Unmanned aerial vehicle methods makes species composition monitoring easier in grasslands

Sun, Yi; Yi, Shuai; Hou, Fujiang

doi:10.1016/j.ecolind.2018.08.042

Cited by 37 publications

(56 citation statements)

References 24 publications

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“…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: 76%

“…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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Section: Automated Species Identification Using Hyperspectral Datasupporting

confidence: 76%

Section: Manual Species Identification Using Rgb Imagerymentioning

confidence: 99%

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

Garzón‐López

Lasso

2020

Drones

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“…There are apparently few studies carried out with the goal of identifying or quantifying native herbaceous species from drone imagery [12,[23][24][25][26][27]. These studies were implemented at a range of spatial and spectral resolutions with varying degrees of sophistication and mixed results.…”

Section: Introductionmentioning

confidence: 99%

Application of UAV-Based Methodology for Census of an Endangered Plant Species in a Fragile Habitat

Rominger

Meyer

2019

Remote Sensing

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Accurate census is essential for endangered plant management, yet lack of resources may make complete on-the-ground census difficult to achieve. Accessibility, especially for species in fragile habitats, is an added constraint. We examined the feasibility of using UAV (unmanned aerial vehicle, drone)-based imagery for census of an endangered plant species, Arctomecon humilis (dwarf bear-poppy), an herbaceous perennial gypsophile endemic of the Mojave Desert, USA. Using UAV technology, we captured imagery at both 50-m altitude (census) and 15-m altitude (validation) at two populations, White Dome (325 ha) and Red Bluffs (166 ha). The imagery was processed into orthomosaics that averaged 2.32 cm ground sampling distance (GSD) for 50-m imagery and 0.73 cm GSD for 15-m imagery. Putative poppy plants were marked in the 50-m imagery according to predefined criteria. We then used the 15-m imagery from each area to verify the identification accuracy of marked plants. Visual evaluation of the 50-m imagery resulted in errors of both commission and omission, mainly caused by failure to accurately identify or detect small poppies (<10 cm diameter). Higher-resolution 30-m altitude imagery (1.19 cm GSD) greatly reduced errors of commission. Habitat classification demonstrated that poppy density variation was closely tied to soil surface color. This study showed that drone imagery can potentially be used to census rare plant species with distinctive morphology in open habitats and understand their spatial distribution.

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“…Recently, lightweight unmanned aerial vehicles (UAVs) with low-cost and high resolution [30] have gradually been applied to monitor vegetation species composition [31][32][33][34] and investigate pika density at plot scale [35]. Nevertheless, existing studies regarding the vegetation composition monitoring mainly focused on one ecosystem at a single site [36,37] or the dominant species [38,39]. Our knowledge of vegetation species composition in multiple ecosystems is still insufficient, especially in the alpine region.…”

Section: Introductionmentioning

confidence: 99%

“…The UAV, together with automatic flight control system (e.g., Fragmentation Monitoring and Analysis with aerial Photography) could be a potential solution. On the one hand, it has been proved that it is feasible to identify and monitor species composition and pika burrows using UAVs [35,37]. On the other hand, the UAV-based method is cost-efficient and has high frequency as it is a non-destructive and fixed points monitoring method, which is suitable for monitoring objects (e.g., species composition and pika burrow) in the real-world ecosystems.…”

Section: Introductionmentioning

confidence: 99%

Species Monitoring Using Unmanned Aerial Vehicle to Reveal the Ecological Role of Plateau Pika in Maintaining Vegetation Diversity on the Northeastern Qinghai-Tibetan Plateau

et al. 2020

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Plateau pika (Ochotona curzoniae, hereafter pika) is considered to exert a profound impact on vegetation species diversity of alpine grasslands. Great efforts have been made at mound or quadrat scales; nevertheless, there is still controversy about the effect of pika. It is vital to monitor vegetation species composition in natural heterogeneous ecosystems at a large scale to accurately evaluate the real role of pika. In this study, we performed field survey at 55 alpine grassland sites across the Shule River Basin using combined methods of aerial photographing using an unmanned aerial vehicle (UAV) and traditional ground measurement. Based on our UAV operation system, Fragmentation Monitoring and Analysis with aerial Photography (FragMAP), aerial images were acquired. Plot-scale vegetation species were visually identified, and total pika burrow exits were automatically retrieved using the self-developed image processing software. We found that there were significant linear relationships between the vegetation species diversity indexes obtained by these two methods. Additionally, the total number of identified species by the UAV method was 71, which was higher than the Quadrat method recognition, with the quantity of 63. Our results indicate that the UAV was suitable for long-term repeated monitoring vegetation species composition of multiple alpine grasslands at plot scale. With the merits of UAV, it confirmed that pika’s disturbance belonged to the medium level, with the density ranging from 30.17 to 65.53 ha−1. Under this density level, pika had a positive effect on vegetation species diversity, particularly for the species richness of sedge and forb. These findings conclude that the UAV was an efficient and economic tool for species monitoring to reveal the role of pika in the alpine grasslands.

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Unmanned aerial vehicle methods makes species composition monitoring easier in grasslands

Cited by 37 publications

References 24 publications

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

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

Application of UAV-Based Methodology for Census of an Endangered Plant Species in a Fragile Habitat

Species Monitoring Using Unmanned Aerial Vehicle to Reveal the Ecological Role of Plateau Pika in Maintaining Vegetation Diversity on the Northeastern Qinghai-Tibetan Plateau

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