Electric mobility is critical to reducing emissions from transport and dependency on Internal Combustion Engine vehicles. This study attempts to model the suitability of the built environment for electric vehicle (EV) adoption in urban areas based on sociodemographics and access to driveways for installing charging infrastructure. A novel approach using geospatial techniques is adopted to detect driveways from multispectral remote sensing information. A region in Dublin, Ireland, has been chosen as the study area. The region is further categorised based on the feasibility of EV adoption using hierarchical cluster analysis. Initial results highlight the disparity in access to low-emission modes to those not dependent on cars. Results from zero-inflated count models at the neighbourhood level reiterate the impact of driveways and sociodemographic factors on EV adoption. The proposed methodology can help evaluate infrastructure availability for widespread EV transition and inform strategic planning. The driveway detection framework may be adapted to other regions while accounting for geographic characteristics.

中文翻译：

---

使用地理空间技术评估城市人口采用电动汽车的准备情况


电动汽车对于减少交通排放和对内燃机车辆的依赖至关重要。本研究试图根据社会人口统计数据和安装充电基础设施的车道，对城市地区电动汽车 (EV) 采用的建筑环境的适宜性进行建模。采用一种使用地理空间技术的新颖方法来从多光谱遥感信息中检测车道。爱尔兰都柏林的一个地区被选为研究区域。使用分层聚类分析，根据电动汽车采用的可行性对该地区进行进一步分类。初步结果突显了那些不依赖汽车的人在使用低排放模式方面的差异。社区层面的零膨胀计数模型的结果重申了车道和社会人口因素对电动汽车采用的影响。所提出的方法可以帮助评估广泛的电动汽车转型的基础设施可用性并为战略规划提供信息。车道检测框架可以适应其他区域，同时考虑地理特征。