Item talk:Q323578

{

 "DOI": {
   "doi": "10.5066/p9bd5v4b",
   "identifiers": [],
   "creators": [
     {
       "name": "Petrasova, Anna",
       "nameType": "Personal",
       "givenName": "Anna",
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         "Center for Geospatial Analytics, NC State University"
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     {
       "name": "Sanchez Salas, Georgina M",
       "nameType": "Personal",
       "givenName": "Georgina M",
       "familyName": "Sanchez Salas",
       "affiliation": [
         "United States Geological Survey"
       ],
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     },
     {
       "name": "Skrip, Megan M",
       "nameType": "Personal",
       "givenName": "Megan M",
       "familyName": "Skrip",
       "affiliation": [
         "Center for Geospatial Analytics, NC State University"
       ],
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           "nameIdentifier": "https://orcid.org/0000-0001-7972-7330",
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     },
     {
       "name": "Collins, Elyssa L.",
       "nameType": "Personal",
       "givenName": "Elyssa L.",
       "familyName": "Collins",
       "affiliation": [
         "null"
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           "nameIdentifier": "https://orcid.org/0000-0002-8054-8468",
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       ]
     },
     {
       "name": "Lawrimore, Margaret A",
       "nameType": "Personal",
       "givenName": "Margaret A",
       "familyName": "Lawrimore",
       "affiliation": [
         "Center for Geospatial Analytics, NC State University"
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           "nameIdentifier": "https://orcid.org/0000-0003-2266-3588",
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       ]
     },
     {
       "name": "Vogler, John B",
       "nameType": "Personal",
       "givenName": "John B",
       "familyName": "Vogler",
       "affiliation": [
         "Center for Geospatial Analytics, NC State University"
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           "nameIdentifier": "https://orcid.org/0000-0003-1829-8506",
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     },
     {
       "name": "Terando, Adam J",
       "nameType": "Personal",
       "givenName": "Adam J",
       "familyName": "Terando",
       "affiliation": [],
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         {
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           "nameIdentifier": "https://orcid.org/0000-0002-9280-043X",
           "nameIdentifierScheme": "ORCID"
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       ]
     },
     {
       "name": "Vukomanovic, Jelena",
       "nameType": "Personal",
       "givenName": "Jelena",
       "familyName": "Vukomanovic",
       "affiliation": [
         "Center for Geospatial Analytics, NC State University"
       ],
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           "nameIdentifier": "https://orcid.org/0000-0001-6477-6551",
           "nameIdentifierScheme": "ORCID"
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       ]
     },
     {
       "name": "Mitasova, Helena",
       "nameType": "Personal",
       "givenName": "Helena",
       "familyName": "Mitasova",
       "affiliation": [],
       "nameIdentifiers": [
         {
           "schemeUri": "https://orcid.org",
           "nameIdentifier": "https://orcid.org/0000-0002-6906-3398",
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       ]
     },
     {
       "name": "Meentemeyer, Ross K.",
       "nameType": "Personal",
       "givenName": "Ross K.",
       "familyName": "Meentemeyer",
       "affiliation": [
         "null"
       ],
       "nameIdentifiers": [
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           "nameIdentifier": "https://orcid.org/0000-0002-1247-6212",
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   ],
   "titles": [
     {
       "title": "FUTURES v3: Scenarios of Future Patterns of Urbanization in Response to Sea Level Rise and Frequent Flooding Across the Southeast United States from 2020 to 2100"
     }
   ],
   "publisher": "U.S. Geological Survey",
   "container": {},
   "publicationYear": 2023,
   "subjects": [
     {
       "subject": "Climatology, Land Use Change"
     }
   ],
   "contributors": [],
   "dates": [
     {
       "date": "2023",
       "dateType": "Issued"
     }
   ],
   "language": null,
   "types": {
     "ris": "DATA",
     "bibtex": "misc",
     "citeproc": "dataset",
     "schemaOrg": "Dataset",
     "resourceType": "Dataset",
     "resourceTypeGeneral": "Dataset"
   },
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   "version": null,
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   "descriptions": [
     {
       "description": "Policy-relevant flood risk modeling must capture interactions between physical and social processes to accurately project impacts from scenarios of sea level rise and inland flooding due to climate change. Here we simultaneously model urban growth, flood hazard change, and adaptive response using the FUTure Urban-Regional Environment Simulation (FUTURES) version 3 framework (Sanchez et al., 2023). FUTURES is an open source urban growth model designed to address the regional-scale ecological and environmental impacts of urbanization; it is one of the few land change models that explicitly captures the spatial structure of development in response to user-specified scenarios. We present probabilistic land change projections that predict urban growth while also simulating human migration and other response actions. We simulated two scenarios of urban growth and adaptive response: 1) \"Reactive\", wherein residents are assumed to adapt to threats as they occur, without incentives or policies in place to affect outcomes; and 2) \"Managed Retreat\", in which policymakers incentivize converting at-risk developed land to undeveloped land (i.e., abandoned), with residents of all levels of adaptive capacity moving elsewhere. We computed each scenario for 20 stochastic iterations from 2020 through 2100 at annual time steps. Our scenario advances local to national-scale efforts to evaluate tradeoffs between adaptation strategies in response to global anthropogenic change.",
       "descriptionType": "Abstract"
     }
   ],
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   "url": "https://www.sciencebase.gov/catalog/item/6463b6dbd34ec179a83d2ae5",
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   "created": "2023-06-15T15:48:38Z",
   "registered": "2023-06-15T15:48:39Z",
   "published": null,
   "updated": "2023-06-15T15:48:39Z"
 }

}