用高分辨率航拍图重建难民营电力网,解决缺电难题
PGRID: Power Grid Reconstruction in Informal Developments Using High-Resolution Aerial Imagery
- 通过航拍图像自动识别电杆和电线,生成精准电网图
- 在肯尼亚卡库马难民营测试中,电杆检测F1达0.71,线路分割达0.82
- 适合资源有限地区用于快速规划可持续能源基础设施
截至2023年,全球有1.17亿人流离失所,是十年前的两倍以上[22]。其中3200万为联合国难民署管辖的难民,870万居住在难民营。这些人群普遍缺乏电力,全球80%的难民营居民依赖传统生物质燃料做饭,且无法可靠供电用于烹饪或手机充电。收集柴火的负担多由妇女和儿童承担,常需前往20公里外危险区域,加剧其风险。电力接入可显著缓解此问题,但关键障碍在于缺乏准确的电网地图,尤其在资源匮乏的难民营等非正规聚居地。现有电网图常过时、不完整或依赖昂贵复杂技术,实用性差。为此,本文提出PGRID,一种基于应用的新方法,利用高分辨率航拍影像检测电杆并分割电线,生成精确电网地图。该方法在肯尼亚图尔卡纳地区的卡库马与卡拉贝伊难民营测试,覆盖84平方公里,服务超20万人。结果显示,PGRID在非正规聚居地能生成高质量电网图,电杆检测与线路分割的F1-score分别为0.71和0.82。研究证明,借助开放数据与少量标注,可在非正规定居点实现高效电网制图,为日益增长的流离失所者提供可持续能源解决方案。
原文摘要 · Abstract (English)
As of 2023, a record 117 million people have been displaced worldwide, more than double the number from a decade ago [22]. Of these, 32 million are refugees under the UNHCR mandate, with 8.7 million residing in refugee camps. A critical issue faced by these populations is the lack of access to electricity, with 80% of the 8.7 million refugees and displaced persons in camps globally relying on traditional biomass for cooking and lacking reliable power for essential tasks such as cooking and charging phones. Often, the burden of collecting firewood falls on women and children, who frequently travel up to 20 kilometers into dangerous areas, increasing their vulnerability.[7] Electricity access could significantly alleviate these challenges, but a major obstacle is the lack of accurate power grid infrastructure maps, particularly in resource-constrained environments like refugee camps, needed for energy access planning. Existing power grid maps are often outdated, incomplete, or dependent on costly, complex technologies, limiting their practicality. To address this issue, PGRID is a novel application-based approach, which utilizes high-resolution aerial imagery to detect electrical poles and segment electrical lines, creating precise power grid maps. PGRID was tested in the Turkana region of Kenya, specifically the Kakuma and Kalobeyei Camps, covering 84 km2 and housing over 200,000 residents. Our findings show that PGRID delivers high-fidelity power grid maps especially in unplanned settlements, with F1-scores of 0.71 and 0.82 for pole detection and line segmentation, respectively. This study highlights a practical application for leveraging open data and limited labels to improve power grid mapping in unplanned settlements, where the growing number of displaced persons urgently need sustainable energy infrastructure solutions.
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