Remote sensing technologies for forest health monitoring
An example of how remote sensing technology can help monitor forest health. A recent study by Forest Service researchers mapped the health of individual conifers with airborne light detection and ranging (lidar) in an Oregon forest that has been severely affected by Armillaria root disease (A). Researchers flew a lidar instrument over the forest (B) which generates three-dimensional point cloud data (C) that can be separated into individual tree objects (D). With the help of field observations and statistical modeling, researchers were able to map tree health of individual trees across the affected forest (E).
Each year, forest insects and diseases cause widespread tree damage and mortality across the coniferous forests of the western United States. Monitoring this forest damage is expensive and time-consuming. Remote sensing technologies, such as satellite imagery, help make this monitoring possible. Although remote sensing does an excellent job finding dead trees, identifying what insect or disease is killing trees remains a challenge for scientists. Also, one single remote sensing technology cannot detect all types of tree damage; each technology has strengths and weaknesses.
Scientists from the Rocky Mountain Research Station produced a review that summarizes the different types of forest insects and diseases that attack and kill conifers in the western United States. These pests include insects that kill trees quickly, such as bark beetles, along with insects that weaken trees, such as defoliators. Many different remote sensing technologies are available for detecting tree mortality and damage. These range from multispectral and thermal cameras aboard spaceborne satellites to light detection and ranging (lidar) systems aboard airplanes. The review concludes with discussions of how researchers and managers are using these new technologies to detect and map different types of forest damage.