Large numbers of indigenous groups in the Amazon are facing high levels of poverty, at times exacerbated by their level of isolation and lack of access to basic services like electricity. The project, led by the University of Bonn Center for Remote Sensing of Land Surfaces (ZFL), developed rural electrification plans based on remote sensing imagery combined with participatory mapping involving indigenous local technicians. The combined data fed into a GIS-based suitability analysis of renewable energy power options for the remote indigenous communities.
This project addressed SDG 7 - Clean energy for all, but also had links to SDG 1 - Zero poverty, SDG 3 - Health and Well-being, SDG 4 - Education, SDG 13 - Climate Action, and SDG 15 - Life on land. With the use of an interdisciplinary framework which integrated remote sensing and GIS technology, and in addition a participatory mapping approach involving indigenous local technicians, this project created an innovative data collection approach for clean energy provision for indigenous communities in the Amazon region. Ecuador was the pilot country for this research, while further transferability analysis was also started in Colombia and Bolivia during the final project stage.
With inputs from different freely available remote sensing sensors, in addition to participatory mapping, the size, location and distribution of the communities that were off-the-grid were estimated. First, the shape and construction of communities defined the type of electrification. For instance, a solar mini-grid is more suitable for concentrated communities living densely together, while individual solar systems are better for highly scattered households. Second, by knowing people's real development needs, the energy demand could be calculated for power appliances such as refrigerators to store medicines, light to read at night or listen to the radio, or power mills for post-processing agricultural activities. As a result of these assessments, decision makers have a planning tool to develop electrification plans that incorporate indigenous people's viewpoints and needs.
Through capacity building workshops a team of local technicians was trained to gather spatially-based information from communities with and without electricity. The training was given by AmazonGISnet a network that supports indigenous communities to manage their own territories using spatial technologies. The information collected by the field technicians through participatory mapping included: number of houses, number of people per household, infrastructures available (health center, school, workshop, etc.) but also demographic structures. This information determined the electricity needs and potentials of each community, and was used to build a GIS-based model that can extrapolate the electricity needs to non-surveyed communities using satellite information.
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