Samuel D. Jones

Works by this author

Language: English

Wildland Fire Tree Mortality Mapping from Hyperspatial Imagery Using Machine Learning

Samuel D. Jones
Thesis title page

Submitted to the Department of Mathematics and Computer Science in partial fulfillment of the requirements for the degree of Bachelor of Arts

The use of small Unmanned Aircraft Systems (sUAS) for obtaining wildland imagery has enabled the production of more accurate data regarding the effects of fire on forested land. This increase in precision enables accurate detection of trees from hyperspatial imagery, and thus the calculation of canopy cover. When pre-fire data is compared with post-fire data from existing canopy cover products such as the LANDFIRE project, a measure of tree mortality, which is a measure of burn severity, can be calculated from the difference between the two.
English
Type: 
Thesis
WHDL ID: 
WHDL-00021270