Using Sensor Data to Inform and Evaluate Environmental Initiatives

Fellows: Nadya Calderon, Scott Cambo, Christopher Lazarus, Raphael Stern
Data Science Mentor(s): Varun Chandola
Project Partner: Conservation International

Conservation International (CI) is a non-profit organization that works to protect nature through scientific research and partnerships with communities, industry, and governments. A key aspect for evaluating the impact of conservation projects is to account for natural capital — ecosystem goods and services, such as fresh water, flood control, agriculture, and forest products.

The Tropical Ecology, Assessment and Monitoring (TEAM) Network, originally created by CI, is now a partnership among CI, the Smithsonian Institution, and the Wildlife Conservation Society. TEAM’s global network of scientists is collecting and distributing near-real-time data on trends in biodiversity, climate, land cover change and ecosystem services. In many sites, TEAM collects sensor data to understand the status of tropical ecosystems in terms of meteorological variables, vegetation, and wildlife in the tropical forest. When triggered by motion, camera traps deployed throughout these sites take a photograph and record the temperature.

To help TEAM get the most information from this sensor network, we developed an algorithm for interpolating and extrapolating camera trap data to generate micro-climate information for protected sites. TEAM is now able to use the algorithm to better understand how micro-climate changes are related to the patterns of movement of vertebrate species that have a very narrow temperature window of comfort. The project helped CI and other environmental organizations understand how this high-resolution, spatiotemporal data can assist current and future monitoring initiatives.

You can read more about this project here.