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Modelling the spatial impact of regional planning and climate change prevention strategies on land consumption in the Rhine-Ruhr Metropolitan Area 2017–2030

Rienow, Andreas und Kantakumar, Lakshmi N. und Ghazaryan, Gohar und Dröge-Rothaar, Arne und Sticksel, Sarah und Trampnau, Birte und Thonfeld, Frank (2021) Modelling the spatial impact of regional planning and climate change prevention strategies on land consumption in the Rhine-Ruhr Metropolitan Area 2017–2030. Landscape and Urban Planning, 217, Seiten 1-20. Elsevier. doi: 10.1016/j.landurbplan.2021.104284. ISSN 0169-2046.

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Offizielle URL: https://www.sciencedirect.com/science/article/pii/S0169204621002474

Kurzfassung

Urban sprawl is a ubiquitous with a complex network of driving forces and human and natural impacts on various scales of the coupled human-environment urban system. In Germany, a land consumption of 30 ha per day is envisaged. In that regard, the effect of growing metropolitan areas on the climate of local neighborhoods becomes more and more a topic in regional planning. Accordingly, the objectives of the study are a) to contribute to the climate change related land cover simulation efforts in Germany in a spatially explicit manner with a resolution of 30 m, b) to investigate future land consumption rates and population growth rates having a view on goal 11 of UN’s SDG, and c) analyze the spatial impact of planning policies in regard to land use planning and official climate change prevention strategies using Rhine-Ruhr Metropolitan Area (RRMA) in Western Germany as a study area. The study makes use of land use and land cover classification of multispectral satellite data and the derivation of land surface temperature based on Landsat satellite in order to calibrate and validate the urban growth model SUSM (scenario-based urban growth simulation model). Two scenarios for future land consumption 2030 are implemented and the future impacts of urban growth with the projection of land consumption rate (LCR), population growth rate (PGR), and LCRPGR index on municipality level, as well as the impact on regions vulnerable to climate change evaluated. The comparison of simulated urban growth to observed urban growth from 2005 to 2017 shows that the PA of SUSM for historic scenario is 68.06% with an overall accuracy of 97.15%, a Matthews correlation coefficient of 0.66, a figure of merit of 0.51 and area under curve of 0.84. The total quantity of new urban areas of our SUSM simulation 2030 were approximately 283 km2. While the difference in the simulated total quantity is nearly zero, the simulated allocation of new urban areas across the districts can differ by up to 25 km2 in the two scenarios. The number of municipalities with efficient urban land development rates increases in the SUSM scenario where no regional land development plan has been incorporated. This holds true for the number of municipalities with inefficient land use where even an increase from no plan to plan can be observed. LCRPGR is negative in most municipalities reflecting opposing trends of population and land consumption development. Most of new urban areas are distributed in open spaces important for the regional climate change prevention strategy. 32.98 % of new urban areas in our region of interest can be found in these zones in the planning scenario and 25.76 % in the scenario without planning information in SUSM model. It can be concluded that regional planning in RRMA region has no positive effect on the interregional development of future land consumption in terms of quantity, allocation, and impact on climate change prevention.

elib-URL des Eintrags:https://elib.dlr.de/144793/
Dokumentart:Zeitschriftenbeitrag
Titel:Modelling the spatial impact of regional planning and climate change prevention strategies on land consumption in the Rhine-Ruhr Metropolitan Area 2017–2030
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Rienow, Andreasandreas.rienow (at) ruhr-uni-bochum.dehttps://orcid.org/0000-0003-3893-3298NICHT SPEZIFIZIERT
Kantakumar, Lakshmi N.Lakshmikanth (at) bvieer.edu.inhttps://orcid.org/0000-0002-8912-3853NICHT SPEZIFIZIERT
Ghazaryan, GoharGohar.Ghazaryan (at) ruhr-uni-bochum.dehttps://orcid.org/0000-0003-4606-0140NICHT SPEZIFIZIERT
Dröge-Rothaar, ArneArne.Droege-Rothaar (at) ruhr-uni-bochum.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Sticksel, SarahS.Sticksel (at) stadt-duisburg.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Trampnau, Birtebirte.trampnau (at) rub.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Thonfeld, FrankFrank.Thonfeld (at) dlr.dehttps://orcid.org/0000-0002-3371-7206144888728
Datum:21 Oktober 2021
Erschienen in:Landscape and Urban Planning
Referierte Publikation:Ja
Open Access:Nein
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Ja
Band:217
DOI:10.1016/j.landurbplan.2021.104284
Seitenbereich:Seiten 1-20
Verlag:Elsevier
ISSN:0169-2046
Status:veröffentlicht
Stichwörter:Regional planning, Climate change prevention, Scenario-based modeling, SUSM, Remote sensing, Land consumption
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Raumfahrt
HGF - Programmthema:Erdbeobachtung
DLR - Schwerpunkt:Raumfahrt
DLR - Forschungsgebiet:R EO - Erdbeobachtung
DLR - Teilgebiet (Projekt, Vorhaben):R - Fernerkundung u. Geoforschung
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Deutsches Fernerkundungsdatenzentrum > Dynamik der Landoberfläche
Hinterlegt von: Thonfeld, Dr. Frank
Hinterlegt am:02 Nov 2021 20:13
Letzte Änderung:20 Okt 2023 07:20

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