Integrating Optimization-Based Spatial Unit Allocation into a Multi-Agent Model for the Simulation of Urban Growth

Annika Bonerath; Yannick Orgeig; Jan Henrik Haunert; Youness Dehbi

doi:10.1145/3615891.3628012

Integrating Optimization-Based Spatial Unit Allocation into a Multi-Agent Model for the Simulation of Urban Growth

Annika Bonerath, Yannick Orgeig, Jan Henrik Haunert, Youness Dehbi

Abstract

Land use changes have a major impact on the population, the ecosystem, and the economy. Simulating these changes supports decision makers, e.g., it allows early compensation of negative impacts on the climate and ecosystem. We present a multi-agent system for the simulation. In particular, we model the agents intelligently so that they can find the optimal set of land patches for the new development (a spatial unit allocation problem). We demonstrate the feasibility of our approach providing experiments with real-world data in the region of Erftstadt in Germany.

Originalsprache	Englisch
Titel	GEOSIM 2023 - Proceedings of the 6th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation
Redakteure/-innen	Joon-Seok Kim, Ashwin Shashidharan, Andreas Züfle
Erscheinungsort	New York
Verlag	Association for Computing Machinery
Seiten	19-22
ISBN (elektronisch)	979-8-4007-0353-9
DOIs	https://doi.org/10.1145/3615891.3628012
Publikationsstatus	Veröffentlicht - 13 Nov. 2023
Veranstaltung	6th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GEOSIM 2023 - Hamburg, Deutschland Dauer: 13 Nov. 2023 → …

Tagung/Konferenz

Tagung/Konferenz	6th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GEOSIM 2023
Land/Gebiet	Deutschland
Ort	Hamburg
Zeitraum	13/11/23 → …

UN SDGs

Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung

SDG 13 – Klimaschutzmaßnahmen
SDG 15 – Lebensraum Land

Zugriff auf Dokument

10.1145/3615891.3628012Lizenz: Nicht angegeben

Dieses zitieren

Bonerath, A., Orgeig, Y., Haunert, J. H., & Dehbi, Y. (2023). Integrating Optimization-Based Spatial Unit Allocation into a Multi-Agent Model for the Simulation of Urban Growth. in J.-S. Kim, A. Shashidharan, & A. Züfle (Hrsg.), GEOSIM 2023 - Proceedings of the 6th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation (S. 19-22). Association for Computing Machinery. https://doi.org/10.1145/3615891.3628012

Bonerath, Annika ; Orgeig, Yannick ; Haunert, Jan Henrik et al. / Integrating Optimization-Based Spatial Unit Allocation into a Multi-Agent Model for the Simulation of Urban Growth. GEOSIM 2023 - Proceedings of the 6th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation. Hrsg. / Joon-Seok Kim ; Ashwin Shashidharan ; Andreas Züfle. New York : Association for Computing Machinery, 2023. S. 19-22

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title = "Integrating Optimization-Based Spatial Unit Allocation into a Multi-Agent Model for the Simulation of Urban Growth",

abstract = "Land use changes have a major impact on the population, the ecosystem, and the economy. Simulating these changes supports decision makers, e.g., it allows early compensation of negative impacts on the climate and ecosystem. We present a multi-agent system for the simulation. In particular, we model the agents intelligently so that they can find the optimal set of land patches for the new development (a spatial unit allocation problem). We demonstrate the feasibility of our approach providing experiments with real-world data in the region of Erftstadt in Germany.",

keywords = "Land Use Change, Multi-Agent Systems, Spatial Unit Allocation",

author = "Annika Bonerath and Yannick Orgeig and Haunert, \{Jan Henrik\} and Youness Dehbi",

note = "Publisher Copyright: {\textcopyright} 2023 ACM.; 6th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GEOSIM 2023 ; Conference date: 13-11-2023",

year = "2023",

month = nov,

day = "13",

doi = "10.1145/3615891.3628012",

language = "English",

pages = "19--22",

editor = "Joon-Seok Kim and Ashwin Shashidharan and Andreas Z{\"u}fle",

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publisher = "Association for Computing Machinery",

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Bonerath, A, Orgeig, Y, Haunert, JH & Dehbi, Y 2023, Integrating Optimization-Based Spatial Unit Allocation into a Multi-Agent Model for the Simulation of Urban Growth. in J-S Kim, A Shashidharan & A Züfle (Hrsg.), GEOSIM 2023 - Proceedings of the 6th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation. Association for Computing Machinery, New York, S. 19-22, 6th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GEOSIM 2023, Hamburg, Deutschland, 13/11/23. https://doi.org/10.1145/3615891.3628012

Integrating Optimization-Based Spatial Unit Allocation into a Multi-Agent Model for the Simulation of Urban Growth. / Bonerath, Annika; Orgeig, Yannick; Haunert, Jan Henrik et al.
GEOSIM 2023 - Proceedings of the 6th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation. Hrsg. / Joon-Seok Kim; Ashwin Shashidharan; Andreas Züfle. New York: Association for Computing Machinery, 2023. S. 19-22.

Publikation: Beitrag in Buch/Konferenzband › Konferenzbeitrag/Konferenzpaper › Wissenschaftlicher Artikel/Beitrag › Begutachtung

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AU - Bonerath, Annika

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AU - Dehbi, Youness

PY - 2023/11/13

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AB - Land use changes have a major impact on the population, the ecosystem, and the economy. Simulating these changes supports decision makers, e.g., it allows early compensation of negative impacts on the climate and ecosystem. We present a multi-agent system for the simulation. In particular, we model the agents intelligently so that they can find the optimal set of land patches for the new development (a spatial unit allocation problem). We demonstrate the feasibility of our approach providing experiments with real-world data in the region of Erftstadt in Germany.

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KW - Multi-Agent Systems

KW - Spatial Unit Allocation

U2 - 10.1145/3615891.3628012

DO - 10.1145/3615891.3628012

M3 - Conference Paper

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Bonerath A, Orgeig Y, Haunert JH, Dehbi Y. Integrating Optimization-Based Spatial Unit Allocation into a Multi-Agent Model for the Simulation of Urban Growth. in Kim JS, Shashidharan A, Züfle A, Hrsg., GEOSIM 2023 - Proceedings of the 6th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation. New York: Association for Computing Machinery. 2023. S. 19-22 doi: 10.1145/3615891.3628012