scholarly journals Citizen-Science with off-the-shelf UAV for Coastal Monitoring

2021 ◽  
Vol 930 (1) ◽  
pp. 012001
Author(s):  
S M Beselly ◽  
M A Sajali
Keyword(s):  
Citizen Science ◽  
Structure From Motion ◽  
Coastal Management ◽  
Low Cost ◽  
Coastal Monitoring ◽  
Shoreline Position ◽  
The Public ◽  
Promising Tool ◽  
Aerial Vehicle

Abstract Accurate and repetitive observation and quantification of the shoreline position and the coastal feature are essential aspects of coastal management and planning. Commonly, the dataset associated with coastal observation and quantification is obtained with in-situ coastal surveys. The current methods are mostly quite expensive, time-consuming, and require trained individuals to do the task. With the availability of the off-the-shelf low cost, lightweight, and reliable Unmanned Aerial Vehicle (UAV) with the advances of the algorithms such as structure-from-motion (SfM), UAV-based measurement becomes a promising tool. Open SfM initiative, open topographical database, and UAV communities are the enablers that make it possible to collect accurate and frequent coastal monitoring and democratize data. This paper provides a review and discussions that highlight the possibility of conducting scientific coastal monitoring or collaborating with the public. Literature was examined for the advances in coastal monitoring, challenges, and recommendations. We identified and proposed the use of UAV along with the strategies and systems to encourage citizen-led UAV observation for coastal monitoring while attaining the quality.

scholarly journals Monitoring snow depth change across a range of landscapes with ephemeral snowpacks using structure from motion applied to lightweight unmanned aerial vehicle videos

2018 ◽  
Vol 12 (11) ◽  
pp. 3535-3550 ◽  
Author(s):  
Richard Fernandes ◽  
Christian Prevost ◽  
Francis Canisius ◽  
Sylvain G. Leblanc ◽  
Matt Maloley ◽  
...  
Keyword(s):  
Free Surface ◽  
Unmanned Aerial Vehicle ◽  
Structure From Motion ◽  
Snow Depth ◽  
Low Cost ◽  
Horizontal Resolution ◽  
Absolute Difference ◽  
Flat Surfaces ◽  
Aerial Vehicle

Abstract. Differencing of digital surface models derived from structure from motion (SfM) processing of airborne imagery has been used to produce snow depth (SD) maps with between ∼2 and ∼15 cm horizontal resolution and accuracies of ±10 cm over relatively flat surfaces with little or no vegetation and over alpine regions. This study builds on these findings by testing two hypotheses across a broader range of conditions: (i) that the vertical accuracy of SfM processing of imagery acquired by commercial low-cost unmanned aerial vehicle (UAV) systems can be adequately modelled using conventional photogrammetric theory and (ii) that SD change can be more accurately estimated by differencing snow-covered elevation surfaces rather than differencing a snow-covered and snow-free surface. A total of 71 UAV missions were flown over five sites, ranging from short grass to a regenerating forest, with ephemeral snowpacks. Point cloud geolocation performance agreed with photogrammetric theory that predicts uncertainty is proportional to UAV altitude and linearly related to horizontal uncertainty. The root-mean-square difference (RMSD) over the observation period, in comparison to the average of in situ measurements along ∼50 m transects, ranged from 1.58 to 10.56 cm for weekly SD and from 2.54 to 8.68 cm for weekly SD change. RMSD was not related to microtopography as quantified by the snow-free surface roughness. SD change uncertainty was unrelated to vegetation cover but was dominated by outliers corresponding to rapid in situ melt or onset; the median absolute difference of SD change ranged from 0.65 to 2.71 cm. These results indicate that the accuracy of UAV-based estimates of weekly snow depth change was, excepting conditions with deep fresh snow, substantially better than for snow depth and was comparable to in situ methods.

scholarly journals A new rapid, low-cost and GPS-centric unmanned aerial vehicle incorporating in-situ multispectral oil palm trees health detection.

2018 ◽  
Vol 02 (04) ◽  
Author(s):  
Bryan D. See ◽  
Shaiful J. Hashim ◽  
Helmi Z. M. Shafri ◽  
Syaril Azrad ◽  
Mohd. Roshdi Hassan
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Oil Palm ◽  
Low Cost ◽  
Palm Trees ◽  
Aerial Vehicle

scholarly journals Citizen Science for Marine Litter Detection and Classification on Unmanned Aerial Vehicle Images

Water ◽  
2021 ◽  
Vol 13 (23) ◽  
pp. 3349
Author(s):  
Silvia Merlino ◽  
Marco Paterni ◽  
Marina Locritani ◽  
Umberto Andriolo ◽  
Gil Gonçalves ◽  
...  
Keyword(s):  
Citizen Science ◽  
Remote Detection ◽  
Visual Census ◽  
Marine Litter ◽  
Training Plan ◽  
Aerial Vehicle ◽  
Manual Processing ◽  
Item Properties ◽  
Uav Images

Unmanned aerial vehicles (UAV, aka drones) are being used for mapping macro-litter in the environment. As drone images require a manual processing task for detecting marine litter, it is of interest to evaluate the accuracy of non-expert citizen science operators (CSO) in performing this task. Students from Italian secondary schools (in this work, the CSO) were invited to identify, mark, and classify stranded litter items on a UAV orthophoto collected on an Italian beach. A specific training program and working tools were developed for the aim. The comparison with the standard in situ visual census survey returned a general underestimation (50%) of items. However, marine litter bulk categorisation was fairly in agreement with the in situ survey, especially for sources classification. The concordance level among CSO ranged between 60% and 91%, depending on the item properties considered (type, material, and colour). As the assessment accuracy was in line with previous works developed by experts, remote detection of marine litter on UAV images can be improved through citizen science programs, upon an appropriate training plan and provision of specific tools.

scholarly journals Anthropogenic Sources of Non-Migratory Avian Mortalities In Singapore

2018 ◽  
Vol 2 (2) ◽  
pp. 17-27
Author(s):  
David J. X. TAN ◽  
Ding Li YONG ◽  
Bing Wen LOW ◽  
Alan OWYONG ◽  
Alfred CHIA
Keyword(s):  
Citizen Science ◽  
Low Cost ◽  
Bird Species ◽  
Cost Effective ◽  
Forest Edge ◽  
Urban Spaces ◽  
Anthropogenic Sources ◽  
Ecological Data ◽  
The Public ◽  
Survey Methodologies

Although urban spaces are increasingly recognised as viable habitats for wildlife, cities remain a major source of anthropogenic mortality for wild birds. While the sources of urban avian mortalities have been well documented in North America, these phenomena remain poorly studied in Southeast Asia, especially for resident species. Here we present the first summary of non-migratory urban bird mortalities for the heavily urbanised island of Singapore. We conducted a citizen science study using print and social media outreach to encourage members of the public to report their observations of dead birds between November 2013 and October 2017, and collected a total of 362 mortality records across 65 resident bird species and five mortality sources. Our results show that a diverse array of bird species is directly impacted by anthropogenic sources of mortality, although mortalities stemming from roadkill and cat predation are likely to be undersampled. We also find that forest-edge frugivores such as the Pink-necked Green Pigeon are likely to be especially vulnerable to building collisions. Our study shows that despite its limitations, opportunistic sampling using citizen science can generate large amounts of ecological data at relatively low cost, and serve as a cost-effective complement to standardised survey methodologies.

scholarly journals Seamless integration of above- and under-canopy unmanned aerial vehicle laser scanning for forest investigation

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Yunsheng Wang ◽  
Antero Kukko ◽  
Eric Hyyppä ◽  
Teemu Hakala ◽  
Jiri Pyörälä ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Laser Scanning ◽  
High Efficiency ◽  
Low Cost ◽  
Seamless Integration ◽  
Aerial Vehicle ◽  
Individual Trees ◽  
Mobile Mapping Systems ◽  
Aerial Perspective

Abstract Background Current automated forest investigation is facing a dilemma over how to achieve high tree- and plot-level completeness while maintaining a high cost and labor efficiency. This study tackles the challenge by exploring a new concept that enables an efficient fusion of aerial and terrestrial perspectives for digitizing and characterizing individual trees in forests through an Unmanned Aerial Vehicle (UAV) that flies above and under canopies in a single operation. The advantage of such concept is that the aerial perspective from the above-canopy UAV and the terrestrial perspective from the under-canopy UAV can be seamlessly integrated in one flight, thus grants the access to simultaneous high completeness, high efficiency, and low cost. Results In the experiment, an approximately 0.5 ha forest was covered in ca. 10 min from takeoff to landing. The GNSS-IMU based positioning supports a geometric accuracy of the produced point cloud that is equivalent to that of the mobile mapping systems, which leads to a 2–4 cm RMSE of the diameter at the breast height estimates, and a 4–7 cm RMSE of the stem curve estimates. Conclusions Results of the experiment suggested that the integrated flight is capable of combining the high completeness of upper canopies from the above-canopy perspective and the high completeness of stems from the terrestrial perspective. Thus, it is a solution to combine the advantages of the terrestrial static, the mobile, and the above-canopy UAV observations, which is a promising step forward to achieve a fully autonomous in situ forest inventory. Future studies should be aimed to further improve the platform positioning, and to automatize the UAV operation.

scholarly journals Rapid quantification of cryoconite: granule geometry and in situ supraglacial extents, using examples from Svalbard and Greenland

2010 ◽  
Vol 56 (196) ◽  
pp. 297-308 ◽  
Author(s):  
Tristram D.L. Irvine-Fynn ◽  
Jonathan W. Bridge ◽  
Andrew J. Hodson
Keyword(s):  
Spatial Scales ◽  
Low Cost ◽  
Image Data ◽  
Major Axis ◽  
Primary Data ◽  
Digital Cameras ◽  
The Public ◽  
Automated Processing ◽  
Public Domain Software

AbstractSupraglacial dust (cryoconite) is an important but poorly understood component of the glacial system. There is a lack of primary data on cryoconite form, extent and dynamics. Here we present a suite of rapid, low-cost methodologies for quantification of granule geometry and supraglacial cryoconite coverage using image data captured by commercially available digital cameras. We develop robust, transferable protocols for analysis of (1) cryoconite granule geometry (major axis, Feret diameter, circularity); (2) centimetre–metre scale supraglacial extent (m2cryoconite m−2surface); and (3) temporal change in supraglacial extent at hourly intervals over several days. Image-processing methodologies were developed using the public domain software ImageJ. Manual (supervised) controls were used to estimate sources of error, and measurements then automated using simple scripting tools (macros). Fully automated processing successfully identified ∼90% of a sample of isolated granules ranging between 2.5 and 39.2 mm, with uncertainties of <20%. Particle sphericity (inferred from circularity) decreased as particle size increased. Supraglacial cryoconite extent was obtained with a mean uncertainty of 37% and 22% for data from field sites in Greenland and Svalbard, respectively. These methods will facilitate acquisition and analysis of datasets for cryoconite across a range of spatial scales, supporting research into cryoconite impacts on supraglacial hydrological connections, nutrient and carbon cycling, and initiation of primary succession in deglaciating environments.

scholarly journals Image-based surface reconstruction in geomorphometry – merits, limits and developments of a promising tool for geoscientists

2015 ◽  
Vol 3 (4) ◽  
pp. 1445-1508 ◽  
Author(s):  
A. Eltner ◽  
A. Kaiser ◽  
C. Castillo ◽  
G. Rock ◽  
F. Neugirg ◽  
...  
Keyword(s):  
Structure From Motion ◽  
High Performance ◽  
Scientific Practice ◽  
Low Cost ◽  
Image Data ◽  
Ground Truth ◽  
Scale Invariant ◽  
High Quality ◽  
Promising Tool ◽  
Wide Range

Abstract. Photogrammetry and geosciences are closely linked since the late 19th century. Today, a wide range of commercial and open-source software enable non-experts users to obtain high-quality 3-D datasets of the environment, which was formerly reserved to remote sensing experts, geodesists or owners of cost-intensive metric airborne imaging systems. Complex tridimensional geomorphological features can be easily reconstructed from images captured with consumer grade cameras. Furthermore, rapid developments in UAV technology allow for high quality aerial surveying and orthophotography generation at a relatively low-cost. The increasing computing capacities during the last decade, together with the development of high-performance digital sensors and the important software innovations developed by other fields of research (e.g. computer vision and visual perception) has extended the rigorous processing of stereoscopic image data to a 3-D point cloud generation from a series of non-calibrated images. Structure from motion methods offer algorithms, e.g. robust feature detectors like the scale-invariant feature transform for 2-D imagery, which allow for efficient and automatic orientation of large image sets without further data acquisition information. Nevertheless, the importance of carrying out correct fieldwork strategies, using proper camera settings, ground control points and ground truth for understanding the different sources of errors still need to be adapted in the common scientific practice. This review manuscript intends not only to summarize the present state of published research on structure-from-motion photogrammetry applications in geomorphometry, but also to give an overview of terms and fields of application, to quantify already achieved accuracies and used scales using different strategies, to evaluate possible stagnations of current developments and to identify key future challenges. It is our belief that the identification of common errors, "bad practices" and some other valuable information in already published articles, scientific reports and book chapters may help in guiding the future use of SfM photogrammetry in geosciences.

scholarly journals Thermal Remote Sensing from UAVs: A Review on Methods in Coastal Cliffs Prone to Landslides

2020 ◽  
Vol 12 (12) ◽  
pp. 1971
Author(s):  
Maria Teresa Melis ◽  
Stefania Da Pelo ◽  
Ivan Erbì ◽  
Marco Loche ◽  
Giacomo Deiana ◽  
...  
Keyword(s):  
Structure From Motion ◽  
Quantitative Data ◽  
Methodological Approach ◽  
Mitigation Measures ◽  
Improve Accuracy ◽  
Coastal Cliffs ◽  
Aerial Vehicle ◽  
Coastal Retreat ◽  
Social And Environmental Impacts

Coastal retreat is a non-recoverable phenomenon that—together with a relevant proneness to landslides—has economic, social and environmental impacts. Quantitative data on geological and geomorphologic features of such areas can help to predict and quantify the phenomena and to propose mitigation measures to reduce their impact. Coastal areas are often inaccessible for sampling and in situ surveys, in particular where steeply sloping cliffs are present. Uses and capability of infrared thermography (IRT) were reviewed, highlighting its suitability in geological and landslides hazard applications. Thanks to the high resolution of the cameras on the market, unmanned aerial vehicle-based IRT allows to acquire large amounts of data from inaccessible steep cliffs. Coupled structure-from-motion photogrammetry and coregistration of data can improve accuracy of IRT data. According to the strengths recognized in the reviewed literature, a three-step methodological approach to produce IRTs was proposed.

Rapid mapping accuracy assessment using low-cost UAV and open-source Structure from Motion

2020 ◽  
Vol 52 ◽  
pp. 55-61
Author(s):  
Ettore Potente ◽  
Cosimo Cagnazzo ◽  
Alessandro Deodati ◽  
Giuseppe Mastronuzzi
Keyword(s):  
Open Source ◽  
Structure From Motion ◽  
Accuracy Assessment ◽  
Low Cost ◽  
Mapping Accuracy ◽  
Rapid Mapping ◽  
Source Structure

To Eliminate Curtain Effect of FIB TEM Samples by a Combination of Sample Dicing and Backside Milling

2014 ◽  
Author(s):  
Jian-Shing Luo ◽  
Hsiu Ting Lee
Keyword(s):  
Sample Preparation ◽  
Focused Ion Beam ◽  
Preparation Method ◽  
Low Cost ◽  
Ion Beam ◽  
Sample Preparation Method ◽  
Site Specific ◽  
Dual Beam ◽  
Transmission Electron

Abstract Several methods are used to invert samples 180 deg in a dual beam focused ion beam (FIB) system for backside milling by a specific in-situ lift out system or stages. However, most of those methods occupied too much time on FIB systems or requires a specific in-situ lift out system. This paper provides a novel transmission electron microscopy (TEM) sample preparation method to eliminate the curtain effect completely by a combination of backside milling and sample dicing with low cost and less FIB time. The procedures of the TEM pre-thinned sample preparation method using a combination of sample dicing and backside milling are described step by step. From the analysis results, the method has applied successfully to eliminate the curtain effect of dual beam FIB TEM samples for both random and site specific addresses.

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