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.

Original language	English
Title of host publication	GEOSIM 2023 - Proceedings of the 6th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation
Editors	Joon-Seok Kim, Ashwin Shashidharan, Andreas Züfle
Place of Publication	New York
Publisher	Association for Computing Machinery
Pages	19-22
ISBN (Electronic)	979-8-4007-0353-9
DOIs	https://doi.org/10.1145/3615891.3628012
Publication status	Published - 13 Nov 2023
Event	6th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GEOSIM 2023 - Hamburg, Germany Duration: 13 Nov 2023 → …

Conference

Conference	6th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GEOSIM 2023
Country/Territory	Germany
City	Hamburg
Period	13/11/23 → …

Keywords

Land Use Change
Multi-Agent Systems
Spatial Unit Allocation

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1145/3615891.3628012

Cite this

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 (Eds.), GEOSIM 2023 - Proceedings of the 6th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation (pp. 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. editor / Joon-Seok Kim ; Ashwin Shashidharan ; Andreas Züfle. New York : Association for Computing Machinery, 2023. pp. 19-22

@inproceedings{943a8af87db441d490d0ce96207cb9bc,

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",

booktitle = "GEOSIM 2023 - Proceedings of the 6th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation",

publisher = "Association for Computing Machinery",

address = "United States",

}

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 (eds), GEOSIM 2023 - Proceedings of the 6th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation. Association for Computing Machinery, New York, pp. 19-22, 6th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GEOSIM 2023, Hamburg, Germany, 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. ed. / Joon-Seok Kim; Ashwin Shashidharan; Andreas Züfle. New York: Association for Computing Machinery, 2023. p. 19-22.

Research output: Chapter in Book (Inbook) /Conference Proceeding › Conference Paper › Research Article/Contribution › peer-review

TY - GEN

T1 - Integrating Optimization-Based Spatial Unit Allocation into a Multi-Agent Model for the Simulation of Urban Growth

AU - Bonerath, Annika

AU - Orgeig, Yannick

AU - Haunert, Jan Henrik

AU - Dehbi, Youness

PY - 2023/11/13

Y1 - 2023/11/13

N2 - 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.

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.

KW - Land Use Change

KW - Multi-Agent Systems

KW - Spatial Unit Allocation

U2 - 10.1145/3615891.3628012

DO - 10.1145/3615891.3628012

M3 - Conference Paper

AN - SCOPUS:85178625564

SP - 19

EP - 22

BT - GEOSIM 2023 - Proceedings of the 6th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation

A2 - Kim, Joon-Seok

A2 - Shashidharan, Ashwin

A2 - Züfle, Andreas

PB - Association for Computing Machinery

CY - New York

T2 - 6th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GEOSIM 2023

Y2 - 13 November 2023

ER -

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, editors, GEOSIM 2023 - Proceedings of the 6th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation. New York: Association for Computing Machinery. 2023. p. 19-22 doi: 10.1145/3615891.3628012