Unmanned aircraft in nature conservation: an example from plant invasions

Müllerová, Jana; Bartaloš, Tomáš; Bruna, J; Dvořák, Petr; Vítková, Michaela

doi:10.1080/01431161.2016.1275059

Cited by 65 publications

(51 citation statements)

References 51 publications

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“…In general, this approach can allow environmental managers to monitor the distribution and spread of invasive plants in similar situations once the classification models are adjusted to the respective species. Environmental managers should be strongly encouraged to use low-cost UAS approaches to avoid high costs and timeconsuming field surveys, especially in sites of low accessibility (Wan et al, 2014;Chabot et al, 2016;Hill et al, 2016;Müllerová et al, 2017). Minimizing in situ mapping and control operations is also an added advantage for using UAS, because reduction in habitat disturbance can encourage the recovery of native plants that are threatened by biological invasion (Mack and D'Antonio, 1998;Huston, 2004).…”

Section: Applicability Of Low-cost Uasmentioning

confidence: 99%

“…Small model aircrafts, also called fixed-wing UAS, as an alternative to widely used multirotor drones, have proved successful as an environmental remote sensing platform (Laliberte et al, 2011;Anderson and Gaston, 2013;Colomina and Molina, 2014;Müllerová et al, 2017). Due to the uplift generated by airflow over the wings and more efficient aerodynamics, these platforms provide the advantage of longer flight times at higher speeds and greater payloads and, thus, can cover larger survey areas per flight compared to multirotor UAS.…”

Section: Introductionmentioning

confidence: 99%

“…However, these studies used either expensive high-end UAS (e.g., Michez et al, 2016) or commercial image processing and analysis software. For example, Müllerová et al (2017) used a self-built, low-cost fixed-wing UAS to detect invasive Robinia pseudoacacia in a recently published study, but applied commercial stitching software. Such sophisticated software products are usually expensive, often exceeding 3,000 US dollars for a single license.…”

Section: Applicability Of Low-cost Uasmentioning

confidence: 99%

“…Unmanned Aerial Systems (UAS), popularly known as drones, introduce a new remote sensing technique that may become an applicable and affordable alternative to conventional approaches, as they reduce costs and increase the spatial resolution of aerial images (Wan et al, 2014;Dvořák et al, 2015;Chabot et al, 2016;Hill et al, 2016;Müllerová et al, 2016Müllerová et al, , 2017. The technical development, component miniaturization, and increased sales in recent years resulted in the rapid growth of UAS as an environmental remote-sensing platform.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Open-Source Processing and Analysis of Aerial Imagery Acquired with a Low-Cost Unmanned Aerial System to Support Invasive Plant Management

Lehmann¹,

Prinz

Ziller³

et al. 2017

Front. Environ. Sci.

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Remote sensing by Unmanned Aerial Systems (UAS) is a dynamic evolving technology. UAS are particularly useful in environmental monitoring and management because they have the capability to provide data at high temporal and spatial resolutions. Moreover, data acquisition costs are lower than those of conventional methods such as extensive ground sampling, manned airplanes, or satellites. Small fixed-wing UAS in particular offer further potential benefits as they extend the operational coverage of the area under study at lower operator risks and accelerate data deployment times. Taking these aspects into account, UAS might be an effective tool to support management of invasive plant based on early detection and regular monitoring. A straightforward UAS approach to map invasive plant species is presented in this study with the intention of providing ready-to-use field maps essential for action-oriented management. Our UAS utilizes low-cost sensors, free-of-charge software for mission planning and an affordable, commercial aerial platform to reduce operational costs, reducing expenses with personnel while increasing overall efficiency. We illustrate our approach using a real example of invasion by Acacia mangium in a Brazilian Savanna ecosystem. A. mangium was correctly identified with an overall accuracy of 82.7% from the analysis of imagery. This approach provides land management authorities and practitioners with new prospects for environmental restoration in areas where invasive plant species are present.

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Section: Applicability Of Low-cost Uasmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Applicability Of Low-cost Uasmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Open-Source Processing and Analysis of Aerial Imagery Acquired with a Low-Cost Unmanned Aerial System to Support Invasive Plant Management

Lehmann¹,

Prinz

Ziller³

et al. 2017

Front. Environ. Sci.

View full text Add to dashboard Cite

show abstract

“…Recent developments in the use of Unmanned Aerial Vehicles (UAV) make these a low-cost option to acquire high resolution imagery for local-scale investigations of vegetation dynamics and ecological processes [34]. Recently, UAVs have gained interest as a data acquisition tool for targeted monitoring, largely for the management of invasive species where timely and repeated assessments are required [35,36]. In comparison to more conventional methods for acquiring high resolution imagery, such as images obtained from aircraft or satellites, the operational requirements and cost of UAVs are reduced as they can be operated by personnel with basic training.…”

Section: Introductionmentioning

confidence: 99%

Mapping Wild Leek through the Forest Canopy Using a UAV

Leduc

Knudby

2018

Remote Sensing

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Abstract:Wild leek, an endangered plant species of Eastern North America, grows on forest floors and greens up to approximately three weeks before the trees it is typically found under, temporarily allowing it to be observed through the canopy by remote sensing instruments. This paper explores the accuracy with which wild leek can be mapped with a low-flying UAV. Nadir video imagery was obtained using a commercial UAV during the spring of 2017 in Gatineau Park, Quebec. Point clouds were generated from the video frames with the Structure-from-Motion framework, and a multiscale curvature classification was used to separate points on the ground, where wild leek grows, from above-ground points belonging to the forest canopy. Five-cm resolution orthomosaics were created from the ground points, and a threshold value of 0.350 for the green chromatic coordinate (GCC) was applied to delineate wild leek from wood, leaves, and other plants on the forest floor, with an F1-score of 0.69 and 0.76 for two different areas. The GCC index was most effective in delineating bigger patches, and therefore often misclassified patches smaller than 30 cm in diameter. Although short flight times and long data processing times are presently technical challenges to upscaling, the low cost and high accuracy of UAV imagery provides a promising method for monitoring the spatial distribution of this endangered species.

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Estimating the cover of Phragmites australis using unmanned aerial vehicles and neural networks in a semi‐arid wetland

Higgisson

Cobb

Tschierschke

et al. 2021

River Research & Apps

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Unmanned aerial vehicles (UAVs) provide high‐spatial‐resolution imagery and allow the collection of data in locations or periods of time where field‐based data collection is challenging or impossible, such as in wetlands and floodplains. Computational deep learning techniques are transforming the way in which remotely sensed imagery and data can be used and are having an increasing role in remote sensing. Here, we describe a method using UAV and machine learning technique convolutional neural networks (CNNs) to estimate the cover of wetland features Phragmites australis reeds, leaf litter, water, bareground, and other vegetation in a large inland floodplain wetland in Western New South Wales (NSW), Australia. We firstly describe the process we took to train, validate, and test the model. We describe the model's performance by calculating a range of performance indicators and provide density maps and results from individual sites. The model had an overall accuracy of 0.947 and recognized and estimated Phragmites australis reeds to a very high accuracy (>98%). Here, we show an effective, accurate, and reproducible way to estimate the cover of Phragmites australis reeds and other wetland features using UAV and CNNs in a semi‐arid wetland.

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Unmanned aircraft in nature conservation: an example from plant invasions

Cited by 65 publications

References 51 publications

Open-Source Processing and Analysis of Aerial Imagery Acquired with a Low-Cost Unmanned Aerial System to Support Invasive Plant Management

Open-Source Processing and Analysis of Aerial Imagery Acquired with a Low-Cost Unmanned Aerial System to Support Invasive Plant Management

Mapping Wild Leek through the Forest Canopy Using a UAV

Estimating the cover of Phragmites australis using unmanned aerial vehicles and neural networks in a semi‐arid wetland

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