Assessing the impacts of canopy openness and flight parameters on detecting a sub-canopy tropical invasive plant using a small unmanned aerial system

Perroy, Ryan L.; Sullivan, Timo; Stephenson, Nathan

doi:10.1016/j.isprsjprs.2017.01.018

Cited by 47 publications

(57 citation statements)

References 48 publications

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“…In total, we downloaded 131 articles that were then re-checked to assess their relevance. Ultimately, we only found 18 original-research articles that assessed both understorey vegetation and used high resolution remote sensing (Table 1; [1,18,19,22,[36][37][38][39][40][41][42][43][44][45][46][47][48][49]). We reviewed all of them.…”

Section: Resultsmentioning

confidence: 99%

“…Getzin et al [39] used RGB data with 70 mm resolution and correlated it with field work to successfully assess understorey diversity within canopy gaps of deciduous and deciduous/coniferous forests of Germany. Conversely, using RGB data to identify an invasive understorey tree in a tropical forest of Hawaii, Perroy et al [46] acquired data at different heights, with pixel resolution between 14 and 53 mm, with different camera angles and degrees of canopy cover, and found that their finest resolution (flying at 30 m) only detected 41% of the tree stands, that oblique angles increased the detection rates, but also that their methods failed to detect individuals under thick overstorey (<10% openness).…”

Section: Resultsmentioning

confidence: 99%

“…The most important issues relevant to the assessment of understorey species can be the lack of penetration of spectral sensors or partial penetration of active sensors (due to visual obstruction or signal thinning by overstorey, respectively), and the intrinsic characteristics of species in the understorey, an issue that has been reported by several authors [1,6,38,46,48,53]. In relation to penetration, it is unsurprising that the main success stories of UAS-based understorey monitoring occur in open environments where 'above canopy' images can be acquired without concealing understorey species.…”

Section: Recommendationsmentioning

confidence: 99%

“…UAS systems can attain ultra-high resolutions related to sensor capabilities (e.g., megapixel resolution of the camera) and to the UAS-flight elevation, with finer resolutions attained closer to the ground. Testing flight elevations between 30 and 120 m, Perroy et al [46] concluded that data acquired at 30 m, resulting in a pixel resolution of 14 mm, in their case, was best to detect tree stands in a tropical forest. Although elevation parameters have not been tested in open environments, which intrinsically have less overlap among vegetation (and therefore higher detectability than similar species in closed forests), similar resolution (<14 mm) may allow the identification of vegetation species smaller than a tree stand, while coarser resolutions should be adequate to detect open forest tree stands.…”

Section: Recommendationsmentioning

confidence: 99%

See 3 more Smart Citations

Identifying Species and Monitoring Understorey from UAS-Derived Data: A Literature Review and Future Directions

Hernández-Santín

Rudge

Bartolo³

et al. 2019

Drones

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Understorey vegetation plays an important role in many ecosystems, yet identifying and monitoring understorey vegetation through remote sensing has proved a challenge for researchers and land managers because understorey plants tend to be small, spatially and spectrally similar, and are often blocked by the overstorey. The emergence of Unmanned Aerial Systems (UAS) is revolutionising how vegetation is measured, and may allow us to measure understorey species where traditional remote sensing previously could not. The goal of this paper was to review current literature and assess the current capability of UAS to identify and monitor understorey vegetation. From the literature, we focused on the technical attributes that limit the ability to monitor understorey vegetation—specifically (1) spatial resolution, (2) spectral sensitivity, (3) spatial extent, and (4) temporal frequency at which a sensor acquires data. We found that UAS have provided improved levels of spatial resolution, with authors reporting successful classifications of understorey vegetation at resolutions of between 3 mm and 200 mm. Species discrimination can be achieved by targeting flights to correspond with phenological events to allow the detection of species-specific differences. We provide recommendations as to how UAS attributes can be tailored to help identify and monitor understorey species.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Recommendationsmentioning

confidence: 99%

Section: Recommendationsmentioning

confidence: 99%

See 2 more Smart Citations

Identifying Species and Monitoring Understorey from UAS-Derived Data: A Literature Review and Future Directions

Hernández-Santín

Rudge

Bartolo³

et al. 2019

Drones

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show abstract

“…In order to carry out operations beyond visual line of sight (BVLOS), the more advanced 102 certification can be granted by New Zealand's CAA if an operator can manage the high level of safety and risk (Perlman, 2017). New technology such as UTMs (UAV Traffic Management Systems) and the ADS-B (Automatic Dependent Surveillance Broadcast) systems are being developed to provide pilots with information on the altitude, velocity and position of any manned aircraft in the area (Kopardekar 2014;Knight 2016;Patterson 2017).…”

Section: Challenges To Using Uav For Precision Pest Controlmentioning

confidence: 99%

The potential of using Unmanned Aerial Vehicles (UAVs) for precision pest control of possums (Trichosurus vulpecula)

Morley¹,

Braodley²,

Hartley³

et al. 2017

ReEco

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Unmanned Aerial Vehicles (UAVs) and remote image sensing cameras have considerable potential for use in pest control operations. UAVs equipped with remote sensing cameras could be flown over forests and remnant bush sites, particularly those not currently receiving any pest control, to record the unique spectral signature of the vegetation and to detect the presence of possums (Trichosurus vulpecula) and the damage they cause. UAVs could then be deployed to precisely distribute either toxins or kill traps to these identified locations. Predator-free 2050 is an ambitious policy announced by the New Zealand Government where several pests, including possums, are to be eradicated by the year 2050. In order to achieve this goal, pests must be identified, targeted and controlled, requiring creative and novel ideas. UAVs provide flexibility, can fly in remote and difficult terrain, and are considerably cheaper to purchase and operate than the planes and helicopters currently used in conventional aerial pest control operations. Current challenges associated with UAVs include payload capacity, battery limitations, weather, and flying restrictions. However, these issues are rapidly being resolved with sophisticated technological advances and improved regulations. A directed and targeted approach using UAVs is an additional and novel tool in the pest management toolbox that could significantly reduce pest control costs, cover inaccessible areas not receiving any pest management, and will help New Zealand advance towards its predator-free aspiration by 2050.

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Influence of altitude on tropical marine habitat classification using imagery from fixed‐wing, water‐landing UAVs

Ellis

Taylor

Schiele

et al. 2020

Remote Sens Ecol Conserv

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Unmanned aerial vehicles (UAVs) are cost-effective remote sensing tools useful for generating very high-resolution (VHR) aerial imagery. Habitat maps generated from UAV imagery are a fundamental component of marine spatial planning, essential for the designation and governance of marine protected areas (MPAs). We investigated whether UAV survey altitude affects habitat classification performance and the classification accuracy of thematic maps from a tropical shallow water environment. We conducted repeated UAV flights at 75, 85, and 110 m, using a fixed-wing UAV on the Turneffe Atoll, Belize. Flights were ground truthed with snorkel surveys. Images were mosaiced to form orthomosaics and transformed into thematic maps through semi-automatic object-based image analysis (OBIA). Three subset areas (4000 m 2 , 17 000 m 2 and 17 000 m 2) from two cayes on the atoll were selected to investigate the effect of survey altitude. A linear regression demonstrated that for every 1 m increase in survey altitude, there was a~1% decrease in the overall classification accuracy. A low survey altitude of 75 m produced a higher classification accuracy for thematic maps and increased the representation of mangrove, seagrass and sand. The variability in classified cover was driven by altitude, although the direction and extent of this relationship was specific to each class. For coral and sea, classified cover decreased with increased altitude. Mangrove classified cover was non-sensitive to altitude changes, demonstrating a lesser need for a consistent survey altitude. Sand and seagrass had a greater sensitivity to altitude, due to classified cover variability between altitudes. Our findings suggest that survey altitude should be minimized when classifying tropical marine environments (coral, seagrass) and, given that most fixed-wing UAVs are restricted to a minimum altitude of 70 m, we recommend an altitude of 75 m. Survey altitude should be a major consideration when targeting habitats with greater sensitivity to altitude variability.

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Assessing the impacts of canopy openness and flight parameters on detecting a sub-canopy tropical invasive plant using a small unmanned aerial system

Cited by 47 publications

References 48 publications

Identifying Species and Monitoring Understorey from UAS-Derived Data: A Literature Review and Future Directions

Identifying Species and Monitoring Understorey from UAS-Derived Data: A Literature Review and Future Directions

The potential of using Unmanned Aerial Vehicles (UAVs) for precision pest control of possums (Trichosurus vulpecula)

Influence of altitude on tropical marine habitat classification using imagery from fixed‐wing, water‐landing UAVs

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