Mapping Solar Arrays With Aerial Imagery

Policymakers need accurate data in order to make strategic investments decisions for grids, microgrids, and off-grid solar home systems, but those data are often missing.

Two critical inputs for planning—who has access to electricity, and the location of infrastructure—are often unavailable or overly time-consuming to collect and maintain.

Building on our work to identify energy access using satellite imagery, EAP is investigating the value of high-resolution imagery collected by unpiloted aerial vehicles (UAVs or drones) for identifying energy infrastructure—such as small solar panels, diesel and gasoline generators, and distribution lines. Collecting this information can support public policy and private investments in sustainable energy access. While UAV imagery has a much higher detection accuracy than satellite-based images, it introduces a number of challenges that must be overcome with advances in the machine learning algorithm.

The outcomes of the project could add significant value for decision makers and communities. For instance, identifying the location and capacity of small PV panels would help donor agencies who require, as a precondition for companies to receive promised funds, monitoring to verify firms have installed systems. This monitoring typically requires expensive, large-scale ground surveys, but drone-based surveys could reduce the effective cost for donors and increase funds available for new connections. Similarly, developers considering entering a new market need to understand current levels of access to assess the competitive landscape, but the only option to collect data on SHS penetration now involves expensive door-to-door surveys. Providing a scalable method to measure existing access could be a game-changing development in many communities.

Team Members: Rob Fetter, Kyle Bradbury, Jordan Malof

Partners: Robert Beach and Jay Rineer, RTI International