Geospatial mapping

Geospatial data and maps for the PV industry

Solar resource and other meteorological and environmental factors change over time and across locations. Understanding the geographical and temporal variability is critical for site selection and developing an optimum project design, taking into account the project location in a geographical context.

Geodata, maps, and visual tools simplify the complexity of interaction between the local environment and PV technology, helping people find patterns and make sense of vast amounts of information. Map tools make it easier to understand relationships between different factors of the environment and plan PV projects more effectively, minimizing weather- and environment-related risks. Accurate and visually appealing maps play a crucial role in supporting informed decision-making for PV projects.

Key concepts in geodatabases and maps

Creating high-quality maps for solar energy involves several prerequisites that work together to provide accurate site evaluation, understanding a regional context, focusing on maximizing the performance of a solar project, and minimizing environmental risks. The key components include:

• High-Quality Geodata: Accurate geographical data representing solar radiation, meteorological, and environmental factors - all needed for evaluating PV power output and risks to operation and damage - is essential for effectively evaluating a site's potential.

• Data Processing Techniques: Each data parameter and format requires specific handling, especially when dealing with large and complex datasets available globally. With extensive experience in Geographic Information Systems (GIS), geographical modeling, and geo-Python libraries, we ensure geodata processing and management are both efficient and highly professional.

• Visualization Techniques: Expertise in digital cartography is vital for designing intuitive maps that support informed decision-making. We focus on creating visually informative maps with thoughtful color schemes, styles, and labels. Advanced visualization techniques, such as shaded terrain rendering, are used to produce a pseudo-3D effect while maintaining readability and functionality as top priorities.

• Map Layers: The data are composed and made accessible as multiple layers. The base layers typically represent primary parameters such as Global Horizontal Irradiance (GHI), Direct Normal Irradiance (DNI), PV power output (PVOUT), multiple meteorological and environmental data, terrain, or land cover. The top layers often include geographic details like location names, administrative borders, water bodies, and road networks, which aid in site localization and identification.

The Solargis approach

The name Solargis is a fusion of "Solar" and "GIS" (Geographic Information System), reflecting the company's dedication to leveraging geospatial data for solar energy applications. Solargis has developed a robust portfolio of solutions that utilize its extensive expertise to deliver accurate and reliable solar resource, meteorological and environmental data for PV projects globally.

At Solargis, we leverage advanced geodata processing techniques and satellite technology to generate accurate maps. Our approach integrates high-quality solar irradiance data, meteorological, and other geographic data to effectively assist site selection, optimize project designs, and enhance the performance of solar energy projects.

Technologies used by Solargis

As an extension to our massive geodata processing, we utilize various methods to generate maps for solar project evaluation.

At Solargis, we visualize the data on maps without smoothing, as it ensures that the representation accurately reflects real-world conditions. This approach preserves important details that could be lost in a smoothed visualization, allowing for detail-based informed analysis and decision-making.

Our map products

We prepare a variety of maps tailored to different use cases and environments.

Let's take a look at the map products we generate for different use cases.

Solargis Prospect

Solargis Prospect features multiple map layers that are useful during the site selection and planning phase. It provides geographical information on long-term averages of solar resources, PV power potential, and various climate characteristics, including air temperature, wind, and snow cover. The support data describing terrain, land cover and other geographic features are available for a context.  

Global Solar atlas

The Global Solar Atlas is a free, lightweight version of Solargis Prospect, primarily targeted for educational purposes and preliminary planning. It provides users with essential information about solar energy potential across different regions.

Solargis download section

The Solargis Download section offers free solar resource and PVOUT country maps for download, which are useful for presentations, reports, or large-format printing. Users can access solar resource and PVOUT data in GIS-friendly formats.

Monthly reporting

The monthly reporting service includes a map-based evaluation of climate parameters relevant to the PV industry, including global horizontal irradiation (GHI), air temperature, and precipitation. This service is essential for regular monitoring and performance assessment of solar projects and portfolios.

Solargis Solarmaps

The Solarmaps application serves as a viewer of various meteorological and geographical data in different time aggregations. The current version offers geographic insights into monthly and yearly variability of solar and meteorological parameters, enhancing users' ability to visualize and analyze time series data in a geographical context.

Poster maps

Solargis produces high-quality, high-resolution poster maps of solar resource and PVOUT data for large-scale printing. These maps are widely used in offices and public spaces around the world.

Example: How solar resource maps for Prospect are created

• Original output from Solargis solar model: The process begins with the original output from Solargis's solar model, which generates 10, 15, and 30-minute time-series GHI and DNI data in a global scale with a spatial resolution of 2 arc minutes (nominally ~4 km). This data is then aggregated into long-term averages of monthly and yearly totals using statistical algorithms implemented in Python. The algorithm on losses from terrain shading is applied in a spatial resolution of 9 arcsecs (nominally 250 m).

• Creation of suitable map style: A suitable map style is created, featuring color-coded interval values of GHI and DNI, which enhances the visual representation of solar resource data.

• Map-tiles generation with quasi-3D effect: Map-tiles are generated with a quasi-3D effect of terrain features using in-house developed Python processing. This involves superimposing primary parameters (GHI or DNI) with other data layers, such as water bodies and terrain shading.

• Organization of map tiles in XYZ structure: The generated map tiles are organized in an XYZ structure for fast reading, ensuring efficient access to the data.

• Visualization of map tiles in Prospect interactive map window: Finally, the map tiles are visualized in the Prospect interactive map window, providing a user with a dynamic and informative interface for exploring solar resource data.