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The Use of Low-Altitude UAV Imagery to Assess Western Juniper Density and Canopy Cover in Treated and Untreated Stands

TitleThe Use of Low-Altitude UAV Imagery to Assess Western Juniper Density and Canopy Cover in Treated and Untreated Stands
Publication TypeJournal Article
Year of Publication2019
AuthorsDurfee, N, Ochoa, CG, Mata-Gonzalez, R
JournalForests: Special Issue on Forestry Applications of Unmanned Aerial Vehicles (UAVs)
Volume10(4)
Issue296
Pagination1-18
Date Published03/2019
KeywordsJuniper Woodlands; Ecohydrology; Remote sensing; Unmanned Aerial Systems; Central Oregon; Rangelands
Abstract

Monitoring vegetation characteristics and ground cover is crucial to determine appropriate management techniques in western juniper (Juniperus occidentalis) ecosystems. Remote sensing techniques have been used to study vegetation cover; yet, few studies have applied these techniques using Unmanned Aerial Vehicles (UAV), specifically in areas of juniper woodlands. We used ground-based data in conjunction with low-altitude UAV imagery to assess vegetation and ground cover characteristics in a paired watershed study located in central Oregon, USA. The study was comprised of a treated watershed (most juniper removed) and an untreated watershed. Research objectives were to: 1) evaluate the density and canopy cover of western juniper in a treated (juniper removed) and an untreated watershed; and, 2) assess the effectiveness of using low altitude UAV-based imagery to measure juniper-sapling population density and canopy cover. Ground- based measurements were used to assess vegetation features in each watershed and as a means to verify analysis from aerial imagery. Visual imagery (red, green, and blue wavelengths) and multispectral imagery (red, green, blue, near-infrared, and red-edge wavelengths) were captured using quadcopter-style UAV. Canopy cover in the untreated watershed was estimated using two different methods: vegetation indices and support vector machine classification. Supervised classification was used to assess juniper sapling density and vegetation cover in the treated watershed. Results showed that vegetation indices that incorporated near-infrared reflectance values estimated canopy cover within 0.7% to 4.1% of ground-based calculations. Canopy cover estimates at the untreated watershed using supervised classification were within 0.9% to 2.3% of ground-based results. Supervised classification applied to fall imagery using multispectral bands provided the best estimates of juniper sapling density compared to imagery taken in the summer or using visual imagery. Study results suggest that low-altitude multispectral imagery obtained using small UAV can be effectively used to assess western juniper density and canopy cover.

URLwww.mdpi.com/1999-4907/10/4/296/htm
DOI10.3390/f10040296