The Amazon region includes nine countries in South America, all characterized by a highly culturally diverse population. However, a large number of indigenous groups are facing high levels of poverty, strengthened by their isolation and lack of access to basic services, such as electricity. These indigenous communities, which, paradoxically, would benefit the most from an increase in the provision of basic services, are often left behind national development plans [1
In order to provide such services and contribute to the Agenda 2030 and related Sustainable Development Goals (SDG), governments and development agencies need information on their numbers, distributions and specific needs. At the moment, this spatial information is missing in the Amazon region. Access is often expensive and restricted, and frequently only possible by air or via rivers, which hampers traditional methods of survey. Since early 90’s, the initiative AmazonGISnet (http://www.amazongisnet.net/
), supported by the University San Francisco de Quito (USFQ), Ecuador, has been working with indigenous communities creating a GIS framework for the territorial self-determination of their territories. In this context, Earth observation (EO) represents an outstanding tool to support the targets of AmazonGISnet, as well as the Global Development Agenda to reach the Sustainable Development Goals (SDGs), but without interfering with the ways of life of their indigenous communities. Many of these communities have seen their health and environmental conditions worsen due to oil extraction, mining, logging and agricultural industries, and some are reticent to trust outsiders [1
It is well established that the access to electricity in rural communities enables many economic activities of high added value that can prompt a self-sustained development [6
]. However, the provision of electricity services in isolated Amazonian communities is a complex problem that faces particular challenges. Due to their isolation, low demand, high dispersion and low income, electricity supply is an expensive and non-profitable enterprise which discourages electricity companies, governments and international cooperation entities [2
]. The logistics and accessibility here are expensive and dangerous. This exacerbates field work and data collection, which are essential for an appropriate design that covers the real needs of Amazonian people. The situation has led to high inequalities in electricity access. In Ecuador, 99% of the population has access to electricity. However, in some parishes, representing administrative units of the Amazonia, this percentage decreases to less than 1% [10
]. Ironically, this region is the main source of income for the country via oil and gas exportation [10
Once electrification projects have been implemented, additional challenges remain, such as the maintenance of the installations in such remote areas [9
]. In some occasions, the provision of electricity has not triggered the expected development outcomes that would allow income generation, which increases the payment capacity for electricity services [6
]. Further, socio-cultural differences between indigenous communities and electricity suppliers can lead to project failures [9
]. In the Amazon region there are many native languages and their understanding of Spanish can be marginal, which limits potential communication with electricity suppliers during data collection, while also affecting project planning and design [9
]. Besides, indigenous people perceive the natural resources as free, including solar energy. This can reduce their willingness to pay, even if subsidized, when electricity comes from solar panels [9
]. In order to overcome these challenges, an active participation of the indigenous communities on the design and implementation has been highlighted as a success factor [9
Other rural electrification projects have been carried out already in Latin America, such as the Brazilian Luz Para Todos [8
], the Venezuelan Sembrando Luz [13
] or the Yantsa Li Etsari in Ecuador [9
]. However, few of them use spatial information (e.g., [15
]), some of them have failed to target the least developed communities [11
] and, to our knowledge, none of them involved the indigenous peoples in the phases of planning and design. The present challenges also include the difficulty of mapping their settlements with EO due to their small size and different construction materials used (wood, leaves and other forest resources.) and the dense cloud cover over the Amazonia. Satellite imagery allows us to generate information on the location, size and distribution of these communities. In combination with survey data, this can be used to estimate the needs of basic services in these regions and the optimal way to supply their populations [16
]. For instance, sparse settlements with low demand will benefit most from standalone solar panels, while isolated but clustered communities with higher demand will benefit from a solar minigrid. On-demand high resolution imagery of new Very High Resolution (VHR) sensors, such as SkySat (1 m) or PlanetScope (3 m), is adequate to identify these indigenous settlements. While this imagery can be affordable for national entities, it can be too costly for development initiatives of large territories coming from indigenous sparse populations.
The project Participatory Mapping to Support Sustainable Energy for All in the Amazon—Sustainable Energy for Amazonian (SE4Amazonian, http://www.se4amazonian.com/en/)—aims
to strengthen the work of AmazonGISnet on the energy dimensions and support SDG7 through innovative data collection methods using EO, participatory mapping, and GIS technologies. We work with community leaders and local technicians that we have engaged and trained through several community and capacity building workshops. The trainings were designed so that the workflows for rural electrification planning can be replicated by the indigenous technicians themselves in other areas. These included several informative workshops about the project goals with different communities, EO and GIS-based analysis, and field data collection about socioeconomic variables using tablets.
The goal of our investigation is to develop and test a methodology which is simple and accurate enough to identify and quantify small settlements in the Amazonia. This is done with the objective to generate a spatially explicit model of the electricity demand in off-grid settlements. For that, we made use of geolocated survey data, the Google Earth Engine (GEE) cloud computing platform [19
] and freely available Landsat imagery, and a small subset of VHR imagery.
Earth Observation is key to enable development action plans to reach the Sustainable Development Goals in marginalized communities and the Global Development Agenda 2030. Indigenous communities in the Amazon are often left out national development plans. Additionally, their location, size, or spatial arrangement is mostly unknown or misinterpreted as they live in very remote areas. By using remote sensing derived proxies, such as the Tasseled Cap Wetness component we can map the location, size and distribution of settlements at sufficient resolutions to identify even small rural villages. Combining this information with data on living conditions, we can efficiently estimate the needs of basic services, such as electricity for larger territories, and especially for the regions that need it the most. Besides, the simplicity of the methodology we have developed makes it possible to transfer it to trained indigenous technicians so that they can replicate it in their territories and have more autonomy in the development of their own communities. Moreover, integrating the indigenous communities directly using a participatory mapping approach helps to get demographic insights relevant to set up development plans. Additionally, their involvement helps to give a voice to rural communities living in remote areas and to understand their views and needs. The approach developed in the project SE4Amazonian can support renewable energy companies to draw rural electrification plans in a few months compared to the years it would take by carrying out field inspections on their own. Furthermore, the here presented methods could be embedded in other attempts to foster sustainability.