How ARL is automating forest research

July 30, 2026

Forests absorb nearly 16 billion metric tonnes of carbon per year, making them an incredibly valuable carbon sink. Studying the forest growing season can help scientists understand the productivity of the forest and the processes that drive carbon transfer from the atmosphere to trees. Monitoring changes from season to season is vital, as trees serve as an indicator for agricultural cycles, food webs, and global climate patterns.

Looking over the top of a forest canopy, the left side of the forest is shaded by clouds in the bright blue sky. There is a scientific instrument extending into the image on the left.
View from the top of the Chestnut Ridge tower. Credit: NOAA/ARL

To better understand these dynamics, ARL launched a project at the Chestnut Ridge research site in Oak Ridge, Tennessee to study the dynamics between the atmosphere and the forest. By monitoring the vertical structure of the leaf canopy, researchers are trying to further understand carbon intake, the growing season, and weather impacts over time. While initial data collection currently requires frequent, manual field trips, the lab is now developing a more automated system. This effort builds on a previous project led by Will Pendergrass, who conducted leaf coverage experiments at Chestnut Ridge between 2015 and 2016.

For over 40 years ARL’s Atmospheric Turbulence and Dispersion Division (ATDD) has been taking measurements of deciduous trees in east Tennessee. In 2005 Chestnut Ridge was established to expand data collection for meteorological, energy flow and tree cover monitoring. The site features a 60 meter walk up tower in the middle of dense forest, allowing researchers to get above the canopy to monitor leaf coverage and measure how turbulent the air is.

Improving ways to collect data

The primary focus of this project is to measure the Leaf Area Index (LAI), which determines how much sunlight and precipitation get intercepted by leaves before hitting the ground. This allows researchers to track the growth season timeline. Researchers collect LAI using a device called the LAI-2200C Canopy Analyzer. This involves two individuals going to the walkup tower; one climbs up and the other stays at the bottom. When in position, they must start sensors at the same time to get a proper measurement. The team of Tim Wilson, Mauricio Toro and Mike Rutherford have done this manual work almost every week since early March and plan to take manual measurements until next March.

three men in a garage-type building. The two in front are wearing hardhats and climbing harnesses.
(L to R) Mauricio Toro, Tim Wilson and Mike Rutherford ready to take LAI measurements. Mauricio and Mike are dressed in safety equipment to climb the tower. Credit: NOAA/ARL
Circular image in the middle of a black rectangle. The image shows trees from the ground looking straight up into the sky. There is some leaf cover and the leaves are the bright yellow-green of new growth.
Leaf Area Index image captured in the Spring. Credit: NOAA/ARL
circular image in a black rectangle. View is from the floor of the forest looking up to see trees extending up. There is significant, dark green leaf cover.
Leaf Area Index photo taken in the summer. Credit: NOAA/ARL
Circular image in a black rectangle. View is from the floor of the forest looking up to see trees extending up. Leaves cover about half of the visible sky and are turning shades of yellow, orange and red.
Leaf Area Index photo taken in the fall. Credit: NOAA/ARL
Circular image in a black rectangle. View is from the floor of the forest looking up to see trees extending up. There are very few leaves on the trees so much of the sky is visible.
Leaf Area Index photo captured in the winter. Credit: NOAA/ARL

While this collection method works, to improve efficiency and consistency, the team is developing an onsite camera to measure LAI. This system will use digital hemispherical photography, where a camera takes fisheye photos pointed directly up at the canopy. The photos will be automatically transmitted and run through a software program to compute the LAI estimate. The camera will be programmed to take photos soon after sunrise and before sunset. This is because direct daytime sun makes it difficult for the algorithm to differentiate between the blue sky and the semi-transparent leaves.

In the future the team is considering installing multiple instruments at different levels of the tower, or sending a mobile device up and down to capture exactly how the vertical structure of the canopy changes over the seasons.

This project will also allow the lab to look backward: between 2015-2016, Will Pendergrass (ret.)  took fish eye photographs of the forest canopy that were never analyzed to estimate LAI. As part of the current initiative, ARL will finish the analysis to estimate the LAI and then compare today’s data with that of a decade ago.