Geographically Weighted Regression-Based Predictions of Water–Soil–Energy Nexus Solutions in Île-de-France
Due to global urbanization, urban areas are encountering many environmental, social, and economic challenges. Different solutions have been proposed and implemented, such as nature-based solutions and green and blue infrastructure. Taking into consideration exogenous factors that are associated with...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-11-01
|
| Series: | Urban Science |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2413-8851/6/4/81 |
| _version_ | 1797455068790784000 |
|---|---|
| author | Walid Al-Shaar Olivier Bonin Bernard de Gouvello Patrice Chatellier Martin Hendel |
| author_facet | Walid Al-Shaar Olivier Bonin Bernard de Gouvello Patrice Chatellier Martin Hendel |
| author_sort | Walid Al-Shaar |
| collection | DOAJ |
| description | Due to global urbanization, urban areas are encountering many environmental, social, and economic challenges. Different solutions have been proposed and implemented, such as nature-based solutions and green and blue infrastructure. Taking into consideration exogenous factors that are associated with these solutions is a crucial question to assess their possible effects. This study examines the possible explanatory factors and their evolution until the year 2054 of several solutions in the Île-de-France region: wastewater heat-recovery, surface geothermal energy, and heat-mitigation capacities of zones. This investigation is performed by a series of statistical models, namely the ordinary least squares (OLS) and the geographically weighted regressions (GWR), integrated within a geographic information system. The main driving factors were identified as land use/land cover and population distribution. The results show that GWR models capture a large part of spatial autocorrelation. Apropos of prediction results, areas with low, medium, and high potential for implementing specific solutions are determined. Furthermore, the implementation capacities of solutions are compared with the demand depicted as the need for slowing down the effects of surface urban heat islands and the dependence on fossil energy. Moreover, the heat mitigation capacities are not at all times distinctively linked to human activities. Further investigations are needed to discover the remaining possible reasons, particularly air quality, water, vegetation, and climate change. |
| first_indexed | 2024-03-09T15:47:12Z |
| format | Article |
| id | doaj.art-edc1b93ac3f14e45a5fcf0c27f5c6dbc |
| institution | Directory Open Access Journal |
| issn | 2413-8851 |
| language | English |
| last_indexed | 2024-03-09T15:47:12Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Urban Science |
| spelling | doaj.art-edc1b93ac3f14e45a5fcf0c27f5c6dbc2023-11-24T18:30:07ZengMDPI AGUrban Science2413-88512022-11-01648110.3390/urbansci6040081Geographically Weighted Regression-Based Predictions of Water–Soil–Energy Nexus Solutions in Île-de-FranceWalid Al-Shaar0Olivier Bonin1Bernard de Gouvello2Patrice Chatellier3Martin Hendel4LVMT—Laboratoire Ville Mobilité Transport, Université Gustave Eiffel, 77420 Champs sur Marne, FranceLVMT—Laboratoire Ville Mobilité Transport, Université Gustave Eiffel, 77420 Champs sur Marne, FranceCSTB—Centre Scientifique et Technique du Bâtiment, 77447 Marne-la-Vallée, FranceIMSE—Instrumentation, Modélisation, Simulation et Expérimentation, Université Gustave Eiffel, 77420 Champs sur Marne, FranceDépartement Santé Energie Environnement (SEN), ESIEE, Université Gustave Eiffel, 93162 Noisy le Grand, FranceDue to global urbanization, urban areas are encountering many environmental, social, and economic challenges. Different solutions have been proposed and implemented, such as nature-based solutions and green and blue infrastructure. Taking into consideration exogenous factors that are associated with these solutions is a crucial question to assess their possible effects. This study examines the possible explanatory factors and their evolution until the year 2054 of several solutions in the Île-de-France region: wastewater heat-recovery, surface geothermal energy, and heat-mitigation capacities of zones. This investigation is performed by a series of statistical models, namely the ordinary least squares (OLS) and the geographically weighted regressions (GWR), integrated within a geographic information system. The main driving factors were identified as land use/land cover and population distribution. The results show that GWR models capture a large part of spatial autocorrelation. Apropos of prediction results, areas with low, medium, and high potential for implementing specific solutions are determined. Furthermore, the implementation capacities of solutions are compared with the demand depicted as the need for slowing down the effects of surface urban heat islands and the dependence on fossil energy. Moreover, the heat mitigation capacities are not at all times distinctively linked to human activities. Further investigations are needed to discover the remaining possible reasons, particularly air quality, water, vegetation, and climate change.https://www.mdpi.com/2413-8851/6/4/81water–soil–energy nexusnature-based solutionsgreen and blue infrastructureheat recoverysurface geothermal energygeographically weighted regression |
| spellingShingle | Walid Al-Shaar Olivier Bonin Bernard de Gouvello Patrice Chatellier Martin Hendel Geographically Weighted Regression-Based Predictions of Water–Soil–Energy Nexus Solutions in Île-de-France Urban Science water–soil–energy nexus nature-based solutions green and blue infrastructure heat recovery surface geothermal energy geographically weighted regression |
| title | Geographically Weighted Regression-Based Predictions of Water–Soil–Energy Nexus Solutions in Île-de-France |
| title_full | Geographically Weighted Regression-Based Predictions of Water–Soil–Energy Nexus Solutions in Île-de-France |
| title_fullStr | Geographically Weighted Regression-Based Predictions of Water–Soil–Energy Nexus Solutions in Île-de-France |
| title_full_unstemmed | Geographically Weighted Regression-Based Predictions of Water–Soil–Energy Nexus Solutions in Île-de-France |
| title_short | Geographically Weighted Regression-Based Predictions of Water–Soil–Energy Nexus Solutions in Île-de-France |
| title_sort | geographically weighted regression based predictions of water soil energy nexus solutions in ile de france |
| topic | water–soil–energy nexus nature-based solutions green and blue infrastructure heat recovery surface geothermal energy geographically weighted regression |
| url | https://www.mdpi.com/2413-8851/6/4/81 |
| work_keys_str_mv | AT walidalshaar geographicallyweightedregressionbasedpredictionsofwatersoilenergynexussolutionsiniledefrance AT olivierbonin geographicallyweightedregressionbasedpredictionsofwatersoilenergynexussolutionsiniledefrance AT bernarddegouvello geographicallyweightedregressionbasedpredictionsofwatersoilenergynexussolutionsiniledefrance AT patricechatellier geographicallyweightedregressionbasedpredictionsofwatersoilenergynexussolutionsiniledefrance AT martinhendel geographicallyweightedregressionbasedpredictionsofwatersoilenergynexussolutionsiniledefrance |