Date of Award
2020
Document Type
Thesis
Publication Status
Version of Record
Submission Date
October 2026
Thesis/Dissertation Advisor [Chair]
Nagarajan, Sudhagar
Abstract
Land cover classification is necessary for understanding the state of the surface of the Earth at varying regions of interest. Knowledge of the Earth’s surface is critical in land-use planning, especially for the project study area Jupiter Inlet Lighthouse Outstanding Natural Area, where various vegetation, wild-life, and cultural components rely on adequate land-cover knowledge. The purpose of this research is to demonstrate the capability of UAV true color imagery for land cover classification. In addition to the objective of land cover classification, comparison of varying spatial resolutions of the imagery will be analyzed in the accuracy assessment of the output thematic maps. These resolutions will also be compared at varying training sample sizes to see which configuration performed best.
Extent
101 p.
Recommended Citation
Castillo, Stephen M., "OBJECT-BASED LAND COVER CLASSIFICATION OF UAV TRUE COLOR IMAGERY" (2020). Electronic Theses and Dissertations 2020 - Present. 563.
https://digitalcommons.fau.edu/etd_general/563
Identifier
FA00013454
Comments
Includes bibliography.|Thesis (M.S.)--Florida Atlantic University, 2020.|FAU Electronic Theses and Dissertations Collection|Includes bibliography.