From Deals to Data: Conservation Finance and the Role for Technology

By Carolyn duPont on January 13, 2020

Gearing up for the annual Credit Suisse Conservation Finance event this week, I’m thinking back to the first time I attended the meeting as a wide-eyed grad student, having recently published a paper on green bonds and land conservation.

My driving interest since then has remained the same — how can we get more money into conservation, quickly and at scale? Several years later, however, I’m now coming to the event with a new lens — thinking about how technology can facilitate large-scale investments in conservation.

Prior to joining the growth and partnerships team at Upstream Tech in early 2019, I was working in the finance world, focused on structuring transactions that could bring new capital into conservation work. Over my time working in conservation finance, I started to notice a set of recurring challenges that came up at conference after conference and in deal after deal:

  1. Building a Sufficient Deal Pipeline: Deal development in new markets is challenging and takes time. It can be hard to find enough of the right type of projects with the right risk/return profile at the right time. As a result, it’s difficult to aggregate deals into a size of investment that’s attractive to investors. “Pilot fatigue” has set in, coupled with an increasing urgency to get to scale.
  2. Optimizing Conservation Impact: Even with a pool of capital in hand, it can be hard to systematically source projects that maximize impact. Often, in the absence of tools to identify projects at scale, other factors such as good existing stakeholder relationships end up being the key criteria for pursuing a project for financing.
  3. Cost-effectively Monitoring and Accounting for Outcomes: Finally, measuring success is challenging and often cost-prohibitive. While we all want to be learning from investments and demonstrating impact to investors and funders, the reality is that monitoring and verification are expensive. Anything that involves field visits, scientific testing, or advanced modeling quickly adds to transaction costs.

An animated example of Lens Upstream Tech’s Lens platform automating the monitoring process — using satellite data to detect a timber harvest on a conservation property.

This is what excited me about Upstream Tech’s work, and what ultimately motivated me to jump on the bandwagon. I met Marshall and Alden, Upstream’s co-founders, a handful of years ago when I was working in venture capital for the State of Massachusetts. I never imagined myself working for a tech company, but the longer I spent trying to navigate the challenges laid out above, the more I saw the need for innovative solutions to escalate the scale and pace of conservation finance deals.

At Upstream Tech, the services we provide are aligned to address core challenges I saw: helping build deal pipeline, identify high-impact conservation opportunities, and measure success. The more I’ve learned, the more I’ve been blown away by the power of remote sensing, machine learning, and cloud-based computing for conservation applications. For example, satellite data enables us not just to monitor ongoing changes, but also to look back in time through the archives and understand how landscapes have changed in the past years — allowing for a richer understanding of where to prioritize conservation work going forward. Coupling these capabilities with our team’s conservation expertise allows us to help partners navigate and overcome barriers to investment.

Workflow to enable high-impact
Workflow to enable high-impact investments

To take the agricultural space as an example, we have developed a service called AgTrends to assess field-level management practices and track changes that impact watershed health.

By leveraging satellite data and machine learning for rapid analysis, we can delineate farm fields and identify those that meet certain criteria, such as having a history of a certain kind of crop cultivation or not yet showing evidence of cover cropping practices that would reduce nutrient run-off into waterways. We can then rapidly build project pipelines by scanning watersheds to surface a set of possible sites for investment in conservation practices.

Through capabilities that we’ve developed in partnership with The Freshwater Trust, we can help partners optimize the outcomes of conservation investments given budget constraints or particular water quality goals — delivering a curated set of field-level management recommendations to achieve water use or nutrient runoff outcomes.

And finally, our technology can then support monitoring and verification programs by detecting practices implemented on a field level and provides year-over-year progress tracking.

Scenario optimization in agriculture
Scenario optimization in agriculture
Screenshot of scenario optimization tool developed with The Freshwater Trust, identifying high-priority fields to target for improvements in management practices.

Our work in the agricultural space is just one example, and we are actively engaged in bringing this same set of capabilities to environmental markets, land conservation, and water planning and forecasting. Fundamentally, we believe that technology can inform more transparent and cost-effective project scoping and monitoring systems that underpin investments at scale.

While I joke to friends that I have clearly drank the tech Kool Aid, I think it’s important to be thoughtful about how we balance technology and interpersonal relationships that are critical to the success of conservation work over time. At a recent Conservation Finance Roundtable, one panelist asked whether “technology can be a substitute for trust” in environmental markets, in the sense that it can be used to monitor and verify if projects are taking place, and whether outcomes are achieved.

In my view, it’s not an either/or — technology is an enabler of trust. If there’s something that investors, farmers, municipalities, and community members can all look at to get a shared understanding of what’s happening, that builds a place for constructive dialogue around what’s working and not, and why. That shared understanding based on accurate, up-to-date data builds a stronger foundation to scale up these kinds of cutting edge partnerships and deals.

Now that I’ve been on the team for almost a year, I’ve been told by my colleagues that at some point I need to stop referring to our work as “satellite magic.” But for now, it feels appropriate. I’m optimistic and continually amazed at the capabilities technology can bring to scaling conservation investments, and excited for the work that lies ahead of us.

PS: I encourage everyone who’s not familiar with satellite technology to read through my colleague Jessie’s Satellites 101 post or join an upcoming webinar.

And if you’re looking to learn more about conservation finance, the Conservation Finance Network is an incredible resource for learning and connecting.