Saving species, time and money: Application of unmanned aerial vehicles (UAVs) for monitoring of an endangered alpine river specialist in a small nature reserve

Woellner, Romy; Wagner, Thomas C.

doi:10.1016/j.biocon.2019.02.037

Cited by 42 publications

(23 citation statements)

References 54 publications

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“…For example, the lakes and forest land monitored using the sky-based tool were of higher preference than when they were monitored using the space-based tool and ground-based tool. The result is in line with other research that has used UAVs to monitor the landscape changes of water bodies [39,40] and woodlands [41,42] and has achieved good monitoring results.…”

Section: Discussionsupporting

confidence: 89%

Suitability Assessment of the Tools Under a Three-Dimension System of Landscape Monitoring: A Case Study in the NWHS of Bogda

Yang

2020

Sustainability

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Landscapes provide significant ecosystem service value in Natural World Heritage Sites (NWHSs) and are required to be preserved by regular monitoring and evaluation. It is vital to choose appropriate monitoring tools according to local conditions to guarantee the process is effective and efficient. This study aims to find out the spatial suitability of monitoring tools under a three-dimension system of space-based monitoring, sky-based monitoring, and ground-based monitoring. A suitability assessment was conducted from three aspects—the monitoring environment, object, and effect—from which typical differences existed among the three types of tools. Nine indicators were finalized, in which eight were classified and scored using the Delphi method with objectivity, and the remaining indicator was processed subjectively by quantifying the different monitoring effects on different landscape units by each of the tools. The method was verified using a case study in Bogda of Xinjiang Tianshan through overlay analysis in ArcGIS. The results showed an apparently stepped distribution characteristic related to altitude, where space-based monitoring zones are located in regions of high altitude, and the landscapes in low-altitude regions had the best monitoring effects using the ground-based tool and sky-based tool. Combined with the distribution characteristics of the 3-level protected zones, the results show a consistency with reality and could help planners to strategically deploy monitoring sites and allocate them advisable monitoring facilities and staffing.

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Section: Discussionsupporting

confidence: 89%

Suitability Assessment of the Tools Under a Three-Dimension System of Landscape Monitoring: A Case Study in the NWHS of Bogda

Yang

2020

Sustainability

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“…Comparing overall model accuracy, combining two classes (binary), all bands and the SVM classifier had high accuracy, followed closely by the model developed using binary classes, SFFS for feature selection, and SVM or RF classifiers ( Figure 7). Our results agree with Burai et al 2015 [56], a study performed on the vegetation of similar characteristics (herbaceous), where, using all the bands, SVN performed slightly better than RF, but the differences were not significant [50]. Additionally, they found that the number of pixels affected the classification accuracy, which was similar to our results at the species level (P. goudotiana, 15,724 pixels, Supp.…”

Section: Automated Species Identification Using Hyperspectral Datasupporting

confidence: 92%

“…Our study has shown that hyperspectral data effectively differentiated five important páramo species, two of them of the same genus and endemic from this ecosystem, following other studies in temperate alpine ecosystems [49,50]. Comparing overall model accuracy, combining two classes (binary), all bands and the SVM classifier had high accuracy, followed closely by the model developed using binary classes, SFFS for feature selection, and SVM or RF classifiers ( Figure 7).…”

Section: Automated Species Identification Using Hyperspectral Datasupporting

confidence: 75%

“…It only required a couple of hours of clear sky to obtain 1cm pixel-resolution used in this study. Previous research has highlighted the importance of this type of imagery in different types of ecosystems from big trees in highly diverse tropical [46,47] and subtropical forests [48], to small stature species in temperate grasslands [49], in a diverse set of ecological studies that include mapping, restoration and monitoring [50][51][52]. In this study, we conclude that high-resolution imagery (1 cm pixel) has great potential for at least 21% of the species, comprising a range of growth forms from big rosettes (P. goudotiana), endemic species (Espeletia sp.)…”

Section: Manual Species Identification Using Rgb Imagerymentioning

confidence: 99%

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Species Classification in a Tropical Alpine Ecosystem Using UAV-Borne RGB and Hyperspectral Imagery

Garzón‐López

Lasso

2020

Drones

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Páramos host more than 3500 vascular plant species and are crucial water providers for millions of people in the northern Andes. Monitoring species distribution at large scales is an urgent conservation priority in the face of ongoing climatic changes and increasing anthropogenic pressure on this ecosystem. For the first time in this ecosystem, we explored the potential of unoccupied aerial vehicles (UAV)-borne red, green, and blue wavelengths (RGB) and hyperspectral imagery for páramo species classification by collecting both types of images in a 10-ha area, and ground vegetation cover data from 10 plots within this area. Five plots were used for calibration and the other five for validation. With the hyperspectral data, we tested our capacity to detect five representative páramo species with different growth forms using support vector machine (SVM) and random forest (RF) classifiers in combination with three feature selection methods and two class groups. Using RGB images, we could classify 21 species with an accuracy greater than 97%. From hyperspectral imaging, the highest accuracy (89%) was found using models built with RF or SVM classifiers combined with a binary grouping method and the sequential floating forward selection feature. Our results demonstrate that páramo species can be accurately mapped using both RGB and hyperspectral imagery.

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“…In the last 20 years Unmanned Aerial Vehicles (UAVs), commonly referred to as drones, have been successfully applied to monitor plant communities for ecological research and for conservation and applicative purposes, but their use regards only horizontal plant communities [29][30][31][32][33][34][35]. On the other hand, for many years, UAVs and digital photogrammetry software have been successfully applied to assess and monitor geological risk in steep slope rocky cliffs [36][37][38][39][40].…”

Section: Introductionmentioning

confidence: 99%

Monitoring of Plant Species and Communities on Coastal Cliffs: Is the Use of Unmanned Aerial Vehicles Suitable?

et al. 2020

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Cliffs are reservoirs of biodiversity; therefore, many plant species and communities of inland and coastal cliffs are protected by Council Directive 92/43/EEC (European Economic Community), and their monitoring is mandatory in European Union countries. Surveying plants on coastal cliff by traditional methods is challenging and alternatives are needed. We tested the use of a small Unmanned Aerial Vehicle (UAV) as an alternative survey tool, gathering aerial images of cliffs at Palinuro Cape (Southern Italy). Four photo-interpreters analysed independently the derived orthomosaic and plotted data needed for the monitoring activity. Data showed to be not affected by photo-interpreters and reliable for the prescribed monitoring in the European Union (EU). Using the GIS analysis tools, we were able to: (a) recognise and map the plant species, (b) derive and measure the area of distribution on the cliff of habitat and species, and (c) count Eokochia saxicola individuals and gather quantitative data on their projected area. Quality of the images represented the main constraint, but incoming technological improvements of sensors and UAVs may overcome this problem. Overall results support the use of UAVs as an affordable and fast survey technique that can rapidly increase the number of studies on cliff habitats and improve ecological knowledge on their plant species and communities.

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Saving species, time and money: Application of unmanned aerial vehicles (UAVs) for monitoring of an endangered alpine river specialist in a small nature reserve

Cited by 42 publications

References 54 publications

Suitability Assessment of the Tools Under a Three-Dimension System of Landscape Monitoring: A Case Study in the NWHS of Bogda

Suitability Assessment of the Tools Under a Three-Dimension System of Landscape Monitoring: A Case Study in the NWHS of Bogda

Species Classification in a Tropical Alpine Ecosystem Using UAV-Borne RGB and Hyperspectral Imagery

Monitoring of Plant Species and Communities on Coastal Cliffs: Is the Use of Unmanned Aerial Vehicles Suitable?

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