COMPASS – An open-source software package for creating multi-level representative nested synthetic populations for small areas

Simulation models, such as agent-based or microsimulation models capturing urban contexts, increasingly draw on spatially explicit, attribute-rich synthetic population datasets as real-world data inputs. Despite their growing relevance, the creation of such datasets via simulated annealing still faces significant limitations. Addressing these limitations, we present the open-source software package Combinatorial Optimisation for Microdata Population Assembly and Spatial Synthesis (COMPASS) . The algorithm implemented in COMPASS enables: aggregate-level representativeness at different levels of counts (e.g., households and individuals); the processing of nested input data (e.g., retaining survey household and kinship structures); and systematic monitoring of uncertainty arising at creation stage. We provide COMPASS as a compiled multi-platform software package, suitable for reproducible workflows via R and Python. This paper introduces COMPASS and illustrates one potential workflow using open access data created to reflect an artificial population – transferable to many national contexts.

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Publication Details

Journal
Environment and Planning B Urban Analytics and City Science
Published
2026-10-07
DOI
https://doi.org/10.1177/23998083261484652
Primary Topic
demographic modeling and climate adaptation
Type
article
Field-Weighted Citation Impact
0.00

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article

COMPASS – An open-source software package for creating multi-level representative nested synthetic populations for small areas

Andreas Höhn, Corinna Elsenbroich, Nik Lomax, Petra Sylvia Meier et al.
Environment and Planning B Urban Analytics and City Science
demographic modeling and climate adaptation
article

COMPASS – An open-source software package for creating multi-level representative nested synthetic populations for small areas

Andreas Höhn, Corinna Elsenbroich, Nik Lomax, Petra Sylvia Meier, Ricardo Colasanti, Hugh Rice, Alison Heppenstall
article en

Abstract

Simulation models, such as agent-based or microsimulation models capturing urban contexts, increasingly draw on spatially explicit, attribute-rich synthetic population datasets as real-world data inputs. Despite their growing relevance, the creation of such datasets via simulated annealing still faces significant limitations. Addressing these limitations, we present the open-source software package Combinatorial Optimisation for Microdata Population Assembly and Spatial Synthesis (COMPASS) . The algorithm implemented in COMPASS enables: aggregate-level representativeness at different levels of counts (e.g., households and individuals); the processing of nested input data (e.g., retaining survey household and kinship structures); and systematic monitoring of uncertainty arising at creation stage. We provide COMPASS as a compiled multi-platform software package, suitable for reproducible workflows via R and Python. This paper introduces COMPASS and illustrates one potential workflow using open access data created to reflect an artificial population – transferable to many national contexts.

Environment and Planning B Urban Analytics and City Science
University of Leeds (GB), The Alan Turing Institute (GB), University of Glasgow (GB)
UK Research and Innovation, National Institute for Health and Care Research, Economic and Social Research Council, Public Health Research Programme
Openalex Percentile: Top 29%
demographic modeling and climate adaptation
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