An ongoing challenge with Environmental, Social, and Governance (ESG) efforts is access to robust data. In response, commercial data providers are continually developing solutions to improve insight. Here the authors discuss one of these potential improvements: the use of geospatial data within ESG focusing on the environmental (E) aspect. Geospatial data can, and is, being used for social (S), and governance (G) purposes, but these are beyond the scope of this paper. This paper explores and tests with real-world examples the potential of geospatial data approaches as means to provide additional insights into the environmental impacts of specific assets, companies, states or nations for sovereign debt investment. Starting with the current data landscape, the document runs through the open ‘environmental’ geospatial data portfolio, outlining its strengths and weaknesses. From this vantage point, the report outlines three case studies in Brazil across differing scales, highlighting various key metrics. The first looks at an asset level example, mining operations; secondly a corporate level example looking at soya production (where asset data is unavailable); and finally a national scale example for sovereign debt insights. Throughout the paper, commercial actors provide technical illustrations as to what more would be possible with additional resources. The document demonstrates that it is possible, even with limited resources and only open data, to generate robust geospatial ESG insights that often can be scaled globally – aiding financial institutions to better differentiate environmental impact at different scales and across different applications The paper concludes by discussing the various future technical developments, highlighting real-world developments, such as eDNA and machine learning, and their implications for the future of geospatial ESG. Finally, the authors look at a breakdown of the critical components of geospatial ESG tools, showing where they fall on a spectrum, with most underutilizing the technical toolkit available. As a result of this potential technical growth, combined with greater demand from the financial sector, they expect to see a rapid development of more refined geospatial ESG products and insights in the near future.