Date of Award

8-2014

Document Type

Thesis

Degree Name

Master of Science (MS)

Legacy Department

Forest Resources

Committee Chair/Advisor

Post, Christopher

Committee Member

Mikhailova , Elena

Committee Member

Gering , Lawrence

Abstract

In contrast to standard aerial imagery, unmanned aerial systems (UAS) utilize recent technological advances to provide an affordable alternative for imagery acquisition. Increased value can be realized through clarity and detail providing higher resolution (2-5 cm) over traditional products. Many natural resource disciplines such as urban forestry will benefit from UAS. Tree inventories for risk assessment, biodiversity, planning, and design can be efficiently achieved with the UAS. Recent advances in photogrammetric processing have proved automated methods for three dimensional rendering of aerial imagery. Point clouds can be generated from images providing additional benefits. Association of spatial locational information within the point cloud can be used to produce elevation models i.e. digital elevation, digital terrain and digital surface. Taking advantage of this point cloud data, additional information such as tree heights can be obtained. Several software applications have been developed for LiDAR data which can be adapted to utilize UAS point clouds. This study examines solutions to provide tree inventory and heights from UAS imagery. Imagery taken with a micro-UAS was processed to produce a seamless orthorectified image. This image provided an accurate way to obtain a tree inventory within the study boundary. Utilizing several methods, tree height models were developed with variations in spatial accuracy. Model parameters were modified to offset spatial inconsistencies providing statistical equality of means. Statistical results (p = 0.756) with a level of significance (α = 0.01) between measured and modeled tree height means resulted with 82% of tree species obtaining accurate tree heights. Within this study, the UAS has proven to be an efficient tool for urban forestry providing a cost effective and reliable system to obtain remotely sensed data.

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