Enoch Levandovsky

Works by this author

Language: English

Mapping Burn Extent of Large Wildland Fires from Satellite Imagery Using Machine Learning Trained from Localized Hyperspatial Imagery

Enoch Levandovsky
Thesis title page

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

Many wildland fire researchers are challenged to get an accurate burn acreage estimates of a wildland fire due to technology limitations. This research aids wildland fire researchers in determining the accuracy of mapping wildland fires by using sUAS (small Unmanned Aircraft System) imagery when comparing hyperspatial to sUAS imagery resampled to satellite scale resolution in. This project made the assumption that sUAS burn extent data was accurate. This assumption allowed for the resampled training data using fuzzy logic control as the method for improving satellite resolution data.
English
Type: 
Thesis
WHDL ID: 
WHDL-00021274