Remote sensing for ash identification and pre-visual decline assessments
PARTNERS: USDA Forest Service Northern Research Station; University of New Hampshire Complex Systems Research Center; Forest Health Technology Enterprise Team (FHTET); USDA Animal and Plant Health Inspection Service
SUMMARY: The Emerald Ash Borer (EAB) is an exotic insect pest currently threatening ash species in the Great Lakes region. Research has been proposed that would develop techniques to create a species map that delineates overstory ash trees and detect incipient health decline in ash trees by collaborating with current remote sensing efforts in Michigan. The research objectives include locating and measuring ground control plots to be used for calibrating and validating remote sensing imagery covering a range of ash abundance and health, using hyperspectral remote sensing imagery to map and validate ash abundance and health, and creating a map of high priority areas for ground inspection crews to examine for possible EAB infestation. Image acquisitions, ground truth data collections, and image processing guidelines will be compiled for easy use and rapid implementation by forest managers. This will facilitate the monitoring of EAB spread and severity and any new threats to forest health that may develop in the future.
EFETAC'S ROLE: EFETAC provided funding for this project.
STATUS: Completed
PROGRESS: The field-based decline rating system developed for this study was able to capture and summarize the full range of ash decline that existed within the study areas. These data were used in conjunction with hyperspectral remote sensing imagery to create landscape scale maps of predicted forest health with an emphasis on ash species in areas that are currently being impacted by EAB infestation. This study shows that commercially available airborne hyperspectral imagery can be used to assess detailed ash decline on a landscape scale. The combination of traditional plot-level forest health assessment techniques with commercially available hyperspectral remote sensing imagery can produce continuous landscape scale maps of predicted forest health. These data products, which can highlight areas of pre-visual decline, represent a significant advance in the ability to identify forest health problems earlier than ever; this should prove essential to the ultimate management and control of invasive species such as EAB.
Pontius, Jennifer; Martin, Mary; Plourde, Lucie; Hallett, Richard. 2008. Ash decline assessment in emerald ash borer-infested regions: A test of tree-level, hyperspectral technologies. Remote Sensing of Environment. 112: 2665-2676.
LINKS:
CONTACT:
- Jennifer Pontius, Northern Research Station Research Ecologist, jennifer.pontius@unh.edu or (603) 868-7739
- Richard Hallett, Northern Research Station Research Ecologist, rhallett@fs.fed.us or (603) 868-7657
Updated May 2010
