The Center for Data Innovation recently spoke with Susan Graham, CEO of Dendra, a company based in the United Kingdom that offers AI-powered solutions for large-scale ecosystem restoration and biodiversity management. Graham discussed how Dendra uses high-resolution imagery and machine learning to help industries, governments, and communities monitor landscapes and drive environmental recovery efforts.
David Kertai: What inspired you to create Dendra ?
Susan Graham: We founded Dendra in 2014 with the vision of leveraging cutting-edge technology to address the pressing challenges of ecosystem degradation. Initially, our focus was on developing drone-based solutions to accelerate reforestation efforts. However, as we engaged with various stakeholders and understood the complexities of ecosystem restoration, our mission expanded. Today, Dendra empowers industries, governments, and communities with AI driven tools to make informed decisions for sustainable environmental stewardship.
Kertai: What is Dendra’s Optical Intelligence Platform?
Graham: Dendra’s Optical Intelligence Platform is designed for industries like mining, environmental consulting, and government agencies that manage large or multiple sites. These users need a system that can both provide a broad, landscape-level view and zoom in to detect specific, localized challenges, such as erosion, invasive species, or human-made disturbances.
The platform uses a combination of drones, planes, and ground surveys to capture ultra-high-definition imagery that generates massive volumes of highly detailed data. Dendra’s technology is built to manage this scale of information efficiently, while making it actionable. By identifying ecological changes down to the species level, the platform enables users to gain both a macro and micro understanding of their landscapes. This comprehensive insight empowers better decision-making for ecosystem management, restoration efforts, and regulatory reporting.
Kertai: How does Dendra use AI to analyze geospatial data for ecosystem management?
Graham: Dendra’s AI tools analyze captured images to detect ecological features and environmental changes. These insights are delivered throughout the platform, empowering users to monitor site conditions in real time, measure the impact of restoration efforts, and make data-driven decisions to better manage ecosystems. The system also identifies and prioritizes areas for intervention by assessing ecological connectivity and restoration potential. This enables more strategic, forward-looking planning and supports sustainable management practices tailored to the unique characteristics of each ecosystem.
Kertai: How are Dendra’s AI tools trained to recognize different environmental features?
Graham: Dendra’s AI models are continually trained and refined using our databases, allowing the system to recognize subtle differences in environmental features and conditions. Dendra uses supervised and reinforcement learning techniques, where the AI models learn from repeated exposure to expertly labeled data, gradually improving classification accuracy over time. Our AI systems produce insights that are shared through a simple interface, so users can easily plug them into their own systems and tools. Through Dendra’s platform, users can view before-and-after snapshots of their sites, highlighting changes over time and tracking the specific classes, like certain plant species, they care about. Annual or multi-year monitoring further enables users to spot trends, assess the effectiveness of interventions, and build a valuable dataset for long-term ecosystem management.
In addition, our platform allows field teams to integrate ground-truth verification data, where on-the-ground observations are fed back into the system. This feedback loop continuously updates and retrains the AI models, ensuring outputs stay aligned with real-world conditions and remain scientifically robust across different sites and ecosystems. By combining massive biodiversity datasets, machine learning models, and ongoing field validation, Dendra ensures its AI tools provide highly detailed, actionable insights to support better ecosystem management at scale.
Kertai: Can you share any examples of Dendra’s work promoting environmental sustainability?
Graham: We’ve partnered with Abu Dhabi to support its vision of restoring mangroves along the coastline. Dendra’s AI system maps sapling growth, tracks mangrove extent, and monitors habitat changes over time. The platform has also identified areas of waste and debris accumulation. Access to this detailed data inspired local action with community groups organizing a targeted cleanup campaign, removing tons of trash in a single day.
Dendra’s technology has also made a significant impact on mining sites in Australia. Traditional ground-based monitoring had missed the full extent of invasive plant species spread, as surveys were limited to easily accessible areas. Using remote sensing and AI analysis, we provided comprehensive landscape-level mapping, allowing environmental teams to identify and manage invasive species across entire sites. Within just two years, these efforts led to substantial improvements in native biodiversity and ecosystem health, a major step forward for long-term sustainability.
Together, these examples show how tackling localized ecosystem challenges, site by site, can contribute to solving the global biodiversity crisis. By leveraging precise, data-driven tools like ours, individuals, industries, and communities can work more effectively to address the broader ecological challenges facing our planet.
