Citizen science unoccupied aerial vehicles: A technique for advancing coastal data acquisition for management and research

Ierodiaconou, Daniel; Kennedy, David M.; Pucino, Nicolas; Allan, Blake M.; McCarroll, Joshua A.; Ferns, Lawrance W.; Carvalho, Rafael Cabral; Sorrell, Karina J.; Leach, Chloe; Young, Mary

doi:10.1016/j.csr.2022.104800

Cited by 10 publications

(5 citation statements)

References 60 publications

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“…The challenge is to coordinate efforts, identify drivers of change and make all sources relevant for their context. RGB imagery consists of three bands (red, green and blue) and is often used for manual identification of features like land cover, organisms' presence and abundance, among others; it is a low-cost method commonly used mounted in UAV and has gained some track for its potential applications for citizen science and conservation (Ierodiaconou et al, 2022;Sauls et al, 2023). Multispectral and thermal imagery, spaceborne imagery like MODIS, Landsat, ASTER or Sentinel, among others; or at higher resolution from WorldView, Quickbird or SPOT (Anderson, 2018); collects data of between three and eleven spectral bands, allowing to capture more information on the spectral properties of the sensed landscape/objects.…”

Section: Remote Sensing Data and Biodiversity Indicatorsmentioning

confidence: 99%

Remote sensing biodiversity monitoring in Latin America: Emerging need for sustained local research and regional collaboration to achieve global goals

Garzon‐Lopez,

Miranda,

Moya

et al. 2024

Global Ecol Biogeogr

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AimBiodiversity monitoring at global scales has been identified as one of the priorities to halt biodiversity loss. In this context, Latin America and the Caribbean (LAC), home to 60% of the global biodiversity, play an important role in the development of an integrative biodiversity monitoring platform. In this review, we explore to what extent LAC has advanced in the adoption of remote sensing for biodiversity monitoring and what are the gaps and opportunities to integrate local monitoring into global efforts to halt biodiversity loss.LocationLatin America and the Caribbean.Time period1995 to 2022.Taxa studiedTerrestrial organisms.MethodsWe reviewed the application of remote sensing for biodiversity monitoring in LAC aiming to identify gaps and opportunities across countries, ecosystem types and research networks.ResultsOur analysis illustrates how the use of remote sensing in LAC is disproportionately low in relation to the biodiversity it supports.Main conclusionsBuild upon this analysis, we present, discuss and offer perspectives regarding four gaps identified in the application of remote sensing for biodiversity monitoring in Latin America and the Caribbean, namely (1) alignment between remote sensing data resolution and ecosystem structure; (2) investment in research, institutions and capacity building within researchers and stakeholders; (3) decolonized practices that promote access to publishing outlets and pluralistic participation among countries that facilitate exchange of experiences and capacity building; and (4) development of networks within and across regions to advance in ground surveys, ensure access and to foster the use of remote sensing data.

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Section: Remote Sensing Data and Biodiversity Indicatorsmentioning

confidence: 99%

Remote sensing biodiversity monitoring in Latin America: Emerging need for sustained local research and regional collaboration to achieve global goals

Garzon‐Lopez,

Miranda,

Moya

et al. 2024

Global Ecol Biogeogr

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“…The cliff rises 30 -50 m in height from the intertidal zone. It is fronted by a lowgradient, dissipative intertidal sandy beach up to 90 m wide at low tide but the cliff toe experiences wave actions during high tide (Ierodiaconou et al, 2022). Tides are semidiurnal and microtidal.…”

Section: Site Descriptionmentioning

confidence: 99%

“…Data collection was undertaken using DJI Phantom P4 and RTK models, as per Ierodiaconou et al (2022) and Pucino et al (2021). Point clouds derived from the drone imagery were georeferenced with an average total error of 40 mm and had an average ground sampling distance of 23 mm.…”

Section: Point Cloud Workflowmentioning

confidence: 99%

“…Of these methods, the LiDAR-based aerial and terrestrial laser scanning have dominated cliff erosion studies in the past decade (Letortu et al, 2018, Theodore et al, 2020, Young et al, 2009, Bezore et al, 2019, Katz and Mushkin, 2013, owing to their ability to produce 3D point clouds (hereafter denoted as "point clouds") that allow visualisation and analysis of landscapes in three dimensions. More recently, UAVs with the ability to collect Structure from Motion (SfM) photogrammetry have provided a cost-effective way to collect data with high spatial resolution and capability to produce point clouds (Mancini et al, 2017, Dewez Thomas et al, 2013, thereby allowing for the generation of extensive multi-temporal datasets (Ierodiaconou et al, 2022). Despite the truly three-dimensional nature of point cloud datasets, it is more common for geomorphic analysis to be performed using digital elevation models (DEM) that are a derived product from the point cloud.…”

Section: Introductionmentioning

confidence: 99%

“…This study aims to develop a methodology for the analysis of large datasets of near vertical coastal cliffs. It utilised a unique citizen-scientist UAV dataset (Ierodiaconou et al, 2022) collected bimonthly over four years along > 1.5 km of coast to test the ability of point clouds to detect meaningful change in coastal cliffs along a high-energy opencoast.…”

Section: Introductionmentioning

confidence: 99%

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Using UAV-Derived Point Clouds to measure high resolution cliff dynamics in soft lithologies: Demons Bluff, Victoria, Australia

Doran,

Kennedy,

McCarroll

et al. 2024

Preprint

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Abstract. Unoccupied aerial vehicles (UAVs) have revolutionised data collection on the Earth’s surface. Through aerial photogrammetry, very high-resolution digital surface models can be produced enabling contemporary research on landscape stability. There are however significant limitations in the imaging of vertical and overhanging landforms when using aerial platforms for data collection. Rather than reconstructing change from a digital surface model, direct analysis of generated point clouds is likely the key for understanding landform change in these morphologically complex environments. In this study, UAV’s were used to collect aerial imagery generating a high spatio-temporal resolution timeseries comprising of thirty point cloud datasets spanning four years for the steeply sloped Demons Bluff cliff located on the Great Ocean Road, Victoria, Australia. A method was developed to analyse the large quantity of 3D point cloud datasets. It was then possible to capture changes in cliff face morphology, enabling us to enhance our understanding of the erosional processes in coastal cliff environments. Over the study, the retreat rate for the upper half of the cliff face was 0.67 m/year (0.60 m3/m/yr). Cliff erosion was found to be dominated by 9 high magnitude, cliff-top collapses that exceeded 1,000 m3 (up to 9,500 m3) and terminated mid-way down the cliff. Below this point, several slab detachments were observed. Pre-collapse deformation was detected before collapses > 300 m3 with success (75 % of the time) in areas with a complete timeseries over the four-year period. Deformation was observed to occur in two ways, and both were observed to be eventuate in high magnitude (> 1,000 m3) collapse. The first which occurred prior to most high magnitude collapses (> 500 m3) was caused by the expansion of tension cracks behind the cliff-top, and the second which was characterised by smaller collapse volumes (> 100–500 m3) was initiated by rock slabs fracturing and cleaving away from the cliff face and was proceeded by high magnitude failure (< 1000 m3). An additional 14 instances of lean have been identified that are yet to result in collapse and should continue to be monitored to assess the success of this method with the forecasting of future collapse locations. Ultimately, this provides the ability to identify potential locations for future collapses which could aid in the development of an early warning system for cliff collapse to improve the management of volatile cliff environments that pose threats to infrastructure and public safety.

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SandSnap: Measuring and mapping beach grain size using crowd-sourced smartphone images

McFall,

Young,

Whitmeyer

et al. 2024

Coastal Engineering

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Citizen science unoccupied aerial vehicles: A technique for advancing coastal data acquisition for management and research

Cited by 10 publications

References 60 publications

Remote sensing biodiversity monitoring in Latin America: Emerging need for sustained local research and regional collaboration to achieve global goals

Remote sensing biodiversity monitoring in Latin America: Emerging need for sustained local research and regional collaboration to achieve global goals

Using UAV-Derived Point Clouds to measure high resolution cliff dynamics in soft lithologies: Demons Bluff, Victoria, Australia

SandSnap: Measuring and mapping beach grain size using crowd-sourced smartphone images

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