The amount of sun cast on roads and parking lots determines the charging opportunities for solar vehicles and impacts the efficiency of conventional vehicles. Estimates of solar energy potential on urban surfaces to assess parking and driving conditions need to account for the shadows cast by surrounding trees and buildings. However, though existing GIS tools can calculate solar potential on surfaces that have buildings and trees, these tools do not estimate the conditions beneath trees and do not consider the seasonal changes in deciduous trees. We introduce a new approach to address these factors using pixel substitution and a light penetration factor. In this paper, we describe how to integrate these techniques into a workflow for computing solar potential estimates for parking and driving conditions. We demonstrate the methodology in an urban setting in North Carolina that includes a mixture of urban structures and trees. We provide code samples so that this workflow is easily repeatable. The solar maps produced with our method are a useful resource for planning solar vehicle parking and routing, and identifying shaded conditions for conventional vehicles.

中文翻译：

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基于GIS的停车场和道路季节性太阳能潜力估算

道路和停车场的日照量决定了太阳能汽车的充电机会，并影响了传统汽车的效率。估计城市表面太阳能潜力以评估停车和驾驶条件需要考虑周围树木和建筑物的阴影。但是，尽管现有的GIS工具可以计算具有建筑物和树木的表面上的太阳能潜力，但这些工具无法估算树木下方的状况，也不会考虑落叶树的季节性变化。我们介绍了一种使用像素替换和光穿透因子来解决这些因素的新方法。在本文中，我们描述了如何将这些技术集成到工作流中，以计算停车和驾驶条件下的太阳势估算值。我们在北卡罗来纳州的城市环境中演示了该方法，其中包括城市结构和树木的混合物。我们提供代码示例，以便此工作流程易于重复。用我们的方法生成的太阳图对于规划太阳能车辆的停车和路线选择以及确定常规车辆的阴影条件是有用的资源。