1 research outputs found
Hyperspectral, thermal and LiDAR remote sensing for red band needle blight detection in pine plantation forests
PhD ThesisClimate change indirectly affects the distribution and abundance of forest insect pests and
pathogens, as well as the severity of tree diseases. Red band needle blight is a disease
which has a particularly significant economic impact on pine plantation forests
worldwide, affecting diameter and height growth. Monitoring its spread and intensity is
complicated by the fact that the diseased trees are often only visible from aircraft in the
advanced stages of the epidemic. There is therefore a need for a more robust method to
map the extent and severity of the disease. This thesis examined the use of a range of
remote sensing techniques and instrumentation, including thermography, hyperspectral
imaging and laser scanning, for the identification of tree stress symptoms caused by the
onset of red band needle blight. Three study plots, located in a plantation forest within
the Loch Lomond and the Trossachs National Park that exhibited a range of red band
needle blight infection levels, were established and surveyed. Airborne hyperspectral and
LiDAR data were acquired for two Lodgepole pine stands, whilst for one Scots pine stand,
airborne LiDAR and Unmanned Aerial Vehicle-borne (UAV-borne) thermal imagery
were acquired alongside leaf spectroscopic measurements. Analysis of the acquired data
demonstrated the potential for the use of thermographic, hyperspectral and LiDAR
sensors for detection of red band needle blight-induced changes in pine trees. The three
datasets were sensitive to different disease symptoms, i.e. thermography to alterations in
transpiration, LiDAR to defoliation, and hyperspectral imagery to changes in leaf
biochemical properties. The combination of the sensors could therefore enhance the
ability to diagnose the infection.Natural Environment Research Council (NERC) for funding
this PhD program (studentship award 1368552) and providing access to specialist
equipment through a Field Spectroscopy Facility loan (710.114). I would like to thank
NERC Airborne Research Facility for providing airborne data (grant: GB 14-04) that
made the PhD a challenge, to say the least. My sincere gratitude goes to the Douglas
Bomford Trust for providing additional funds, which allowed for completion of the
UAV-borne part of this research