Estimating tree heights with images from an unmanned aerial vehicle

Birdal, Anıl Can; Avdan, Uğur; Türk, Tarık

doi:10.1080/19475705.2017.1300608

Cited by 87 publications

(57 citation statements)

References 28 publications

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“…In addition to density and canopy cover, sapling height is an important characteristic in understanding juniper re-establishment. The use of UAV-based imagery to measure tree height has been demonstrated in several studies [57][58][59], and may provide important information regarding juniper height at this study site in future research. However, the height of juniper saplings may be similar to much of the surrounding vegetation (e.g., sagebrush) so consideration should be given to the age and structure of juniper stands.…”

Section: Study Limitations and Future Researchmentioning

confidence: 78%

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

Durfee

Ochoa

Mata-González

2019

Forests

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Monitoring vegetation characteristics and ground cover is crucial to determine appropriate management techniques in western juniper (Juniperus occidentalis Hook.) 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. Groundbased 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 a 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 to 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. western juniper in particular has arisen in two primary forms: through the encroachment of juniper into areas previously dominated by sagebrush (Artemisia tridentata Nutt.), and through increases in the density of juniper in areas where it was relatively sparse [3]. Historically, juniper was largely found in areas with lower fire risk [4]. Intensive grazing, reduced fire occurrence, and favorable wetter climate conditions have all been cited as reasons for the vast juniper expansion observed in the late 19th and early 20th century [3,5].Juniper expansion is a concern in many rangeland areas as it may lead to reduced water availability for other types of vegetation. Increased juniper canopy cover has been associated with increased bare ground and decreased shrub, forb, and grass cover [6] and reductions in vegetation production and diversity [7]. Several studies [6,[8][9][10][11...

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Section: Study Limitations and Future Researchmentioning

confidence: 78%

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

Durfee

Ochoa

Mata-González

2019

Forests

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“…Modern forestry mostly requires forest information in digital format for maintaining a continuous workflow, and UAV based remote sensing offers a promising future in that regard [103,104]. In addition to that, ease of data collection, flexible control of spatial and temporal resolution, low operational costs, and safer work environment underpins the possibility of having a "UAV as a service" data collection market in the foreseeable future.…”

Section: Discussionmentioning

confidence: 99%

Individual Tree Detection from Unmanned Aerial Vehicle (UAV) Derived Canopy Height Model in an Open Canopy Mixed Conifer Forest

Mohan

Silva

Klauberg

et al. 2017

Forests

295

211

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Advances in Unmanned Aerial Vehicle (UAV) technology and data processing capabilities have made it feasible to obtain high-resolution imagery and three dimensional (3D) data which can be used for forest monitoring and assessing tree attributes. This study evaluates the applicability of low consumer grade cameras attached to UAVs and structure-from-motion (SfM) algorithm for automatic individual tree detection (ITD) using a local-maxima based algorithm on UAV-derived Canopy Height Models (CHMs). This study was conducted in a private forest at Cache Creek located east of Jackson city, Wyoming. Based on the UAV-imagery, we allocated 30 field plots of 20 m × 20 m. For each plot, the number of trees was counted manually using the UAV-derived orthomosaic for reference. A total of 367 reference trees were counted as part of this study and the algorithm detected 312 trees resulting in an accuracy higher than 85% (F-score of 0.86). Overall, the algorithm missed 55 trees (omission errors), and falsely detected 46 trees (commission errors) resulting in a total count of 358 trees. We further determined the impact of fixed tree window sizes (FWS) and fixed smoothing window sizes (SWS) on the ITD accuracy, and detected an inverse relationship between tree density and FWS. From our results, it can be concluded that ITD can be performed with an acceptable accuracy (F > 0.80) from UAV-derived CHMs in an open canopy forest, and has the potential to supplement future research directed towards estimation of above ground biomass and stem volume from UAV-imagery.

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“…For trees, the highest point in CHM within the individual crown polygon was considered as the canopy height of trees (Birdal, Avdan, & Türk, 2017), whereas the lowest point was taken as the meristem height of oil palms. As a ground-based reference, canopy height of each individual was measured using a pole, and canopy width and projection area were established with the vertical sighting method (Preuhsler, 1979, also see Pretzsch et al, 2015) in the eight cardinal directions.…”

Section: Sap Flux Measurementsmentioning

confidence: 99%

Drone‐based photogrammetry‐derived crown metrics for predicting tree and oil palm water use

et al. 2019

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Transpiration at the stand level is often estimated from water use measurements on a limited number of plants and then scaled up by predicting the remaining plants of a stand by plant size-related variables. Today, drone-based methods offer new opportunities for plant size assessments. We tested crown variables derived from drone-based photogrammetry for predicting and scaling plant water use. In an oil palm agroforest and an oil palm monoculture plantation in lowland Sumatra, Indonesia, tree and oil palm water use rates were measured by sap flux techniques.Simultaneously, aerial images were taken from an octocopter equipped with an Red Green Blue (RGB) camera. We used the structure from motion approach to compute several crown variables such as crown length, width, and volume. Crown volumes for both palms (69%) and trees (81%) explained much of the observed spatial variability in water use; however, the specific crown volume model differed between palms and trees and there was no single linear model fitting for both. Among the trees, crown volume explained more of the observed variability than stem diameter, and in consequence, uncertainties in stand level estimates resulting from scaling were largely reduced. For oil palms, an appropriate whole-plant size-related predictor variable was thus far not available. Stand level transpiration estimates in the studied oil palm agroforest were lower than those in the oil palm monoculture, which is probably due to the small-statured trees. In conclusion, we consider drone-derived crown metrics very useful for the scaling from single plant water use to stand-level transpiration.

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Estimating tree heights with images from an unmanned aerial vehicle

Cited by 87 publications

References 28 publications

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

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

Individual Tree Detection from Unmanned Aerial Vehicle (UAV) Derived Canopy Height Model in an Open Canopy Mixed Conifer Forest

Drone‐based photogrammetry‐derived crown metrics for predicting tree and oil palm water use

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