Multi-objective Optimization of Digital Terrain Models for Climate Adaptation Planning
dc.contributor | Aalto-yliopisto | fi |
dc.contributor | Aalto University | en |
dc.contributor.author | Hermansdorfer, Mariusz | en_US |
dc.contributor.author | Skov-Petersen, Hans | en_US |
dc.contributor.author | Fricker, Pia | en_US |
dc.contributor.department | Department of Architecture | en |
dc.contributor.organization | University of Copenhagen | en_US |
dc.date.accessioned | 2022-08-10T08:28:53Z | |
dc.date.available | 2022-08-10T08:28:53Z | |
dc.date.issued | 2022 | en_US |
dc.description | Funding Information: The authors would like to acknowledge Ramboll Studio Dreseitl and Henning Larsen Architects for providing data related to projects which served as case studies for this work. We would also like to thank the Ramboll Foundation for sponsoring the industrial PhD program, which this research is part of. Publisher Copyright: © Wichmann Verlag, VDE VERLAG GMBH · Berlin · Offenbach. | |
dc.description.abstract | As part of a joint effort between academia and practice, we propose a novel approach to digital terrain modelling for climate adaptation planning. In contrast to existing workflows, it allows designers to merely describe desired drainage patterns for a given site and use genetic solvers for their subsequent optimization. Leveraging algorithmic strategies opens the possibility to analyse multiple proposed site layouts and identify the most resilient ones. By validating the method on three typical residential development projects, this paper puts renewed emphasis on the importance of terrain modelling in the context of flood protection – a domain often dominated by technical, hardscape solutions. | en |
dc.description.version | Peer reviewed | en |
dc.format.extent | 10 | |
dc.format.extent | 453-462 | |
dc.format.mimetype | application/pdf | en_US |
dc.identifier.citation | Hermansdorfer, M, Skov-Petersen, H & Fricker, P 2022, ' Multi-objective Optimization of Digital Terrain Models for Climate Adaptation Planning ', Journal of Digital Landscape Architecture, vol. 2022, no. 7, pp. 453-462 . https://doi.org/10.14627/537724044 | en |
dc.identifier.doi | 10.14627/537724044 | en_US |
dc.identifier.issn | 2367-4253 | |
dc.identifier.issn | 2511-624X | |
dc.identifier.other | PURE UUID: f2d7ad7a-5fae-45fe-919f-ec3b6d22134b | en_US |
dc.identifier.other | PURE ITEMURL: https://research.aalto.fi/en/publications/f2d7ad7a-5fae-45fe-919f-ec3b6d22134b | en_US |
dc.identifier.other | PURE LINK: http://www.scopus.com/inward/record.url?scp=85132071781&partnerID=8YFLogxK | en_US |
dc.identifier.other | PURE FILEURL: https://research.aalto.fi/files/86624305/Multi_objective_optimization_of_digital_terrain_models_for_climate_adaptation_planning_2022.pdf | en_US |
dc.identifier.uri | https://aaltodoc.aalto.fi/handle/123456789/115977 | |
dc.identifier.urn | URN:NBN:fi:aalto-202208104799 | |
dc.language.iso | en | en |
dc.publisher | Wichmann Verlag im VDE Verlag GmbH | |
dc.relation.ispartofseries | Journal of Digital Landscape Architecture | en |
dc.relation.ispartofseries | Volume 2022, issue 7 | en |
dc.rights | openAccess | en |
dc.subject.keyword | Algorithmic design | en_US |
dc.subject.keyword | climate adaptation planning | en_US |
dc.subject.keyword | evolutionary solvers | en_US |
dc.subject.keyword | terrain modelling | en_US |
dc.title | Multi-objective Optimization of Digital Terrain Models for Climate Adaptation Planning | en |
dc.type | A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä | fi |
dc.type.version | publishedVersion |