“Spottitt’s product simply does what it says. It’s an off-the-shelf solution to get insights that will increase the success of renewable energy projects. The analysis of the sites was available quickly, super helpful and easy to understand. It’s already in a GIS-compatible format, so it’s easy to pull it down and load it into our internal systems. This product is of great use for anybody that needs to quickly incorporate geospatial data and analytics into their digital site selection and site monitoring workflows”.

About the Client:

The Company is the world’s largest independent renewable energy company and has been at the forefront of the industry for over 40 years. It has delivered more than 23GW of renewable energy projects across the globe and supports an operational asset portfolio exceeding 12GW worldwide for a large client base. It employs more than 2,500 people and is active in 14 countries working across onshore and offshore wind, solar, energy storage, transmission and distribution.

Client's request to Spottitt:

The Client was looking for digital solutions to support the selection of optimal sites for solar park development, find suitable grid connection points, and monitor the condition and performance of their power generation assets in situ.

A new solution should meet the following criteria: 

  • requires no travel to the site and be fully remote
  • be global in coverage due to the geographical extent of the Client’s activities
  • be fast and responsive in terms of service request and service delivery

Project details:

After a detailed analysis of the Client’s use cases, the following work was performed and analysis delivered:

Work Specification 


Satellite Image 

Pylon detection to determine suitable grid connection points


50 cm resolution satellite imagery

Cropland detection as a part of Spottitt’s habitat classification services to inform RES on what might be high-value cropland versus lower-value land


50 cm resolution satellite imagery

Object height estimation for vegetation close to PV generation sites to determine vegetation growth and risk of reduced energy output and other disruptions



50 cm resolution satellite imagery

Four years of historical climate data analysis which allowed RES to understand the site risk of heavy rainfall, high soil moisture and flooding


Satellite-derived climate data

Comparison of solar PV condition monitoring outcome using satellite NIR spectral band vs traditional thermal surveys performed by drones


46 cm resolution satellite imagery

single image trees height estimation with satellite technology
habitat classification with satellite technology
pylon detection with satellite technology

Glossary of vocabulary:

  • Solar PV stands for “solar photovoltaic” and refers to the use of solar cells (also called photovoltaic cells) to convert sunlight directly into electricity.
  • NIR stands for “near-infrared radiation”, which is part of the electromagnetic spectrum close in frequency to thermal radiation. Solar cells’ performance is negatively impacted by dirt and dust, which lowers the reflectance of the cell; another sign of cell performance deterioration is elevated cell operating temperatures. Both of these could potentially be monitored using satellites.