Recipient Organization
LINCOLN UNIVERSITY
820 CHESTNUT ST
JEFFERSON CITY,MO 651023537
Performing Department
Agriculture
Non Technical Summary
The invasive insect pest, emerald ash borer, infects and eventually kills ash trees and is currently spreading across Missouri. The emerald ash borer (EAB) infestation was first detected in Missouri near Lake Wappapello, Wayne County in 2008. It has since spread to eighty-seven Missouri Counties, including Cole County. Early detection of emerald ash borer (EAB) infestation is critical to managing the spread of this pest through biological or chemical control. Small-unmanned aerial vehicle (sUAV) or drone-based studies will be used to establish a remote sensing-based approach for mapping ash trees and assess EAB infestations. To accomplish this, sUAV/drone images will be collected over targeted EAB infested sites. The data will be processed and field verified. The research work is anticipated to produce sUAV data-based procedures that can be used to identify ash trees, map and assess the severity of EAB infestation in forest stands.
Animal Health Component
100%
Research Effort Categories
Basic
0%
Applied
100%
Developmental
0%
Goals / Objectives
The objectives of this research are threefold: 1) Utilize remote sensing technology, primarily, small unmanned aerial vehicle (sUAV) and high spatial resolution satellite imagery to map ash trees in Jefferson City and surroundings, both in rural and urban settings (Cole County), 2) Formulate digital image processing producers to identify and map the extent of EAB infestation in ash trees in target areas, and 3) Assess the effectiveness mitigation procedures, biological or chemical, implemented to control the spread of EAB infestations.
Project Methods
Small-unmanned aerial vehicle (sUAV) based very high spatial resolution multispectral imagery in conjunction with high spatial resolution multispectral satellite imagery will be used to investigate the EAB infestation in and around Jefferson City, Central Missouri. A MicaSense RedEdge 3 multispectral and Zenmuse X5 cameras mounted on a DJI Matrice 600 Pro sUAV will be used to collect imagery over target areas. In addition, archival high spatial resolution multispectral satellite imagery including WorldView-2 and 3 [spatial resolution <0.50m panchromatic and <2.0m multispectral (8-band)] and Pleiades-1A and 1B [spatial resolution 0.5m panchromatic and 2m multispectral (4-band)] will be sought for this study. The sUAV and satellite images will be subjected to various image processing techniques; the goal being identifying and mapping ash trees and also assessing the health status of the EAB infested trees. To accomplish this different vegetation indices using red and infrared bands, classification approaches including Geographic object-based image analysis (GEOBIA), and integration with GIS analytical tools will be implemented. To verify the remote sensing findings field surveys will be conducted with guidance from high-end mapping-grade GPS receivers. The resources at Lincoln University's Center of Excellence in Geospatial Information Science Laboratory will be used to collect, process, and analyze the remote sensing imagery. A graduate and an undergraduate student will be involved in the project. They will play an integral role in data collection and processing. Federal Aviation Administration rules limit the flying height of sUAV at or below 400 ft. above the ground. Since the flying height determines the pixel size different flying heights will be experimented with to select the optimal flying height that enables the identification of ash trees, EAB infested or otherwise. A big advantage of sUAV imagery is that one can collect data as frequently as needed barring adverse weather conditions, as a multitemporal data set is critical in monitoring vegetation changes over time. On the other hand, a drawback of sUAV imagery is their limited aerial extent (a few acres). One cannot envisage mapping a large area using sUAV technology. To overcome this the sUAV imagery will be paired with high spatial resolution satellite imagery that, in general, have swath widths of <20km, which are better suited for forest, stand level studies. The satellite imagery will also be processed to identify ash trees and EAB infestations. Moreover, the sUAV imagery findings will be used as a reference to guide the identifications of EAB infestations in the high spatial resolution satellite imagery. However, the archival pool of high spatial resolution satellite imagery is very limited. It can hinder the chance of obtaining imagery that is relevant for vegetation change studies over time.