The effects of population aggregation in geospatial electrification planning

The introduction of geospatial data into modelling efforts carries many advantages but also introduces numerous challenges. A common challenge is the Modifiable Areal Unit Problem (MAUP), describing how results change as the spatial aggregation of data changes. Here, we have studied MAUP in geospati...

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Autores principales:	Babak Khavari, Andreas Sahlberg, Will Usher, Alexandros Korkovelos, Francesco Fuso Nerini
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Population aggregation Geospatial electrification Energy access Sensitivity analysis Energy industries. Energy policy. Fuel trade HD9502-9502.5
Acceso en línea:	https://doaj.org/article/61e3e168d1b44f2b903e32f1f0770796
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id	oai:doaj.org-article:61e3e168d1b44f2b903e32f1f0770796
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spelling	oai:doaj.org-article:61e3e168d1b44f2b903e32f1f07707962021-11-06T04:27:32ZThe effects of population aggregation in geospatial electrification planning2211-467X10.1016/j.esr.2021.100752https://doaj.org/article/61e3e168d1b44f2b903e32f1f07707962021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2211467X21001371https://doaj.org/toc/2211-467XThe introduction of geospatial data into modelling efforts carries many advantages but also introduces numerous challenges. A common challenge is the Modifiable Areal Unit Problem (MAUP), describing how results change as the spatial aggregation of data changes. Here, we have studied MAUP in geospatial least-cost electrification modelling. We do this by assessing the effects of using 26 different population bases each for Benin, Malawi and Namibia. We use the population bases to generate 2080 electrification scenarios per country and conducting a global sensitivity analysis using the Delta Moment-Independent Measure. We identify population aggregation to be highly influential to the model results with regards to method of aggregation (delta values of 0.06–0.24 depending on output studied), administrative division (0.05–0.14), buffer chosen in the clustering process (0.05–0.32) and the minimum number of neighbours within the buffer required for clustering (0.05–0.19). Based on our findings, we conclude that geospatial electrification studies are not robust concerning the choice of population data. We suggest, that modelers put larger emphasis on different population aggregation methods in their sensitivity analyses and that the methods chosen to conduct sensitivity analysis are global in nature (i.e. moving all inputs simultaneously through their possible range of values).Babak KhavariAndreas SahlbergWill UsherAlexandros KorkovelosFrancesco Fuso NeriniElsevierarticlePopulation aggregationGeospatial electrificationEnergy accessSensitivity analysisEnergy industries. Energy policy. Fuel tradeHD9502-9502.5ENEnergy Strategy Reviews, Vol 38, Iss , Pp 100752- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Population aggregation Geospatial electrification Energy access Sensitivity analysis Energy industries. Energy policy. Fuel trade HD9502-9502.5
spellingShingle	Population aggregation Geospatial electrification Energy access Sensitivity analysis Energy industries. Energy policy. Fuel trade HD9502-9502.5 Babak Khavari Andreas Sahlberg Will Usher Alexandros Korkovelos Francesco Fuso Nerini The effects of population aggregation in geospatial electrification planning
description	The introduction of geospatial data into modelling efforts carries many advantages but also introduces numerous challenges. A common challenge is the Modifiable Areal Unit Problem (MAUP), describing how results change as the spatial aggregation of data changes. Here, we have studied MAUP in geospatial least-cost electrification modelling. We do this by assessing the effects of using 26 different population bases each for Benin, Malawi and Namibia. We use the population bases to generate 2080 electrification scenarios per country and conducting a global sensitivity analysis using the Delta Moment-Independent Measure. We identify population aggregation to be highly influential to the model results with regards to method of aggregation (delta values of 0.06–0.24 depending on output studied), administrative division (0.05–0.14), buffer chosen in the clustering process (0.05–0.32) and the minimum number of neighbours within the buffer required for clustering (0.05–0.19). Based on our findings, we conclude that geospatial electrification studies are not robust concerning the choice of population data. We suggest, that modelers put larger emphasis on different population aggregation methods in their sensitivity analyses and that the methods chosen to conduct sensitivity analysis are global in nature (i.e. moving all inputs simultaneously through their possible range of values).
format	article
author	Babak Khavari Andreas Sahlberg Will Usher Alexandros Korkovelos Francesco Fuso Nerini
author_facet	Babak Khavari Andreas Sahlberg Will Usher Alexandros Korkovelos Francesco Fuso Nerini
author_sort	Babak Khavari
title	The effects of population aggregation in geospatial electrification planning
title_short	The effects of population aggregation in geospatial electrification planning
title_full	The effects of population aggregation in geospatial electrification planning
title_fullStr	The effects of population aggregation in geospatial electrification planning
title_full_unstemmed	The effects of population aggregation in geospatial electrification planning
title_sort	effects of population aggregation in geospatial electrification planning
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/61e3e168d1b44f2b903e32f1f0770796
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The effects of population aggregation in geospatial electrification planning

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