Additional geo data

Overview

Solar project developers combine terrain information with other geo-data layers like land cover and population that provide useful information for the study of project feasibility.

Land cover data provides valuable insights into the characteristics of an area, such as vegetation, urban development, and water bodies, which can influence the feasibility of solar installations. Additionally, it aids in selecting locations that align with existing land uses, minimizing conflicts with agricultural or ecologically sensitive areas.

Population data can be particularly helpful in ensuring solar projects address local energy needs effectively. By analyzing population density and distribution, planners can identify areas where solar installations might have the most social or economic impact, such as regions or communities with limited access to energy.

Land cover

Land cover data offers information about how the surface is covered e.g. forecasts, agriculture, urban areas, etc. This information is key to determining the suitability of solar energy assets and it helps when doing a comprehensive analysis of the ground albedo of a particular site or area.

In Solargis we use the Land Cover (LC) maps provided by Copernicus Climate Change Service (C3S). The classification used in this map of land cover types follows the Land Cover Classification System (LCCS) developed by the UN's Food and Agriculture Organization (FAO). This system is designed to be compatible with other global land cover products like GLC2000, GlobCover 2005, and 2009, and it aligns well with Plant Functional Types (PFTs) used in climate models.

One crucial aspect of land cover data is their consistency over time. The data are derived from a unique baseline map created using MERIS data. Changes are detected at a 1 km resolution through different satellite data series (AVHRR, SPOT-VGT, PROBA-V, and S3-OLCI). When higher-resolution Time Series are available, changes at 1 km are remapped to 300 m. All this transformation process is managed by C3S and included in the maps provided in Solargis applications like Prospect.

Land cover changes are increasingly important for climate modeling as they both influence and result from climate change.

Population density

Population density data is important for solar energy project development as it helps estimate energy demand, guides site selection, and informs infrastructure planning. It also assists in assessing environmental and social impacts and navigating regulatory and permitting challenges. This ensures projects are efficient, cost-effective, and community-friendly.

In Solargis we utilize data from the Gridded Population of the World, Version 4 (GPWv4). This dataset provides estimates of human population density (persons per square kilometer) based on census data and population registers, adjusted to align with the 2015 Revision of the United Nations' World Population Prospects (UN WPP) for country totals.

The density rasters were generated by dividing the UN WPP-adjusted population count raster for a specific year by a land area raster. These global rasters were produced at a 30 arc-second resolution (~1 km at the equator). For quicker global processing and to support research communities, the 30 arc-second data were aggregated to create lower-resolution density rasters. All this transformation process is managed by the data source and included in the map we use in Solargis applications like Prospect.

Further reading

• Dynamic land cover. The Copernicus Land Monitoring Service (CLMS), 2019.

• Gridded Population of the World. Population Density, Version 4 (GPWv4), revision 11. Socioeconomic Data and Applications Center (SEDAC).