TY - GEN
T1 - Mesa-Geo
T2 - 5th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2022
AU - Wang, Boyu
AU - Hess, Vincent
AU - Crooks, Andrew
N1 - Publisher Copyright:
© 2022 ACM.
PY - 2022/11/1
Y1 - 2022/11/1
N2 - Mesa is an open-source agent-based modeling (ABM) framework implemented in the Python programming language, allowing users to build and visualize agent-based models. It has been used in a diverse range of application areas over the years ranging from biology to workforce dynamics. However, there has been no direct support for integrating geographical data from geographical information systems (GIS) into models created with Mesa. Users have had to rely on their own implementations to meet such needs. In this paper we present Mesa-Geo, a GIS extension for Mesa, which allows users to import, manipulate, visualise and export geographical data for ABM. We introduce the main components and functionalities of Mesa-Geo, followed by example applications utilizing geographical data which demonstrates Mesa-Geo's core functionalities and features common to agent-based models. Finally, we conclude with a discussion and outlook on future directions for Mesa-Geo.
AB - Mesa is an open-source agent-based modeling (ABM) framework implemented in the Python programming language, allowing users to build and visualize agent-based models. It has been used in a diverse range of application areas over the years ranging from biology to workforce dynamics. However, there has been no direct support for integrating geographical data from geographical information systems (GIS) into models created with Mesa. Users have had to rely on their own implementations to meet such needs. In this paper we present Mesa-Geo, a GIS extension for Mesa, which allows users to import, manipulate, visualise and export geographical data for ABM. We introduce the main components and functionalities of Mesa-Geo, followed by example applications utilizing geographical data which demonstrates Mesa-Geo's core functionalities and features common to agent-based models. Finally, we conclude with a discussion and outlook on future directions for Mesa-Geo.
KW - agent-based modeling (ABM)
KW - complex systems
KW - geographic information systems (GIS)
KW - Python
UR - https://www.scopus.com/pages/publications/85142627030
U2 - 10.1145/3557989.3566157
DO - 10.1145/3557989.3566157
M3 - Conference contribution
AN - SCOPUS:85142627030
T3 - Proceedings of the 5th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2022
SP - 1
EP - 10
BT - Proceedings of the 5th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2022
A2 - Anderson, Taylor
A2 - Hohl, Alexander
A2 - Kim, Joon-Seok
A2 - Shashidharan, Ashwin
PB - Association for Computing Machinery, Inc
Y2 - 1 November 2022
ER -