Volume 43 - Article 54 | Pages 1563–1606 Author has provided data and code for replicating results

A spatial population downscaling model for integrated human-environment analysis in the United States

By Hamidreza Zoraghein, Brian C. O'Neill

Print this page  

 

References

Anselin, L. (1995). Local indicators of spatial association – LISA. Geographical analysis 27(2): 93–115.

Download reference in RIS | BibTeX

Balk, D., Leyk, S., Jones, B., Montgomery, M.R., and Clark, A. (2018). Understanding urbanization: A study of census and satellite-derived urban classes in the United States, 1990–2010. PLoS One 13(12): e0208487.

Weblink doi:10.1371/journal.pone.0208487
Download reference in RIS | BibTeX

Balk, D.L., Deichmann, U., Yetman, G., Pozzi, F., Hay, S.I., and Nelson, A. (2006). Determining global population distribution: Methods, applications and data. Advances in Parasitology 62: 119–156.

Weblink doi:10.1016/S0065-308X(05)62004-0
Download reference in RIS | BibTeX

Ballas, D., Clarke, G.P., and Wiemers, E. (2005). Building a dynamic spatial microsimulation model for Ireland. Population, Space and Place 11(3): 157–172.

Weblink doi:10.1002/psp.359
Download reference in RIS | BibTeX

Bengtsson, M., Shen, Y., and Oki, T. (2006). A SRES-based gridded global population dataset for 1990–2100. Population and Environment 28(2): 113–131.

Weblink doi:10.1007/s11111-007-0035-8
Download reference in RIS | BibTeX

Bhaduri, B., Bright, E., Coleman, P., and Urban, M. (2007). LandScan USA: A high-resolution geospatial and temporal modeling approach for population distribution and dynamics. GeoJournal 69(1–2): 103–117.

Download reference in RIS | BibTeX

Bierwagen, B.G., Theobald, D.M., Pyke, C.R., Choate, A., Groth, P., Thomas, J.V., and Morefield, P. (2010). National housing and impervious surface scenarios for integrated climate impact assessments. Proceedings of the National Academy of Sciences 107(49): 20887–20892.

Weblink doi:10.1073/pnas.1002096107
Download reference in RIS | BibTeX

Braimoh, A.K. and Onishi, T. (2007). Spatial determinants of urban land use change in Lagos, Nigeria. Land Use Policy 24(2): 502–515.

Weblink doi:10.1016/j.landusepol.2006.09.001
Download reference in RIS | BibTeX

Caminade, C., Kovats, S., Rocklov, J., Tompkins, A.M., Morse, A.P., Colón-González, F.J., Stenlund, H., Martens, P., and Lloyd, S.J. (2014). Impact of climate change on global malaria distribution. Proceedings of the National Academy of Sciences 111(9): 3286–3291.

Weblink doi:10.1073/pnas.1302089111
Download reference in RIS | BibTeX

Columbia University – Center for International Earth Science Information Network – CIESIN (2018). Gridded Population of the World, Version 4 (GPWv4): Population Count, Revision 11. (Gridded Population of the World, Version 4 (GPWv4): Population Count, Revision 11.).

Download reference in RIS | BibTeX

Dobson, J.E., Bright, E.A., Coleman, P.R., Durfee, R.C., and Worley, B.A. (2000). LandScan: A global population database for estimating populations at risk. Photogrammetric Engineering and Remote Sensing 66(7): 849–857.

Download reference in RIS | BibTeX

Dodman, D. (2009). Blaming cities for climate change? An analysis of urban greenhouse gas emissions inventories. Environment and Urbanization 21: 185–201.

Weblink doi:10.1177/0956247809103016
Download reference in RIS | BibTeX

Dong, W., Liu, Z., Liao, H., Tang, Q., and Li, X. (2015). New climate and socio-economic scenarios for assessing global human health challenges due to heat risk. Climatic Change 130(4): 505–518.

Weblink doi:10.1007/s10584-015-1372-8
Download reference in RIS | BibTeX

Ewing, R. and Rong, F. (2008). The impact of urban form on U.S. residential energy use. Housing Policy Debate 19(1): 1–30.

Weblink doi:10.1080/10511482.2008.9521624
Download reference in RIS | BibTeX

Gao, J. and O’Neill, B.C. (2019). Data-driven spatial modeling of global long-term urban land development: The SELECT model. Environmental Modelling and Software 119: 458–471.

Weblink doi:10.1016/j.envsoft.2019.06.015
Download reference in RIS | BibTeX

Gasparrini, A., Guo, Y., Sera, F., Vicedo-Cabrera, A.M., Huber, V., Tong, S., Sousa Zanotti Stagliorio Coelho, M., Nascimento Saldiva, P.H., Lavigne, E., Matus Correa, P., Valdes Ortega, N., Kan, H., Osorio, S., Kyselý, J., Urban, A., Jaakkola, J.J.K., Ryti, N.R.I., Pascal, M., Goodman, P.G., Zeka, A., Michelozzi, P., Scortichini, M., Hashizume, M., Honda, Y., Hurtado-Diaz, M., Cesar Cruz, J., Seposo, X., Kim, H., Tobias, A., Iñiguez, C., Forsberg, B., Åström, D.O., Ragettli, M.S., Guo, Y.L., Wu, C. fu, Zanobetti, A., Schwartz, J., and Armstrong, B. (2017). Projections of temperature-related excess mortality under climate change scenarios. The Lancet Planetary Health 1(9): 360–367.

Weblink doi:10.1016/S2542-5196(17)30156-0
Download reference in RIS | BibTeX

Georgescu, M., Morefield, P.E., Bierwagen, B.G., and Weaver, C.P. (2014). Urban adaptation can roll back warming of emerging megapolitan regions. Proceedings of the National Academy of Sciences 111(8): 2909–2914.

Weblink doi:10.1073/pnas.1322280111
Download reference in RIS | BibTeX

Grübler, A., O’Neill, B., Riahi, K., Chirkov, V., Goujon, A., Kolp, P., Prommer, I., Scherbov, S., and Slentoe, E. (2007). Regional, national, and spatially explicit scenarios of demographic and economic change based on SRES. Technological Forecasting and Social Change 74(7): 980–1029.

Weblink doi:10.1016/j.techfore.2006.05.023
Download reference in RIS | BibTeX

Güneralp, B. and Seto, K.C. (2013). Futures of global urban expansion: Uncertainties and implications for biodiversity conservation. Environmental Research Letters 8(1).

Weblink doi:10.1088/1748-9326/8/1/014025
Download reference in RIS | BibTeX

Hales, S., De Wet, N., Maindonald, J., and Woodward, A. (2002). Potential effect of population and climate changes on global distribution of dengue fever: An empirical model. Lancet 360(9336): 830–834.

Weblink doi:10.1016/S0140-6736(02)09964-6
Download reference in RIS | BibTeX

Hanasaki, N., Fujimori, S., Yamamoto, T., Yoshikawa, S., Masaki, Y., Hijioka, Y., Kainuma, M., Kanamori, Y., Masui, T., Takahashi, K., and Kanae, S. (2013). A global water scarcity assessment under Shared Socio-economic Pathways – Part 2: Water availability and scarcity. Hydrology and Earth System Sciences 9(12): 2393–2413.

Weblink doi:10.5194/hess-17-2393-2013
Download reference in RIS | BibTeX

Hardy, R.D. and Hauer, M.E. (2018). Social vulnerability projections improve sea-level rise risk assessments. Applied Geography 91: 10–20.

Weblink doi:10.1016/j.apgeog.2017.12.019
Download reference in RIS | BibTeX

Homer, C.G., Dewitz, J.A., Yang, L., Jin, S., Danielson, P., Xian, G., Coulston, J., Herold, N.D., Wickham, J.D., and Megown, K. (2015). Completion of the 2011 National Land Cover Database for the conterminous United States-Representing a decade of land cover change information. Photogrammetric Engineering and Remote Sensing 81(5): 345–354.

Weblink doi:10.14358/PERS.81.5.345
Download reference in RIS | BibTeX

Jones, B. and O’Neill, B.C. (2013). Historically grounded spatial population projections for the continental United States. Environmental Research Letters 8(4): 044021.

Weblink doi:10.1088/1748-9326/8/4/044021
Download reference in RIS | BibTeX

Jones, B. and O’Neill, B.C. (2016). Spatially explicit global population scenarios consistent with the Shared Socioeconomic Pathways. Environmental Research Letters 11(8).

Weblink doi:10.1088/1748-9326/11/8/084003
Download reference in RIS | BibTeX

Jones, B., O’Neill, B.C., McDaniel, L., McGinnis, S., Mearns, L.O., and Tebaldi, C. (2015). Future population exposure to US heat extremes. Nature Climate Change 5(7): 652–655.

Weblink doi:10.1038/nclimate2631
Download reference in RIS | BibTeX

Jongman, B., Winsemius, H.C., Aerts, J.C.J.H., Perez, E., Aalst, M.K., Kron, W., and Ward, P.J. (2015). Declining vulnerability to river floods and the global benefits of adaptation. Proceedings of the National Academy of Sciences 112(18): 2271–2280.

Weblink doi:10.1073/pnas.1414439112
Download reference in RIS | BibTeX

Knorr, W., Jiang, L., and Arneth, A. (2016). Climate, CO2 and human population impacts on global wildfire emissions. Biogeosciences 13(1): 267–282.

Weblink doi:10.5194/bg-13-267-2016
Download reference in RIS | BibTeX

Kraft, D. (1988). A software package for sequential quadratic programming. Deutsche Forschungs- und Versuchsanstalt fur Luft- und Raumfahrt, Forschungsbericht.

Download reference in RIS | BibTeX

Landis, J.D. (1994). The California Urban Futures Model: A new generation of metropolitan simulation models. Environment and Planning B: Planning and Design 21(4): 399–420.

Weblink doi:10.1068/b210399
Download reference in RIS | BibTeX

Lehner, F. and Stocker, T.F. (2015). From local perception to global perspective. Nature Climate Change 5(8): 731–734.

Weblink doi:10.1038/nclimate2660
Download reference in RIS | BibTeX

Leyk, S. and Uhl, J.H. (2018). Data descriptor: HISDAC-US, historical settlement data compilation for the conterminous United States over 200 years. Scientific Data 5: 180175.

Weblink doi:10.1038/sdata.2018.175
Download reference in RIS | BibTeX

McDonald, J.F. (2014). What happened to and in Detroit? Urban Studies 51(16): 3309–3329.

Weblink doi:10.1177/0042098013519505
Download reference in RIS | BibTeX

McGranahan, G., Balk, D., and Anderson, B. (2007). The rising tide: assessing the risks of climate change and human settlements in low elevation coastal zones. Environment and Urbanization 19(1): 17–37.

Weblink doi:10.1177/0956247807076960
Download reference in RIS | BibTeX

McKee, J.J., Rose, A.N., Bright, E.A., Huynh, T., and Bhaduri, B.L. (2015). Locally adaptive, spatially explicit projection of US population for 2030 and 2050. Proceedings of the National Academy of Sciences 112(5): 1344–1349.

Weblink doi:10.1073/pnas.1405713112
Download reference in RIS | BibTeX

Meiyappan, P., Dalton, M., O’Neill, B.C., and Jain, A.K. (2014). Spatial modeling of agricultural land use change at global scale. Ecological Modelling 291: 152–174.

Weblink doi:10.1016/j.ecolmodel.2014.07.027
Download reference in RIS | BibTeX

Minnesota Population Center (2016). National Historical Geographic Information System: Version 11.0 [Database].

Weblink doi:10.18128/D050.V11.0
Download reference in RIS | BibTeX

Neumann, B., Vafeidis, A.T., Zimmermann, J., and Nicholls, R.J. (2015). Future coastal population growth and exposure to sea-level rise and coastal flooding: A global assessment. PloS One 10(3): e0118571.

Weblink doi:10.1371/journal.pone.0118571
Download reference in RIS | BibTeX

O’Neill, B.C., Kriegler, E., Ebi, K.L., Kemp-Benedict, E., Riahi, K., Rothman, D.S., Ruijven, B.J., Vuuren, D.P., Birkmann, J., Kok, K., Levy, M., and Solecki, W. (2017). The roads ahead: Narratives for shared socioeconomic pathways describing world futures in the 21st century. Global Environmental Change 42: 169–180.

Weblink doi:10.1016/j.gloenvcha.2015.01.004
Download reference in RIS | BibTeX

Pesaresi, M., Ehrlich, D., Ferri, S., Florczyk, A., Freire, S., Halkia, M., Julea, A., Kemper, T., Soille, P., and Syrris, V. (2016). Operating procedure for the production of the global human settlement layer from Landsat data of the epochs. Ispra: Joint Research Centre, JRC Technical Reports.

Weblink doi:10.2788/253582
Download reference in RIS | BibTeX

Raupach, M.R., Rayner, P.J., and Paget, M. (2010). Regional variations in spatial structure of nightlights, population density and fossil-fuel CO2 emissions. Energy Policy 38(9): 4756–4764.

Weblink doi:10.1016/j.enpol.2009.08.021
Download reference in RIS | BibTeX

Reimann, L., Merkens, J.L., and Vafeidis, A.T. (2018). Regionalized Shared Socioeconomic Pathways: narratives and spatial population projections for the Mediterranean coastal zone. Regional Environmental Change 18(1): 235–245.

Weblink doi:10.1007/s10113-017-1189-2
Download reference in RIS | BibTeX

Rohat, G. (2018). Projecting drivers of human vulnerability under the shared socioeconomic pathways. International Journal of Environmental Research and Public Health 15(3): 554.

Weblink doi:10.3390/ijerph15030554
Download reference in RIS | BibTeX

Rossiter, K. (2011). What are census blocks? [electronic resource]

Weblink https://www.census.gov/newsroom/blogs/random- ...
Download reference in RIS | BibTeX

Santos, A., McGuckin, N., Nakamoto, H.Y., Gray, D., and Liss, S. (2011). Summary of travel trends: 2009 National Household Travel Survey. Washington, D.C: U.S. Department of Transportation Federal Highway Administration (FHWA).

Download reference in RIS | BibTeX

Stimson, R., Bell, M., Corcoran, J., and Pullar, D. (2012). Using a large scale urban model to test planning scenarios in the Brisbane-South East Queensland region. Regional Science Policy and Practice 4(4): 373–392.

Weblink doi:10.1111/j.1757-7802.2012.01082.x
Download reference in RIS | BibTeX

Verburg, P.H., Eck, J.R., Nijs, T.C.M., Dijst, M.J., and Schot, P. (2004). Determinants of land-use change patterns in the Netherlands. Environment and Planning B: Planning and Design 31(1): 125–150.

Weblink doi:10.1068/b307
Download reference in RIS | BibTeX

Vuuren, D.P., Lucas, P.L., and Hilderink, H. (2007). Downscaling drivers of global environmental change: Enabling use of global SRES scenarios at the national and grid levels. Global Environmental Change 17: 114–130.

Weblink doi:10.1016/j.gloenvcha.2006.04.004
Download reference in RIS | BibTeX

Zhang, G., Ge, R., Lin, T., Ye, H., Li, X., and Huang, N. (2018). Spatial apportionment of urban greenhouse gas emission inventory and its implications for urban planning: A case study of Xiamen, China. Ecological Indicators 85: 644–656.

Weblink doi:10.1016/j.ecolind.2017.10.058
Download reference in RIS | BibTeX

Zoraghein, H. and O’Neill, B. (2020). Data Supplement: U.S. state-level projections of the spatial distribution of population consistent with Shared Socioeconomic Pathways.

Weblink doi:10.5281/zenodo.3756179
Download reference in RIS | BibTeX

Zoraghein, H., O’Neill, B.C., and Vernon, C. (2020). Population Gravity Model.

Weblink https://github.com/IMMM-SFA/population_gravity
Download reference in RIS | BibTeX

Zwick, P.D. and Carr, M.H. (2006). Florida 2060: A population distribution scenario for the state of Florida. Gainesville: University of Florida, GeoPlan Center.

Download reference in RIS | BibTeX