Analysis of the dynamics of land use change and its prediction based on the integration of remotely sensed data and CA-Markov model, in the upstream Citarum Watershed, West Java, Indonesia

References

• Adam, E., O. Mutanga, J. Odindi, and E. M. Abdel-Rahman. 2014. “Land-use/cover Classification in a Heterogeneous Coastal Landscape Using RapidEye Imagery: Evaluating the Performance of Random Forest and Support Vector Machines Classifiers.” International Journal of Remote Sensing 35 (10): 3440–3458.
   Web of Science ®Google Scholar
• Ahmad, A. 2012. “Analysis of Maximum Likelihood Classification.” Applied Mathematical Sciences 6 (129): 6425–6436.
   Google Scholar
• Ahmed, B., R. Ahmed, and X. Zhu. 2013. “Evaluation of Model Validation Techniques in Land Cover Dynamics.” ISPRS International Journal of Geo-Information 2 (3): 577–597.
   Web of Science ®Google Scholar
• Alexakis, D. D., M. G. Grillakis, A. G. Koutroulis, A. Agapiou, K. Themistocleous, I. K. Tsanis, S. Michaelides, S. Pashiardis, C. Demetriou, et al. 2014. “GIS and Remote Sensing Techniques for Assessment of Land Use Change Impact on Hydrology: The Case Study of Yialis Basin in Cyprus.” Natural Hazards and Earth System Science 14: 413–426.
   Web of Science ®Google Scholar
• Al-Fares, W. 2013. Historical Land use/ Land Cover Classification Using Remote Sensing. Springer Briefs in Geography. Springer. doi:10.1007/978-3-319-00624-6.
   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: 265–275.
   Web of Science ®Google Scholar
• Arslan, O. 2009. “A Novel Confidence Estimation Method for Neural Networks in Multispectral Image Classification.” International Journal of Digital Earth 2 (4): 343–358.
   Web of Science ®Google Scholar
• Asdak, C. 1995. Hydrology and Watershed Management. Yogyakarta: Gadjah Mada University Press. In Indonesian.
   Google Scholar
• BAPPENAS. 2013. Integrated Water Resources Management of Citarum River (March 2013 Edition). Jakarta: Roadmap Coordination Management Unit.
   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: 1011–1024.
   Web of Science ®Google Scholar
• Bronto, S., and U. Hartono. 2006. “Potential Geological Resources in the Bandung Basin and Surrounding Areas.” Indonesian Journal of Geology 1 (1): 9–18. In Indonesian.
   Google Scholar
• Chavez, P. S., Jr. 1988. “An Improved Dark-Object Subtraction Technique for Atmospheric Scattering Correction of Multispectral Data.” Remote Sensing of Environment 24: 459–479.
   Web of Science ®Google Scholar
• Civco, D. L. 1993. “Artificial Neural Networks for Land-Cover Classification and Mapping.” International Journal of Geographical Information Systems. doi:10.1080/02693799308901949.
   Web of Science ®Google Scholar
• Frohn, R. C., B. C. Autrey, C. R. Lane, and M. Reif. 2011. “Segmentation and Object-Oriented Classification of Wetlands in a Karst Florida Landscape Using Multi-Season Landsat-7 ETM+Imagery.” International Journal of Remote Sensing 32 (5): 1471–1489.
   Web of Science ®Google Scholar
• Gong, W., L. Yuan, W. Fanc, and P. Stott. 2015. “Analysis and Simulation of Land use Spatial Pattern in Harbin Prefecture Based on Trajectories and Cellular Automata – Markov Modelling.” International Journal of Applied Earth Observation and Geoinformation 34: 207–216.
   Web of Science ®Google Scholar
• Guan, D., H. F. Li, T. Inohae, W. Su, T. Nagaie, and K. Hakao. 2011. “Modeling Urban Land use Change by the Integration of Cellular Automaton and Markov Model.” Ecological Modelling 222: 3761–3772.
   Web of Science ®Google Scholar
• Hadjimitsis, D. G., G. Papadavid, A. Agapiou, K. Themistocleous, M. G. Hadjimitsis, A. Retalis, S. Michaelides, N. Chrysoulakis, L. Toulios, and C. R. I. Clayton. 2010. “Atmospheric Correction for Satellite Remotely Sensed Data Intended for Agricultural Applications: Impact on Vegetation Indices.” Natural Hazards and Earth System Science 10: 89–95. doi:10.5194/nhess-10-89-2010.
   Web of Science ®Google Scholar
• Halmy, M. W. A., P. E. Gessler, J. A. Hicke, and B. B. Salem. 2015. “Land use/Land Cover Change Detection and Prediction in the Northwestern Coastal Desert of Egypt Using Markov-CA.” Applied Geography 63: 101–112.
   Web of Science ®Google Scholar
• Hereher, M. E. 2017. “Effects of Land Use/Cover Change on Regional Land Surface Temperatures: Severe Warming from Drying Toshka Lakes, the Western Desert of Egypt.” Natural Hazards 88 (1789). doi:10.1007/s11069-017-2946-8.
   Google Scholar
• Hoglnd, J., N. Billor, and N. Anderson. 2013. “Comparison of Standard Maximum Likelihood Classification and Polytomous Logistic Regression Used in Remote Sensing.” European Journal of Remote Sensing 46: 623–640.
   Web of Science ®Google Scholar
• Huang, S. L., S. H. Wang, and W. W. Budd. 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.
   Web of Science ®Google Scholar
• Huth, J., C. Kuenzer, T. Wehrmann, S. Gebhardt, V. Q. Tuan, and S. Dech. 2012. “Land Cover and Land Use Classification with TWOPAC: Towards Automated Processing for Pixel- and Object-Based Image Classification.” Remote Sensing 4: 2530–2553.
   Web of Science ®Google Scholar
• Hyandye, C., C. G. Mandara, and J. Safari. 2015. “GIS and Logit Regression Model Applications in Land Use/Land Cover Change and Distribution in Usangu Catchment.” American Journal of Remote Sensing 3 (1): 6–16. doi:10.11648/j.ajrs.20150301.12.
   Google Scholar
• Kubal, C., D. Haase, V. Mayer, and S. Scheuer. 2009. “Integrated Urban Flood Risk Assessment – Adapting a Multicriteria Approach to a City.” Natural Hazards and Earth System Science 9: 1881–1895.
   Web of Science ®Google Scholar
• Lanfredi, M., R. Lasaponara, T. Simoniello, V. Cuomo, and M. Macchiato. 2003. “Multiresolution Spatial Characterization of Land Degradation Phenomena in Southern Italy From 1985 to 1999 Using NOAA-AVHRR NDVI Data.” Geophysical Research Letters 30 (2): 4181–1081. doi:10.1029/2002GL015514.
   Web of Science ®Google Scholar
• Lee, S., and R. G. Lathrop. 2011. “Sub-pixel Estimation of Urban Land Cover Components with Linear Mixture Model Analysis and Landsat Thematic Mapper Imagery.” International Journal of Remote Sensing 26 (22): 4885–4905.
   Google Scholar
• Li, D. 2010. “Remotely Sensed Images and GIS Data Fusion for Automatic Change Detection.” International Journal of Image and Data Fusion 1: 99–108.
   Google Scholar
• Lindgren, D. T. 1985. Land use Planning and Remote Sensing. Remote Sensing of Earth Resources and Environment. Dordrecht: Springer.
   Google Scholar
• Lu, D., Q. Chen, G. Wang, L. Liu, G. Li, and E. Moran. 2016. “A Survey of Remote Sensing-Based Aboveground Biomass Estimation Methods in Forest Ecosystems.” International Journal of Digital Earth. doi:10.1080/17538947.2014.990526.
   Web of Science ®Google Scholar
• Luca, C., M. Michele, and M. Silvia. 2013. Investigating the relationship between land cover and vulnerability to climate change in Dares Salaam. Working Paper, Rome: Sapienza University.
   Google Scholar
• Mallinis, G., and N. Koutsias. 2008. “Spectral and Spatial-Based Classification for Broad-Scale Land Cover Mapping Based on Logistic Regression.” Sensors 8: 8067–8085. doi:10.3390/s8128067.
   PubMed Web of Science ®Google Scholar
• Moiwo, J. P., W. X. Lu, Y. S. Zhao, Y. H. Yang, and Y. M. Yang. 2010. “Impact of Land use on Distributed Hydrological Processes in the Semi-Arid Wetland Ecosystem of Western Jilin.” Hydrological Processes 24: 492–503.
   Web of Science ®Google Scholar
• Mousivand, A. J., A. A. Sarab, and S. Shayan. 2007. “A New Approach of Predicting Land use and Land Cover Changes by Satellite Imagery and Markov Chain Model (Case Study: Tehran).” MSc thesis, Tarbiat Modares University, Tehran, Iran.
   Google Scholar
• Muin, S. F., R. Boer, and Y. Suharnoto. 2015. “Modeling and Analysis of Loss due to Flood Disaster in Upper Citarum Basin.” Land and Climate Journal 39 (2): 73–83. In Indonesian.
   Google Scholar
• Muller, M. R., and J. Middleton. 1994. “A Markov Model of Land-use Change Dynamics in the Niagara Region, Ontario, Canada.” Landscape Ecology 9: 151–157.
   Web of Science ®Google Scholar
• Nash, N. 2016. “Detection and Accuracy Assessment of Mountain Pine Beetle Infestation Using Landsat 8 OLI and worldview02 Satellite Imagery, Lake Tahoe Basin-Nevada and California.” M.Sc. thesis, Faculty of the USC Graduated School. University of Southern California.
   Google Scholar
• Newson, M. 2002. Land, Water and Development: Sustainable Management of River Basin Systems. 2nd ed. London: Taylor & Francis E-Library, Routledge.
   Google Scholar
• Owrangi, A. M., R. Lannigan, and S. P. Simonovic. 2014. “Interaction Between Land-use Change, Flooding and Human Health in Metro Vancouver, Canada.” Natural Hazards 72 (1219). doi:10.1007/s11069-014-1064-0.
   Google Scholar
• Paegelow, M., O. M. T. Camacho, and J. F. Mas. 2018. “Lecture Notes in Geoinformation and Cartography.” Geomatic Approaches for Modeling Land Change Scenarios, 112: 53–80. doi:10.1007/978-3-319-60801-3_4.
   Google Scholar
• Paegelow, M., O. M. T. Camacho, J. F. Mas, and T. Houet. 2014. “Benchmarking of LUCC Modelling Tools by Various Validation Techniques and Error Analysis.” Cybergeo, 1–30. doi:10.4000/cybergeo.26610.
   Google Scholar
• Pal, M. 2009. “Extreme-Learning-Machine-Based Land Cover Classification.” International Journal of Remote Sensing 30 (14): 3835–3841.
   Web of Science ®Google Scholar
• Pal, M. 2011. “Modified Nearest Neighbour Classifier for Hyperspectral Data Classification.” International Journal of Remote Sensing 32 (24): 9207–9217.
   Web of Science ®Google Scholar
• Pal, M., and P. M. Mather. 2003. “An Assessment of the Effectiveness of Decision Tree Methods for Land Cover Classification.” Remote Sensing of Environment 86 (4): 554–565.
   Web of Science ®Google Scholar
• Park, N. W., K. H. Chi, and B. D. Kwon. 2003. “Geostatistical Integration of Spectral and Spatial Information for Land-Cover Mapping Using Remote Sensing Data.” Geosciences Journal 7: 335–341. doi:10.1007/BF02919565.
   Web of Science ®Google Scholar
• Pontius, R. G., W. Boersma, J. C. Castella, K. Clarke, T. Nijs, C. Dietzel, and P. H. Verburg. 2008. “Comparing the Input, Output, and Validation Maps for Several Models of Land Change.” The Annals of Regional Science 42 (1): 11–37. doi:10.1007/s00168-007-0138-2.
   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
• Portengen, L. 2014. “Landsat Derived Snowline Variations in Nyainqêntanglha Mountains on The Tibetan Plateau.” Bachelor Thesis, TU Delft, University of Technology.
   Google Scholar
• Pratiwi, D. T. 2011. “Flow Hydrograph Analysis Using HEC-HMS.” Thesis, Department of Geophysics and Meteorology, Bogor Agricultural Institute. In Indonesian.
   Google Scholar
• Raharjo, P. D. 2014. “Multi-temporal Remote Sensing Application for Runoff Study due to Change of Land Cover, Case in Grompol Watershed Central Java.” Thesis, Faculty of Geography, Gadjah Mada University. In Indonesian.
   Google Scholar
• Richards, J. A., and X. Jia. 2006. Remote Sensing Digital Image Analysis: An Introduction. Berlin: Springer.
   Google Scholar
• Sarath, T., and G. Nagalakshmi. 2014. “An Land Cover Fuzzy Logic Classification by Maxmimum Likelohood.” International Journal of Computer Trends and Technology 13 (2): 56–60.
   Google Scholar
• Shooshtari, S. J., and M. Gholamalifard. 2015. “Scenario-based Land Cover Change Modeling and its Implications for Landscape Pattern Analysis in the Neka Watershed, Iran.” Remote Sens Appl Soc Environ 1: 1–19.
   Google Scholar
• Silitonga. 1973. Geology map of Bandung, Java. Bandung: Center for Geological Research and Development, Director General of Geology and Mineral Resources. In Indonesian.
   Google Scholar
• Tarantino, C., P. Blonda, and G. Pasquariello. 2007. “Remote Sensed Data for Automatic Detection of Land-use Changes due to Human Activity in Support to Landslide Studies.” Natural Hazards 41: 245–267. doi:10.1007/s11069-006-9041-x.
   Web of Science ®Google Scholar
• Thomas, H., and H. M. Laurence. 2006. “Modeling and Projecting Land-use and Land-Cover Changes with a Cellular Automaton in Considering Landscape Trajectories: An Improvement for Simulation of Plausible Future States.” EARSeLeProc 5: 63–76.
   Google Scholar
• Treitz, P. M., P. J. Howard, and P. Gong. 1992. “Application of Satellite and GIS Technologies for Land-Cover and Land-use Mapping at the Rural-Urban Fringe: A Case Study.” Photogrammetric Engineering and Remote Sensing 58 (4): 439–448.
   Web of Science ®Google Scholar
• Turnbull, L., J. Wainwright, and R. E. Brazier. 2010. “Changes in Hydrology and Erosion Over a Transition from Grassland to Shrubland.” Hydrological Processes 24: 393–414.
   Web of Science ®Google Scholar
• USGS. 2013a. Landsat Missions: Frequently Asked Questions About the Landsat Missions US Geological Survey. Last modified: 5/30/123. Landsat.usgs.gov.
   Google Scholar
• USGS. 2013b. Using the US Geological survey Landsat 8 product. Last modified: 5/30/123. Landsat7.usgs.gov.
   Google Scholar
• van Vliet, J., A. K. Bregt, D. G. Brown, H. van Delden, S. Heckbert, and P. H. Verburg. 2016. “A Review of Current Calibration and Validation Practices in Land-Change Modeling.” Environmental Modelling and Software 82: 174–182.
   Web of Science ®Google Scholar
• van Vliet, J., A. K. Bregt, and A. Hagen-zanker. 2011. “Revisiting Kappa to Account for Change in the Accuracy Assessment of Land-use Change Models.” Ecological Modelling 222: 1367–1375.
   Web of Science ®Google Scholar
• Verrall, R. J. 1991. “Chain Ladder and Makximum Likelohood.” JIA 118: 489–499.
   Google Scholar
• Wang, S. Q., X. Q. Zheng, and X. B. Zang. 2012. “Accuracy Assessments of Land use Change Simulation Based on Markov-Cellular Automata Model.” Procedia Environmental Sciences 13: 1238–1245.
   Google Scholar
• Yang, X., X. C. Zheng, and R. Chen. 2014. “A Land use Change Model: Integrating Landscape Pattern Indexes and Markov-CA.” Ecological Modelling 283: 1–7.
   Web of Science ®Google Scholar
• Yang, X., X. Q. Zheng, and L. N. Lv. 2012. “A Spatiotemporal Model of Land Use Change Based on ant Colony Optimization, Markov Chain and Cellular Automata.” Ecological Modelling 233: 11–19.
   Web of Science ®Google Scholar
• Yulianto, F., I. Prasasti, J. M. Pasaribu, H. L. Fitriana, Haryani N.S. Zylshal, and P. Sofan. 2016. “The Dynamics of Land Use/Land Cover Change Modeling and Their Implication for the flood Damage Assessment in the Tondano Watershed, North Sulawesi, Indonesia.” Modeling Earth Systems and Environment 2 (47): 1–20.
   Google Scholar
• Zaidi, S. M., A. Akbari, A. A. Samah, N. S. Kon, and J. I. A. Gisen. 2017. “Landsat-5 Time Series Analysis for Land Use/Land Cover Change Detection Using NDVI and Semi-Supervised Classification Techniques.” Polish Journal of Environmental Studies 26 (6): 2833–2840.
   Web of Science ®Google Scholar
• Zope, P. E., T. I. Eldho, and V. Jothiprakash. 2017. “Hydrological Impacts of Land Use – Land Cover Change and Detention Basins on Urban Flood Hazard: A Case Study of Poisar River Basin, Mumbai, India.” Natural Hazards 87: 1267–1283. doi:10.1007/s11069-017-2816-4.
   Web of Science ®Google Scholar