Understanding the Carbon Footprint of Tile Transfer for Web Maps

As web maps are now extensively used by billions of users, the energy consumption of these maps is not marginal anymore. Green cartography seeks to reduce the energy consumption of maps to promote more sustainable digital tools. To reduce energy consumption, we first need to better understand the di...

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Main Authors: Guillaume Touya, Azelle Courtial, Jérémy Kalsron, Justin Berli, Bérénice Le Mao, Laura Wenclik
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:ISPRS International Journal of Geo-Information
Subjects:
Online Access:https://www.mdpi.com/2220-9964/14/3/107
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author Guillaume Touya
Azelle Courtial
Jérémy Kalsron
Justin Berli
Bérénice Le Mao
Laura Wenclik
author_facet Guillaume Touya
Azelle Courtial
Jérémy Kalsron
Justin Berli
Bérénice Le Mao
Laura Wenclik
author_sort Guillaume Touya
collection DOAJ
description As web maps are now extensively used by billions of users, the energy consumption of these maps is not marginal anymore. Green cartography seeks to reduce the energy consumption of maps to promote more sustainable digital tools. To reduce energy consumption, we first need to better understand the different sources of energy consumption for web maps. Among these sources, this paper focuses on the tiles that are stored on servers and then constantly transferred each time a user explores the map. This paper presents several experiments carried out with current web maps to assess this energy consumption. We first try to assess the number of map tiles that are loaded through the web when users explore web maps, and we determine which types of interaction are used with the maps, and a similar amount of tiles is loaded. Then, we try to assess which zoom levels are the most loaded by users; it appears that the medium–large scales are the most used (between zoom levels 11 and 17). Then, we explore the size of the map tiles and try to assess which ones are larger and thus require more energy to load over the web; we can find clear differences between zoom levels. Finally, we discuss how map generalization could be used to reduce energy consumption by creating lighter tiles. These experiments show that the current web maps are suboptimal regarding energy consumption, with many tiles loaded at zoom levels where the tiles are larger than necessary.
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spelling doaj-art-3379ece09d354875ab53f5c9213dbccb2025-08-20T01:49:04ZengMDPI AGISPRS International Journal of Geo-Information2220-99642025-03-0114310710.3390/ijgi14030107Understanding the Carbon Footprint of Tile Transfer for Web MapsGuillaume Touya0Azelle Courtial1Jérémy Kalsron2Justin Berli3Bérénice Le Mao4Laura Wenclik5LASTIG, IGN, ENSG, University Gustave Eiffel, F-77420 Champs-sur-Marne, FranceLASTIG, IGN, ENSG, University Gustave Eiffel, F-77420 Champs-sur-Marne, FranceLASTIG, IGN, ENSG, University Gustave Eiffel, F-77420 Champs-sur-Marne, FranceLASTIG, IGN, ENSG, University Gustave Eiffel, F-77420 Champs-sur-Marne, FranceLASTIG, IGN, ENSG, University Gustave Eiffel, F-77420 Champs-sur-Marne, FranceLASTIG, IGN, ENSG, University Gustave Eiffel, F-77420 Champs-sur-Marne, FranceAs web maps are now extensively used by billions of users, the energy consumption of these maps is not marginal anymore. Green cartography seeks to reduce the energy consumption of maps to promote more sustainable digital tools. To reduce energy consumption, we first need to better understand the different sources of energy consumption for web maps. Among these sources, this paper focuses on the tiles that are stored on servers and then constantly transferred each time a user explores the map. This paper presents several experiments carried out with current web maps to assess this energy consumption. We first try to assess the number of map tiles that are loaded through the web when users explore web maps, and we determine which types of interaction are used with the maps, and a similar amount of tiles is loaded. Then, we try to assess which zoom levels are the most loaded by users; it appears that the medium–large scales are the most used (between zoom levels 11 and 17). Then, we explore the size of the map tiles and try to assess which ones are larger and thus require more energy to load over the web; we can find clear differences between zoom levels. Finally, we discuss how map generalization could be used to reduce energy consumption by creating lighter tiles. These experiments show that the current web maps are suboptimal regarding energy consumption, with many tiles loaded at zoom levels where the tiles are larger than necessary.https://www.mdpi.com/2220-9964/14/3/107green cartographygreen computingweb mappingtilingmap generalization
spellingShingle Guillaume Touya
Azelle Courtial
Jérémy Kalsron
Justin Berli
Bérénice Le Mao
Laura Wenclik
Understanding the Carbon Footprint of Tile Transfer for Web Maps
ISPRS International Journal of Geo-Information
green cartography
green computing
web mapping
tiling
map generalization
title Understanding the Carbon Footprint of Tile Transfer for Web Maps
title_full Understanding the Carbon Footprint of Tile Transfer for Web Maps
title_fullStr Understanding the Carbon Footprint of Tile Transfer for Web Maps
title_full_unstemmed Understanding the Carbon Footprint of Tile Transfer for Web Maps
title_short Understanding the Carbon Footprint of Tile Transfer for Web Maps
title_sort understanding the carbon footprint of tile transfer for web maps
topic green cartography
green computing
web mapping
tiling
map generalization
url https://www.mdpi.com/2220-9964/14/3/107
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AT azellecourtial understandingthecarbonfootprintoftiletransferforwebmaps
AT jeremykalsron understandingthecarbonfootprintoftiletransferforwebmaps
AT justinberli understandingthecarbonfootprintoftiletransferforwebmaps
AT berenicelemao understandingthecarbonfootprintoftiletransferforwebmaps
AT laurawenclik understandingthecarbonfootprintoftiletransferforwebmaps