Offset Map

I detail the creation of from ideation to launch

6/3/20233 min read

In this blog post, I will describe the process involved in creating, detailing the project's motivation, the acquisition of information, the development process, and future plans for this venture.

Ideation and Motivation:

Approximately 2.5 years ago, while employed at the Higher School of Economics (HSE), my job entailed researching and authoring pieces on carbon offsets and the Agriculture, Forestry, and Land Use Sector (AFOLU). This responsibility demanded an in-depth study of existing carbon offset standards, methodologies, registries, and monitoring systems. Consequently, I gained a thorough understanding of both compulsory and voluntary carbon markets, their operations, and the critical intermediaries that ensure their smooth functioning. This exciting research required me to keep up with global trends and become familiar with emerging technology related to voluntary carbon markets.

It soon became clear that the current information management systems for major carbon registries were fragmented and challenging to navigate. Tasks such as researching projects, identifying developers, finding documentation, and cross-referencing sources were tedious and time-consuming. While some registries were relatively straightforward, others proved less user-friendly. Despite all the registries providing open access to their data, conducting an analysis across all registries posed significant challenges.

At that time, I did not consider addressing this problem, but rather acknowledged that a better way forward existed, one which could provide increased transparency and, ultimately, improve accessibility to information regarding carbon offsets.

Fast forward to 2023, after leaving HSE and returning to the US, I immersed myself in learning how to work with Chat GPT. Although I had prior experience with R and JavaScript, GIS, and data visualization, I had never programmed with Python or created interactive maps. Upon completing several complex projects involving web scraping, databases, and visualization of geospatial data, I decided to utilize these skills into an ambitious project. A project aimed at benefiting the environment and assisting organizations, corporations, and governments in their journey toward sustainability, climate justice and transparency.

Sourcing the Information:

The data visualized on originates from five primary sources - the four major registries (Verra, Gold Standard, Climate Action Reserve, and the American Carbon Registry) and the Voluntary Registry Offsets Database, maintained by the Berkeley Carbon Trading Project. One of the main challenges was geolocating the projects, and wherever feasible, the process was automated. However, data validation was also required, as several projects had inaccurate geolocations. Once the web app was built, this validation process began. It entailed identifying mislocated projects and correcting their geolocation data, a painstaking but crucial task that remains ongoing, given the nearly 7500 projects in the database.

The Creation Process:

Chat GPT was employed throughout the project, resulting in a web-based Flask app utilizing Python, JavaScript, and the Folium library for data visualization. The project presented several technical hurdles, including data visualization, data aggregation, filtering, table sorting, and combining plot elements with mapping elements.

One of the more challenging tasks was the development of efficient filtering. A simple web app allowing users to select filter layers from a dropdown menu would have been simpler. However, I chose a more flexible, user-friendly design that accommodates multiple selections and filtering across various categories. Consequently, the app automatically updates project types available for a selected country, ensuring only relevant options are displayed. This responsive feature extends across all project types, countries, and databases.

In tandem, I created a table compatible with these filters, providing sorting functionality. This table, when used with the interactive map, offers an efficient way to sort through carbon offset project data and categorize projects according to the user's chosen criteria. A notable use case for the table is sorting by estimated annual emission reductions, enabling users to quickly identify larger, potentially more impactful projects.

Future Plans:

At present, I am optimistic about the project. Initial responses have been overwhelmingly positive, with individuals and organizations voicing their support and expressing belief in the project's potential benefit to the wider environmental community. They appreciate the enhanced transparency and user-friendly access to carbon offset information the project provides.

As I write this, I find myself at a crossroads, contemplating the need for substantial fundraising (non-profit vs. business) and potential partnerships. One thing remains certain - I am committed to ensuring that the information presented on the web app continues to be free and publicly accessible.

Thank you for taking the time to read this. Feel free to explore the web app at and send your feedback to