Land cover and population density data

What additional geo data Solargis provides

Alongside terrain parameters, Solargis provides two additional geo-data layers: land cover (LANDC) and population density (POPUL). Land cover describes how the surface at and around a site is covered – vegetation, agriculture, urban development, water bodies – and supports both site suitability screening and ground albedo analysis. Population density describes how many people live in a given area, expressed in persons per square kilometer, and supports energy demand estimation, infrastructure planning, and social impact assessment. Both layers are published as map layers in Solargis Prospect – see Prospect map layers. For the terrain parameters they complement (ELE, SLO, AZI, HOR), see Terrain models.

Why land cover and population data matter for site selection

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. It also aids in selecting locations that align with existing land uses, minimizing conflicts with agricultural or ecologically sensitive areas.

Population density 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 data in Solargis (LANDC)

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 – for how Solargis derives albedo itself, see Satellite-based albedo data.

Source and classification of the land cover data

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.

How the land cover data stays consistent over time

One crucial aspect of the land cover data used in Solargis 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.

Figure 1: The Solargis LANDC map layer, showing land cover classes

Population density data in Solargis (POPUL)

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.

Source and processing of the population density data

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.

Figure 2: The Solargis POPUL map layer, showing population density in inhabitants per square kilometer

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).