{"title":"城市树木规划:mcda驱动的方法能帮助改善当前的实践吗?加拿大案例研究","authors":"Alexandre Rioux , Sandrine Lacroix , Martijn Kuller , Françoise Bichai , Danielle Dagenais","doi":"10.1016/j.tfp.2025.101029","DOIUrl":null,"url":null,"abstract":"<div><div>Canadian cities are striving to address climate change by setting ambitious goals for tree planting and increasing urban canopy cover. However, urban tree planning is complex, involving multiple objectives like reducing heat islands, improving public health, and minimizing costs, while balancing the interests of various stakeholders. To manage this complexity, a spatial suitability model for tree planting was developed using GIS-MCDA. This model was co-created with stakeholders in Montreal, Canada, and aims to improve upon traditional urban tree planning methods by combining territorial opportunities and needs. A comparison was made between the model's recommendations for tree planting sites and the sites previously planned by municipal institutions in three Montreal boroughs. The analysis, which considered both the entire study area, and a subset comprised of public land, showed a significant discrepancy between the areas prioritized by the model and those selected by the boroughs, with little overlap between the two. This difference may stem from the model's broaderscale approach, while the boroughs focused on individual tree pits at a finer scale. Despite these differences, the framework provides an opportunity for municipal institutions to consider a wider range of planting sites and take into account a more complete set of decision criteria. By using this model, cities can optimize tree planting efforts to provide needed ecosystem services to the local populations.</div></div>","PeriodicalId":36104,"journal":{"name":"Trees, Forests and People","volume":"22 ","pages":"Article 101029"},"PeriodicalIF":2.9000,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Urban tree planning: Can MCDA-driven approaches help improve current practices? A Canadian case study\",\"authors\":\"Alexandre Rioux , Sandrine Lacroix , Martijn Kuller , Françoise Bichai , Danielle Dagenais\",\"doi\":\"10.1016/j.tfp.2025.101029\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Canadian cities are striving to address climate change by setting ambitious goals for tree planting and increasing urban canopy cover. However, urban tree planning is complex, involving multiple objectives like reducing heat islands, improving public health, and minimizing costs, while balancing the interests of various stakeholders. To manage this complexity, a spatial suitability model for tree planting was developed using GIS-MCDA. This model was co-created with stakeholders in Montreal, Canada, and aims to improve upon traditional urban tree planning methods by combining territorial opportunities and needs. A comparison was made between the model's recommendations for tree planting sites and the sites previously planned by municipal institutions in three Montreal boroughs. The analysis, which considered both the entire study area, and a subset comprised of public land, showed a significant discrepancy between the areas prioritized by the model and those selected by the boroughs, with little overlap between the two. This difference may stem from the model's broaderscale approach, while the boroughs focused on individual tree pits at a finer scale. Despite these differences, the framework provides an opportunity for municipal institutions to consider a wider range of planting sites and take into account a more complete set of decision criteria. By using this model, cities can optimize tree planting efforts to provide needed ecosystem services to the local populations.</div></div>\",\"PeriodicalId\":36104,\"journal\":{\"name\":\"Trees, Forests and People\",\"volume\":\"22 \",\"pages\":\"Article 101029\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2025-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Trees, Forests and People\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666719325002559\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"FORESTRY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Trees, Forests and People","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666719325002559","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"FORESTRY","Score":null,"Total":0}
Urban tree planning: Can MCDA-driven approaches help improve current practices? A Canadian case study
Canadian cities are striving to address climate change by setting ambitious goals for tree planting and increasing urban canopy cover. However, urban tree planning is complex, involving multiple objectives like reducing heat islands, improving public health, and minimizing costs, while balancing the interests of various stakeholders. To manage this complexity, a spatial suitability model for tree planting was developed using GIS-MCDA. This model was co-created with stakeholders in Montreal, Canada, and aims to improve upon traditional urban tree planning methods by combining territorial opportunities and needs. A comparison was made between the model's recommendations for tree planting sites and the sites previously planned by municipal institutions in three Montreal boroughs. The analysis, which considered both the entire study area, and a subset comprised of public land, showed a significant discrepancy between the areas prioritized by the model and those selected by the boroughs, with little overlap between the two. This difference may stem from the model's broaderscale approach, while the boroughs focused on individual tree pits at a finer scale. Despite these differences, the framework provides an opportunity for municipal institutions to consider a wider range of planting sites and take into account a more complete set of decision criteria. By using this model, cities can optimize tree planting efforts to provide needed ecosystem services to the local populations.