.02. Worcester, MA: Clark Labs, Clark University.
   Google Scholar
• Ellis, E. 2007. “Land-use and Land-cover Change and Climate Change.” The Encyclopedia of earth, 4. https://web.archive.org/web/20070503192914/http://www.eoearth.org/article/Land-use_and_land-cover_change
   Google Scholar
• Fei, L., S. Zhang, K. Bu, J. Yang, Q. Wang, and L. Chang. 2015. “The Relationships between Land Use Change and Demographic Dynamics in Western Jilin Province.” Journal of Geographical Sciences 25 (5): 617–636. doi:10.1007/s11442-015-1191-x.
   Web of Science ®Google Scholar
• Ghosh, P., A. Mukhopadhyay, A. Chanda, P. Mondal, A. Akhand, S. Mukherjee, S. K. Nayak, et al. 2017. “Application of Cellular Automata and Markov-Chain Model in Geospatial Environmental Modeling- A Review.” Remote Sensing Applications: Society and Environment 5: 64–77. doi:10.1016/j.rsase.2017.01.005.
   Google Scholar
• Grekousis, G., P. Manetos, and Y. N. Photis. 2013. “Modeling Urban Evolution Using Neural Networks, Fuzzy Logic and GIS: The Case of the Athens Metropolitan Area.” Cities 30 (1): 193–203. doi:10.1016/j.cities.2012.03.006.
   Web of Science ®Google Scholar
• Guan, D., H. Li, T. Inohae, W. Su, T. Nagaie, and K. Hokao. 2011. “Modeling Urban Land Use Change by the Integration of Cellular Automaton and Markov Model.” Ecological Modelling 222 (20–22): 3761–3772. doi:10.1016/j.ecolmodel.2011.09.009.
   Web of Science ®Google Scholar
• Hamdy, O., S. Zhao, M. A. Salheen, and Y. Y. Eid. 2016. “Analyses the Driving Forces for Urban Growth by Using IDRISI®Selva Models Abouelreesh - Aswan as a Case Study.” International Journal of Engineering and Technology 9 (3): 226–232. doi:10.7763/ijet.2017.v9.975.
   Google Scholar
• Harrison, P. A., R. W. Dunford, I. P. Holman, and M. D. A. Rounsevell. 2016. “Climate Change Impact Modelling Needs to Include Cross-sectoral Interactions.” Nature Climate Change 6 (9): 885+. doi:10.1038/nclimate3039.
   Web of Science ®Google Scholar
• Holman, I. P., C. Brown, V. Janes, and D. Sandars. 2017. “Can We Be Certain about Future Land Use Change in Europe? A Multi-scenario, Integrated-assessment Analysis.” Agricultural Systems 15: 126–135. doi:10.1016/j.agsy.2016.12.001.
   Web of Science ®Google Scholar
• Hu, Z., and C. P. Lo. 2007. “Modeling Urban Growth in Atlanta Using Logistic Regression.” Computers, Environment and Urban Systems 31 (6): 667–688. doi:10.1016/j.compenvurbsys.2006.11.001.
   Web of Science ®Google Scholar
• Islam, K., M. F. Rahman, and M. Jashimuddin. 2018. “Modeling Land Use Change Using Cellular Automata and Artificial Neural Network: The Case of Chunati Wildlife Sanctuary, Bangladesh.” Ecological Indicators 88: 439–453. doi:10.1016/j.ecolind.2018.01.047.
   Web of Science ®Google Scholar
• Jose, M., and M. Padmanabhan. 2015. “Dynamics of Agricultural Land Use Change in Kerala: A Policy and Social-Ecological Perspective.” International Journal of Agricultural Sustainability 14 (3): 307–324. doi:10.1080/14735903.2015.1107338.
   Web of Science ®Google Scholar
• Kamwi, J. M., M. A. Cho, C. Kaetsch, S. O. Manda, F. P. Graz, and P. W. Chirwa. 2018. “Assessing the Spatial Drivers of Land Use and Land Cover Change in the Protected and Communal Areas of the Zambezi Region, Namibia.” Land 7 (4): 131. doi:10.3390/land7040131.
   Web of Science ®Google Scholar
• Kolb, M., J. F. Mas, and L. Galicia. 2013. “Evaluating Drivers of Land-Use Change and Transition Potential Models in a Complex Landscape in Southern Mexico.” International Journal of Geographical Information Science 27 (9): 1804–1827. doi:10.1080/13658816.2013.770517.
   Web of Science ®Google Scholar
• Lambin, E. F., B. L. Turner, H. J. Geist, S. B. Agbola, A. Angelsen, J. W. Bruce, O. T. Coomes, et al. 2001. “The Causes of Land-Use and Land-Cover Change: Moving beyond the Myths.” Global Environmental Change 11 (4): 261–269. doi:10.1016/S0959-3780(01)00007-3.
   Web of Science ®Google Scholar
• Lambin, E. F., and H. Geist. 2006. Land-use and Land-cover Change: Local Processes and Global Impacts. The IGBP Global Change Series. Berlin, Heidelberg: Springer-Verlag. New York: Springer.
   Google Scholar
• Lee, H. J., Y. E. Choi, and S. W. Lee. 2018. “Complex Relationships of the Effects of Topographic Characteristics and Susceptible Tree Cover on Burn Severity.” Sustainability 10 (2). doi:10.3390/su10020295.
   PubMed Web of Science ®Google Scholar
• Li, X., Y. Wang, J. Li, and B. Lei. 2016. “Physical and Socioeconomic Driving Forces of Land-Use and Land-Cover Changes: A Case Study of Wuhan City, China.” Discrete Dynamics in Nature and Society 2016: 1–11. doi:10.1155/2016/8061069.
   Web of Science ®Google Scholar
• Liu, W., and K. C. Seto. 2008. “Using the ART-MMAP Neural Network to Model and Predict Urban Growth: A Spatiotemporal Data Mining Approach.” Environment and Planning B: Planning and Design 35 (2): 296–317. doi:10.1068/b3312.
   Web of Science ®Google Scholar
• Mahiny, A. S., and B. J. Turner. 2003. Proceedings of the 7th International Conference on GeoComputation.“Modeling past Vegetation Change through Remote Sensing and GIS: A Comparison of Neural Networks and Logistic Regression Methods.” The 7th International Conference on GeoComputation, University of Southampton, UK (2003)..
   Google Scholar
• Mas, J. F., and J. J. Flores. 2008. “The Application of Artificial Neural Networks to the Analysis of Remotely Sensed Data.” International Journal of Remote Sensing 29 (3): 617–663. doi:10.1080/01431160701352154.
   Web of Science ®Google Scholar
• Mas, J. F., M. Kolb, M. Paegelow, M. T. C. Olmedo, and T. Houet. 2014. “Inductive Pattern-Based Land Use/Cover Change Models: A Comparison of Four Software Packages.” Environmental Modelling and Software 51: 94–111. doi:10.1016/j.envsoft.2013.09.010.
   Web of Science ®Google Scholar
• Moulds, S., W. Buytaert, and A. Mijic. 2018. “Data Descriptor: A Spatio-Temporal Land Use and Land Cover Reconstruction for India from 1960-2010.” Scientific Data 5: 1–11. doi:10.1038/sdata.2018.159.
   PubMed Web of Science ®Google Scholar
• Munroe, D. K., J. Southworth, and C. M. Tucker. 2004. “Modeling Spatially and Temporally Complex Land-Cover Change: The Case of Western Honduras.” Professional Geographer 56 (4): 544–559. doi:10.1111/j.0033-0124.2004.00447.x.
   Web of Science ®Google Scholar
• Munshi, T., M. Zuidgeest, M. Brussel, and M. van Maarseveen. 2014. “Logistic Regression and Cellular Automata-Based Modelling of Retail, Commercial and Residential Development in the City of Ahmedabad, India.” Cities 39: 68–86. doi:10.1016/j.cities.2014.02.007.
   Web of Science ®Google Scholar
• Munthali, M. G., N. Davis, A. M. Adeola, J. O. Botai, J. M. Kamwi, H. L. W. Chisale, and O. O. I. Orimoogunje. 2019. “Local Perception of Drivers of Land-Use and Land- Cover Change Dynamics across Dedza District, Central Malawi Region.” Sustainability 11 (3): 832. doi:10.3390/su11030832.
   Web of Science ®Google Scholar
• Nourqolipour, R., A. R. B. M. Shariff, S. K. Balasundram, N. B. Ahmad, A. M. Sood, and T. Buyong. 2016. “Predicting the Effects of Urban Development on Land Transition and Spatial Patterns of Land Use in Western Peninsular Malaysia.” Applied Spatial Analysis and Policy 9 (1): 1–19. doi:10.1007/s12061-014-9128-9.
   Web of Science ®Google Scholar
• Overmars, K. P., and P. H. Verburg. 2005. “Analysis of Land Use Drivers at the Watershed and Household Level: Linking Two Paradigms at the Philippine Forest Fringe.” International Journal of Geographical Information Science 19 (2): 125–152. doi:10.1080/13658810410001713380.
   Web of Science ®Google Scholar
• Ozturk, D. 2015. “Urban Growth Simulation of Atakum (Samsun, Turkey) Using Cellular Automata-Markov Chain and Multi-Layer Perceptron-Markov Chain Models.” Remote Sensing 7 (5): 5918–5950. doi:10.3390/rs70505918.
   Web of Science ®Google Scholar
• Peng, J., M. Zhao, X. Guo, Y. Pan, and Y. Liu. 2017. “Spatial-Temporal Dynamics and Associated Driving Forces of Urban Ecological Land: A Case Study in Shenzhen City, China.” Habitat International 60: 81–90. doi:10.1016/j.habitatint.2016.12.005.
   Web of Science ®Google Scholar
• Poelmans, L., and A. Van Rompaey. 2009. “Detecting and Modelling Spatial Patterns of Urban Sprawl in Highly Fragmented Areas: A Case Study in the Flanders-Brussels Region.” Landscape and Urban Planning 93 (1): 10–19. doi:10.1016/j.landurbplan.2009.05.018.
   Web of Science ®Google Scholar
• Poelmans, L., and A. Van Rompaey. 2010. “Complexity and Performance of Urban Expansion Models.” Computers, Environment and Urban Systems 34 (1): 17–27. doi:10.1016/j.compenvurbsys.2009.06.001.
   Web of Science ®Google Scholar
• Pontius, R. G., E. Shusas, and M. McEachern. 2004. “Detecting Important Categorical Land Changes while Accounting for Persistence.” Agriculture, Ecosystems and Environment 101 (2–3): 251–268. doi:10.1016/j.agee.2003.09.008.
   Web of Science ®Google Scholar
• Pontius, R. G., and L. C. Schneider. 2001. “Land-cover Change Model Validation by an ROC Method for the Ipswich Watershed, Massachusetts, USA.” Agriculture, Ecosystems and Environment 85: 239–248. doi:10.1016/S0167-8809(01)00187-6.
   Web of Science ®Google Scholar
• Pontius, R. G., and M. Millones. 2011. “Death to Kappa: Birth of Quantity Disagreement and Allocation Disagreement for Accuracy Assessment.” International Journal of Remote Sensing 32 (15): 4407–4429. doi:10.1080/01431161.2011.552923.
   Web of Science ®Google Scholar
• Riahi, K., D. P. van Vuuren, E. Kriegler, J. Edmonds, B. C. O’Neill, S. Fujimori, N. Bauer, et al. 2017. “The Shared Socioeconomic Pathways and Their Energy, Land Use, and Greenhouse Gas Emissions Implications: An Overview.” Global Environmental Change 42 :153–168. doi:10.1016/j.gloenvcha.2016.05.009.
   Web of Science ®Google Scholar
• Roy, P. S., and A. Roy. 2010. “Land Use and Land Cover Change in India: A Remote Sensing & GIS Perspective.” Journal of the Indian Institute of Science 90 (4): 489–502.
   Google Scholar
• Roy, P. S., A. Roy, P. K. Joshi, M. P. Kale, V. K. Srivastava, S. K. Srivastava, R. S. Dwevidi, et al. 2015. “Development of Decadal (1985-1995-2005) Land Use and Land Cover Database for India.” Remote Sensing 7 (3): 2401–2430. doi:10.3390/rs70302401.
   Web of Science ®Google Scholar
• Schultz, A., R. Wieland, and G. Lutze. 2000. “Neural Networks in Agroecological Modelling - Stylish Application or Helpful Tool?” Computers and Electronics in Agriculture 29 (1–2): 73–97. doi:10.1016/S0168-1699(00)00137-X.
   Web of Science ®Google Scholar
• Serneels, S., M. Y. Said, and E. F. Lambin. 2001. “Land Cover Changes around a Major East African Wildlife Reserve: The Mara Ecosystem (Kenya).” International Journal of Remote Sensing 22 (17): 3397–3420. doi:10.1080/01431160152609236.
   Web of Science ®Google Scholar
• Singh, A. K., and S. Giri. 2018. “Subarnarekha River: The Gold Streak of India.” The Indian Rivers. Springer Hydrogeology. doi:10.1007/978-981-10-2984-4.
   Google Scholar
• Song, X. P., M. C. Hansen, S. V. Stehman, P. V. Potapov, A. Tyukavina, E. F. Vermote, and J. R. Townshend. 2018. “Global Land Change from 1982 to 2016.” Nature 560 (7720): 639–643. doi:10.1038/s41586-018-0411-9.
   PubMed Web of Science ®Google Scholar
• Tian, H., K. Banger, T. Bo, and V. K. Dadhwal. 2014. “History of Land Use in India during 1880-2010: Large-Scale Land Transformations Reconstructed from Satellite Data and Historical Archives.” Global and Planetary Change 121: 78–88. doi:10.1016/j.gloplacha.2014.07.005.
   Web of Science ®Google Scholar
• Tu, J. V. 1996. “Advantages and Disadvantages of Using Artificial Neural Networks versus Logistic Regression for Predicting Medical Outcomes.” Journal of Clinical Epidemiology 49 (11): 1225–1231. doi:10.1016/S0895-4356(96)00002-9.
   PubMed Web of Science ®Google Scholar
• Turner, B. L. 2006. “Land Change as a Forcing Function in Global Environmental Change.” In Our Earth’s Changing Land: An Encyclopedia of Land Use and Land Cover Change, 1 (A-K), edited by H. J. Geist, xxv–xxxii. Westport< London: Greenwood Press.
   Google Scholar
• Václavík, T., and J. Rogan. 2009. “Identifying Trends in Land Use/Land Cover Changes in the Context of Post-Socialist Transformation in Central Europe: A Case Study of the Greater Olomouc Region, Czech Republic.” GIScience & Remote Sensing 46 (1): 54–76. doi:10.2747/1548-1603.46.1.54.
   Web of Science ®Google Scholar
• Veldkamp, A., and E. F. Lambin. 2001. “Predicting Land Use Change.” Agriculture, Ecosystems and Environment 85 (2001): 1–6. doi:10.1016/S0167-8809(01)00199-2.
   Web of Science ®Google Scholar
• Wear, D. N., and P. Bolstad. 1998. “Land-Use Changes in Southern Appalachian Landscapes: Spatial Analysis and Forecast Evaluation.” Ecosystems 1 (6): 575–594. doi:10.1007/s100219900052.
   Web of Science ®Google Scholar
• Wu, F. 2002. “Calibration of Stochastic Cellular Automata: The Application to Rural-Urban Land Conversions.” International Journal of Geographical Information Science 16 (8): 795–818. doi:10.1080/13658810210157769.
   Web of Science ®Google Scholar
• Xie, C., B. Huang, C. Claramunt, and M. Chandramouli. 2000. “Spatial Logistic Regression and GIS to Model Rural-Urban Land Conversion.” Journal of Polymer Science. Part A-1, Polymer Chemistry 18 (11): 3133–3147.
   Google Scholar
• Yüzer, M. A., and Ş. Yüzer. 2006. “Cellular Automata Tabanlı LUCAM Modeli Ile Istanbul’un Gelişim Ve Dönüşümüne Ilişkin Makro Form Simülasyonları.” Journal of Istanbul Kültür University 4: 231–244.
   Google Scholar
• Zhang, D., C. Narteau, and O. Rozier. 2010. “Morphodynamics of Barchan and Transverse Dunes Using a Cellular Automaton Model.” Journal of Geophysical Research: Earth Surface 115 (3). doi:10.1029/2009JF001620.
   Web of Science ®Google Scholar