Creating a longitudinal, data-driven 3D model of change over time in a postindustrial landscape using GIS and CityEngine
PurposeThe purpose of this paper is to create a longitudinal data-driven model of change over time in a postindustrial landscape, using the “Copper Country” of Michigan’s Upper Peninsula as a case study. The models resulting from this project will support the heritage management and public education...
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Veröffentlicht in: | Journal of Cultural Heritage Management and Sustainable Development 2018-11, Vol.8 (4), p.434-447 |
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description | PurposeThe purpose of this paper is to create a longitudinal data-driven model of change over time in a postindustrial landscape, using the “Copper Country” of Michigan’s Upper Peninsula as a case study. The models resulting from this project will support the heritage management and public education goals of the contemporary communities and Keweenaw National Historical Park that administer this nationally significant mining region through accessible, engaging, and interpretable digital heritage.Design/methodology/approachThe paper applies Esri’s CityEngine procedural modeling software to an existing historical big data set. The Copper Country Historical Spatial Data Infrastructure, previously created by the HESA lab, contains over 120,000 spatiotemporally specific building footprints and other built environment variables. This project constructed a pair of 3D digital landscapes comparing the built environments of 1917 and 1949, reflecting the formal and functional evolution of several of the most important copper mining, milling, and smelting districts of Michigan’s Keweenaw Peninsula.FindingsThis research discovered that CityEngine, while intended for rapid 3D modeling of the contemporary urban landscape, was sufficiently robust and flexible to be applied to modeling serial historic industrial landscapes. While this novel application required some additional coding and finish work, by harnessing this software to existing big data sets, 48,000 individual buildings were rapidly visualized using several key variables.Originality/valueThis paper presents a new and useful application of an existing 3D modeling software, helping to further illuminate and inform the management and conservation of the rich heritage of this still-evolving postindustrial landscape. |
doi_str_mv | 10.1108/JCHMSD-08-2017-0055 |
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The models resulting from this project will support the heritage management and public education goals of the contemporary communities and Keweenaw National Historical Park that administer this nationally significant mining region through accessible, engaging, and interpretable digital heritage.Design/methodology/approachThe paper applies Esri’s CityEngine procedural modeling software to an existing historical big data set. The Copper Country Historical Spatial Data Infrastructure, previously created by the HESA lab, contains over 120,000 spatiotemporally specific building footprints and other built environment variables. This project constructed a pair of 3D digital landscapes comparing the built environments of 1917 and 1949, reflecting the formal and functional evolution of several of the most important copper mining, milling, and smelting districts of Michigan’s Keweenaw Peninsula.FindingsThis research discovered that CityEngine, while intended for rapid 3D modeling of the contemporary urban landscape, was sufficiently robust and flexible to be applied to modeling serial historic industrial landscapes. While this novel application required some additional coding and finish work, by harnessing this software to existing big data sets, 48,000 individual buildings were rapidly visualized using several key variables.Originality/valueThis paper presents a new and useful application of an existing 3D modeling software, helping to further illuminate and inform the management and conservation of the rich heritage of this still-evolving postindustrial landscape.</description><identifier>ISSN: 2044-1266</identifier><identifier>EISSN: 2044-1274</identifier><identifier>DOI: 10.1108/JCHMSD-08-2017-0055</identifier><language>eng</language><publisher>Bingley: Emerald Group Publishing Limited</publisher><subject>Archives & records ; Automation ; Big Data ; Building information modeling ; Built environment ; Computer programs ; Concrete ; Copper ; Cultural heritage ; Data management ; Data processing ; Design ; Environmental impact ; Historic buildings & sites ; Historic preservation ; Historical metallurgy ; Infrastructure ; Landscape ; National parks ; Smelting ; Software ; Spatial data ; Three dimensional models ; Urban environments</subject><ispartof>Journal of Cultural Heritage Management and Sustainable Development, 2018-11, Vol.8 (4), p.434-447</ispartof><rights>Emerald Publishing Limited 2018</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c320t-233ec64d2ecec89f7eb431096144ee9f645a50205e92b06cb80c77cfe9c637f23</citedby><cites>FETCH-LOGICAL-c320t-233ec64d2ecec89f7eb431096144ee9f645a50205e92b06cb80c77cfe9c637f23</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,961,21674,27901,27902</link.rule.ids></links><search><creatorcontrib>Arnold, John David McEwen</creatorcontrib><creatorcontrib>Lafreniere, Don</creatorcontrib><title>Creating a longitudinal, data-driven 3D model of change over time in a postindustrial landscape using GIS and CityEngine</title><title>Journal of Cultural Heritage Management and Sustainable Development</title><description>PurposeThe purpose of this paper is to create a longitudinal data-driven model of change over time in a postindustrial landscape, using the “Copper Country” of Michigan’s Upper Peninsula as a case study. The models resulting from this project will support the heritage management and public education goals of the contemporary communities and Keweenaw National Historical Park that administer this nationally significant mining region through accessible, engaging, and interpretable digital heritage.Design/methodology/approachThe paper applies Esri’s CityEngine procedural modeling software to an existing historical big data set. The Copper Country Historical Spatial Data Infrastructure, previously created by the HESA lab, contains over 120,000 spatiotemporally specific building footprints and other built environment variables. This project constructed a pair of 3D digital landscapes comparing the built environments of 1917 and 1949, reflecting the formal and functional evolution of several of the most important copper mining, milling, and smelting districts of Michigan’s Keweenaw Peninsula.FindingsThis research discovered that CityEngine, while intended for rapid 3D modeling of the contemporary urban landscape, was sufficiently robust and flexible to be applied to modeling serial historic industrial landscapes. While this novel application required some additional coding and finish work, by harnessing this software to existing big data sets, 48,000 individual buildings were rapidly visualized using several key variables.Originality/valueThis paper presents a new and useful application of an existing 3D modeling software, helping to further illuminate and inform the management and conservation of the rich heritage of this still-evolving postindustrial landscape.</description><subject>Archives & records</subject><subject>Automation</subject><subject>Big Data</subject><subject>Building information modeling</subject><subject>Built environment</subject><subject>Computer programs</subject><subject>Concrete</subject><subject>Copper</subject><subject>Cultural heritage</subject><subject>Data management</subject><subject>Data processing</subject><subject>Design</subject><subject>Environmental impact</subject><subject>Historic buildings & sites</subject><subject>Historic preservation</subject><subject>Historical metallurgy</subject><subject>Infrastructure</subject><subject>Landscape</subject><subject>National parks</subject><subject>Smelting</subject><subject>Software</subject><subject>Spatial data</subject><subject>Three dimensional models</subject><subject>Urban environments</subject><issn>2044-1266</issn><issn>2044-1274</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>AVQMV</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>K50</sourceid><sourceid>M1D</sourceid><sourceid>M2O</sourceid><recordid>eNo9kFFLwzAQx4soOHSfwJeAr1YvSdu0j9LNbTLxYfpcsvQ6M7qmJulw396UiQfH_Tnu_sf9ouiOwiOlkD-9lsu3zSyGPGZARQyQphfRhEGSxJSJ5PJfZ9l1NHVuDyEEZTxNJ9FPaVF63e2IJK3pdtoPte5k-0Bq6WVcW33EjvAZOZgaW2Iaor5kt0NijmiJ1wckugu7vXHBpR6ct1q2pJVd7ZTskQxuNF-sNiS0SKn9aR6udHgbXTWydTj9qzfR58v8o1zG6_fFqnxex4oz8DHjHFWW1AwVqrxoBG4TTqHIaJIgFk2WpDIFBikWbAuZ2uaghFANFirjomH8Jro_-_bWfA_ofLU3gw0fuopRzkIKgDDFz1PKGucsNlVv9UHaU0WhGilXZ8pVUCPlaqTMfwGd4XAS</recordid><startdate>20181119</startdate><enddate>20181119</enddate><creator>Arnold, John David McEwen</creator><creator>Lafreniere, Don</creator><general>Emerald Group Publishing Limited</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>7U6</scope><scope>7XB</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AVQMV</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>K50</scope><scope>M1D</scope><scope>M2O</scope><scope>MBDVC</scope><scope>PADUT</scope><scope>PATMY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>Q9U</scope></search><sort><creationdate>20181119</creationdate><title>Creating a longitudinal, data-driven 3D model of change over time in a postindustrial landscape using GIS and CityEngine</title><author>Arnold, John David McEwen ; Lafreniere, Don</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c320t-233ec64d2ecec89f7eb431096144ee9f645a50205e92b06cb80c77cfe9c637f23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Archives & records</topic><topic>Automation</topic><topic>Big Data</topic><topic>Building information modeling</topic><topic>Built environment</topic><topic>Computer programs</topic><topic>Concrete</topic><topic>Copper</topic><topic>Cultural heritage</topic><topic>Data management</topic><topic>Data processing</topic><topic>Design</topic><topic>Environmental impact</topic><topic>Historic buildings & sites</topic><topic>Historic preservation</topic><topic>Historical metallurgy</topic><topic>Infrastructure</topic><topic>Landscape</topic><topic>National parks</topic><topic>Smelting</topic><topic>Software</topic><topic>Spatial data</topic><topic>Three dimensional models</topic><topic>Urban environments</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Arnold, John David McEwen</creatorcontrib><creatorcontrib>Lafreniere, Don</creatorcontrib><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Sustainability Science Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>Arts Premium Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>Art, Design & Architecture Collection</collection><collection>Arts & Humanities Database</collection><collection>Research Library</collection><collection>Research Library (Corporate)</collection><collection>Research Library China</collection><collection>Environmental Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><jtitle>Journal of Cultural Heritage Management and Sustainable Development</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Arnold, John David McEwen</au><au>Lafreniere, Don</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Creating a longitudinal, data-driven 3D model of change over time in a postindustrial landscape using GIS and CityEngine</atitle><jtitle>Journal of Cultural Heritage Management and Sustainable Development</jtitle><date>2018-11-19</date><risdate>2018</risdate><volume>8</volume><issue>4</issue><spage>434</spage><epage>447</epage><pages>434-447</pages><issn>2044-1266</issn><eissn>2044-1274</eissn><abstract>PurposeThe purpose of this paper is to create a longitudinal data-driven model of change over time in a postindustrial landscape, using the “Copper Country” of Michigan’s Upper Peninsula as a case study. The models resulting from this project will support the heritage management and public education goals of the contemporary communities and Keweenaw National Historical Park that administer this nationally significant mining region through accessible, engaging, and interpretable digital heritage.Design/methodology/approachThe paper applies Esri’s CityEngine procedural modeling software to an existing historical big data set. The Copper Country Historical Spatial Data Infrastructure, previously created by the HESA lab, contains over 120,000 spatiotemporally specific building footprints and other built environment variables. This project constructed a pair of 3D digital landscapes comparing the built environments of 1917 and 1949, reflecting the formal and functional evolution of several of the most important copper mining, milling, and smelting districts of Michigan’s Keweenaw Peninsula.FindingsThis research discovered that CityEngine, while intended for rapid 3D modeling of the contemporary urban landscape, was sufficiently robust and flexible to be applied to modeling serial historic industrial landscapes. While this novel application required some additional coding and finish work, by harnessing this software to existing big data sets, 48,000 individual buildings were rapidly visualized using several key variables.Originality/valueThis paper presents a new and useful application of an existing 3D modeling software, helping to further illuminate and inform the management and conservation of the rich heritage of this still-evolving postindustrial landscape.</abstract><cop>Bingley</cop><pub>Emerald Group Publishing Limited</pub><doi>10.1108/JCHMSD-08-2017-0055</doi><tpages>14</tpages></addata></record> |
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subjects | Archives & records Automation Big Data Building information modeling Built environment Computer programs Concrete Copper Cultural heritage Data management Data processing Design Environmental impact Historic buildings & sites Historic preservation Historical metallurgy Infrastructure Landscape National parks Smelting Software Spatial data Three dimensional models Urban environments |
title | Creating a longitudinal, data-driven 3D model of change over time in a postindustrial landscape using GIS and CityEngine |
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