High-resolution urban change modeling and flood exposure estimation at a national scale using open geospatial data: A case study of the Philippines
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Ronald C. Estoque | Ram Avtar | Xuecao Li | Damasa B. Magcale-Macandog | Brian A. Johnson | Pankaj Kumar | Rajarshi Dasgupta | R. Avtar | R. Estoque | R. Dasgupta | B. Johnson | Pankaj Kumar | Xuecao Li | D. Magcale-Macandog
[1] J. Eom,et al. The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview , 2017 .
[2] Jakob van Zyl,et al. The Shuttle Radar Topography Mission (SRTM): a breakthrough in remote sensing of topography , 2001 .
[3] Ian H. Witten,et al. The WEKA data mining software: an update , 2009, SKDD.
[4] Scott Kulp,et al. CoastalDEM: A global coastal digital elevation model improved from SRTM using a neural network , 2018 .
[5] G. Di Baldassarre,et al. GFPLAIN250m, a global high-resolution dataset of Earth’s floodplains , 2019, Scientific Data.
[6] Paula Beatrice M. Macandog,et al. Participatory land-use approach for integrating climate change adaptation and mitigation into basin-scale local planning , 2017 .
[7] Yoshio Yamaguchi,et al. Land Cover Classification of Palsar Images by Knowledge Based Decision Tree Classifier and Supervised Classifiers Based on SAR Observables , 2011 .
[8] J. Eom,et al. Projecting Global Urban Area Growth Through 2100 Based on Historical Time Series Data and Future Shared Socioeconomic Pathways , 2019, Earth's Future.
[9] Y. Zeng,et al. Hidden Loss of Wetlands in China , 2019, Current Biology.
[10] Brian C. O’Neill,et al. Mapping global urban land for the 21st century with data-driven simulations and Shared Socioeconomic Pathways , 2020, Nature Communications.
[11] Xia Li,et al. Data mining of cellular automata's transition rules , 2004, Int. J. Geogr. Inf. Sci..
[12] B. Pijanowski,et al. Using neural networks and GIS to forecast land use changes: a Land Transformation Model , 2002 .
[13] C. L. Anderson,et al. Definitions of “rural” and “urban” and understandings of economic transformation: Evidence from Tanzania , 2020, Journal of rural studies.
[14] S. Cessie,et al. Ridge Estimators in Logistic Regression , 1992 .
[15] Kris A. Johnson,et al. Estimates of present and future flood risk in the conterminous United States , 2017 .
[16] Roger White,et al. Cellular Automata and Fractal Urban Form: A Cellular Modelling Approach to the Evolution of Urban Land-Use Patterns , 1993 .
[17] Julea Andreea Maria,et al. Operating procedure for the production of the Global Human Settlement Layer from Landsat data of the epochs 1975, 1990, 2000, and 2014 , 2016 .
[18] B. O’Neill,et al. Global urbanization projections for the Shared Socioeconomic Pathways , 2017 .
[19] Andrés Manuel García,et al. Cellular automata models for the simulation of real-world urban processes: A review and analysis , 2010 .
[20] Kotaro Iizuka,et al. Modeling Future Urban Sprawl and Landscape Change in the Laguna de Bay Area, Philippines , 2017 .
[21] Iryna Dronova,et al. Modeling stormwater management at the city district level in response to changes in land use and low impact development , 2017, Environ. Model. Softw..
[22] J. Pekel,et al. High-resolution mapping of global surface water and its long-term changes , 2016, Nature.
[23] Yatao Zhang,et al. Mapping fine-scale population distributions at the building level by integrating multisource geospatial big data , 2017, Int. J. Geogr. Inf. Sci..
[24] Xiaohua Tong,et al. Dynamic land use change simulation using cellular automata with spatially nonstationary transition rules , 2018 .
[25] Brian Alan Johnson,et al. Local Climate Zone (LCZ) Map Accuracy Assessments Should Account for Land Cover Physical Characteristics that Affect the Local Thermal Environment , 2019, Remote. Sens..
[26] Fulong Wu,et al. Calibration of stochastic cellular automata: the application to rural-urban land conversions , 2002, Int. J. Geogr. Inf. Sci..
[27] Xia Li,et al. Global projections of future urban land expansion under shared socioeconomic pathways , 2020, Nature Communications.
[28] Chitresh Saraswat,et al. Assessment of stormwater runoff management practices and governance under climate change and urbanization: An analysis of Bangkok, Hanoi and Tokyo , 2016 .
[29] E. Luna,et al. Hidden disasters: Recurrent flooding impacts on educational continuity in the Philippines , 2017 .
[30] Frieke Van Coillie,et al. Quality of Crowdsourced Data on Urban Morphology—The Human Influence Experiment (HUMINEX) , 2017 .
[31] Yuji Murayama,et al. Examining the potential impact of land use/cover changes on the ecosystem services of Baguio city, the Philippines: A scenario-based analysis , 2012 .
[32] Makoto Ooba,et al. Heat health risk assessment in Philippine cities using remotely sensed data and social-ecological indicators , 2020, Nature Communications.
[33] J. Schilling,et al. The Nexus of Climate Change, Land Use, and Conflicts , 2019, Current Climate Change Reports.
[34] Kris A. Johnson,et al. Validation of a 30 m resolution flood hazard model of the conterminous United States , 2017 .
[35] M. Huijbregts,et al. Global patterns of current and future road infrastructure , 2018 .
[36] Xiaoping Liu,et al. Integrating ensemble-urban cellular automata model with an uncertainty map to improve the performance of a single model , 2015, Int. J. Geogr. Inf. Sci..
[37] K. Fukushi,et al. Assessment of future flood inundations under climate and land use change scenarios in the Ciliwung River Basin, Jakarta , 2018 .
[38] Man-Hyung Lee,et al. The Development and Application of the Urban Flood Risk Assessment Model for Reflecting upon Urban Planning Elements , 2019, Water.
[39] M. Miyamoto,et al. Flood damage assessment in the Pampanga river basin of the Philippines , 2016 .
[40] Peng Gong,et al. Urban growth models: progress and perspective , 2016 .
[41] Xi-Ying Zhang,et al. A predator-prey interaction between a marine Pseudoalteromonas sp. and Gram-positive bacteria , 2020, Nature Communications.
[42] Yuyu Zhou,et al. Annual maps of global artificial impervious area (GAIA) between 1985 and 2018 , 2020 .
[43] Le Yu,et al. A systematic sensitivity analysis of constrained cellular automata model for urban growth simulation based on different transition rules , 2014, Int. J. Geogr. Inf. Sci..
[44] Yuyu Zhou,et al. An improved urban cellular automata model by using the trend-adjusted neighborhood , 2020, Ecological Processes.
[45] Achim Roth,et al. Accuracy assessment of the global TanDEM-X Digital Elevation Model with GPS data , 2018 .
[46] Eric Koomen,et al. Comparing the input, output, and validation maps for several models of land change , 2008 .
[47] A. Onishi,et al. A land cover map accuracy metric for hydrological studies , 2017 .