Service coverage is a crucial component of spatial decision‐making involving facility siting. Determining coverage requires knowledge about travel behavior and accessibility across a region, as well as supporting methods of measurement and derivation when actual travel cannot necessarily be observed. When service is provided using vehicles that move freely without the restriction posed by roads (e.g., airplanes, helicopters, unmanned aerial vehicles/drones, boats, ships, and submarines), straight‐line travel is regularly assumed. However, this common assumption is often violated by geographical obstructions, resulting in overestimated service coverage. To date, no methods have been developed capable of accounting for obstacle‐limited service coverage. Existing methods either completely ignore obstructions or crudely estimate impacts on travel. In this research, we develop a novel method, ESP‐Cover, capable of deriving accurate obstacle‐limited coverage without introducing representation errors. A location siting problem involving drone‐based package delivery is presented to highlight the necessity of explicitly accounting for obstacles in system design. The assessment results demonstrate the importance of accurate derivation of the obstacle‐limited coverage for spatial decision‐making and the accuracy of the ESP‐Cover method in coverage derivation.

中文翻译：

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障碍物限制的服务范围：一种新的地理空间方法

服务范围是涉及设施选址的空间决策的重要组成部分。确定覆盖范围需要了解整个区域的旅行行为和可及性，以及在不一定能观察到实际旅行时支持测量和推导的方法。如果使用不受道路限制的自由移动的车辆（例如飞机，直升机，无人驾驶飞机/无人机，船只，轮船和潜艇）提供服务，则通常假定为直线行驶。但是，这种通常的假设通常会因地理障碍而违背，从而导致对服务覆盖率的高估。迄今为止，还没有开发出能够解决障碍物受限服务范围的方法。现有方法要么完全忽略障碍物，要么粗略估计对旅行的影响。在这项研究中，我们开发了一种新颖的方法ESP-Cover，能够在不引入表示误差的情况下获得准确的障碍物限制覆盖范围。提出了涉及基于无人机的包裹递送的选址问题，以突出显示在系统设计中明确考虑障碍的必要性。评估结果表明，准确推导障碍物有限覆盖范围对于空间决策的重要性以及ESP-Cover方法在覆盖范围推导中的准确性。