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opencc-by-4.0Feb 2021View details →

Рис. 3. РаспреΑеΛение гнезΑ ΑаΛьневосточного аиста на воΑно-боΛотных угоΑьях оз. БоΛонь по материаΛам авиаучетов: 1999 г. — треугоΛьник (по: Δарман, АнΑронов, Хигучи и Αр. 2000); 2004 г. — звезΑочка; 2005 г. — кружок Fig. 3. Distribution of nests of the Oriental White Stork in the wetlands of Lake Bolon based on aerial surveys: 1999 — triangle (based on: Darman et al. 2000a); 2004 — asterisk; 2005 — circle in The number and distribution of the Oriental White Stork Ciconia boyciana Swinhoe, 1873 in the Khabarovskiy Region

Рис. 3. РаспреΑеΛение гнезΑ ΑаΛьневосточного аиста на воΑно-боΛотных угоΑьях оз. БоΛонь по материаΛам авиаучетов: 1999 г. — треугоΛьник (по: Δарман, АнΑронов, Хигучи и Αр. 2000); 2004 г. — звезΑочка; 2005 г. — кружок Fig. 3. Distribution of nests of the Oriental White Stork in the wetlands of Lake Bolon based on aerial surveys: 1999 — triangle (based on: Darman et al. 2000a); 2004 — asterisk; 2005 — circle

opencc-by-4.0Apr 2015View details →

Figure 1 in Quantitative assessment of species identification in aerial transect surveys for ice-associated seals

Figure 1. The characteristic bands on the coats of ribbon seals are not necessarily clearly visible in an aerial image. The images on the top right and bottom right were taken with a Canon 1Ds Mark III fitted with a Zeiss 100 mm lens from 300 m during a 2012 line transect survey in the Bering Sea. In the top right image, an observer would likely rely on the clearly visible bands to conclude that the seal is certainly a ribbon seal. In the bottom right image, an observer would likely rely on a combination of body shape, head size, flipper size and shape, and what could be one or more bands to conclude that the seal is probably a ribbon seal.

opencc-by-4.0Apr 2015View details →

Figure 3 in Quantitative assessment of species identification in aerial transect surveys for ice-associated seals

Figure 3. Observed species and age class identification probabilities for four species of iceassociated seals in the Bering Sea. True species and age classes include spotted seal pup (SDP), spotted seal nonpup (SDN), ribbon seal pup (RNP), ribbon seal nonpup (RNN), bearded seal pup (BDP), bearded seal nonpup (BDN), ringed seal pup (RDP), and ringed seal nonpup (RDN). Observed species classifications include spotted seal (red), ribbon seal (green), bearded seal (yellow), ringed seal (blue), and unknown seal (white). Observed age classes include pup, nonpup, and unknown. Solid colors with no hashing indicate unknown age classification. Top panel (a) includes results from an analysis with no observer effects on model parameters. Bottom four panels (b) correspond to four different observers from an analysis including observer effects.

opencc-by-4.0Apr 2015View details →

Figure 2. A in Quantitative assessment of species identification in aerial transect surveys for ice-associated seals

Figure 2. A red face, which is one of the characteristics associated mostly with bearded seals, is not always present, nor is it necessarily visible in an aerial image. The image on the right was taken with a Canon 1Ds Mark III fitted with a Zeiss 100 mm lens from 300 m during a 2012 line transect survey in the Bering Sea. In this image, an observer would likely rely on the combination of body shape, head size, front-flipper size and shape, and position on the floe to conclude that the seal is probably or certainly a bearded seal.

Figure 4 in A comparison of image and observer based aerial surveys of narwhal

Figure 4. Detection function plot of chosen DS model when sightings of both aerial observer pairs were pooled. Intercept obtained from the MR model. The solid black line indicates the probability detection function from the DS model and the open symbols indicate the probability of each detection given its perpendicular distance and other covariate values.

Figure 3. Detection functions for Observer pair 1 in A comparison of image and observer based aerial surveys of narwhal

Figure 3. Detection functions for Observer pair 1 (upper panel) and Observer pair 2 (lower panel) during aerial surveys in Melville Bay from 25 to 30 August 2014. Data are truncated at 1,300 m.

Figure 2 in A comparison of image and observer based aerial surveys of narwhal

Figure 2. Narwhal sighting locations in the Melville Bay survey area in 2014 recorded by aerial observers in real-time and identified by analysts in digital imagery. Most of "observer only" sightings are detections beyond the area covered by images (i.e., beyond 500 m from the trackline). The image of ice distribution was of 30 August 2014. We acknowledge the use of imagery from the NASA Worldview application (https://worldview.earthdata.nasa.gov/) operated by the NASA/Goddard Space Flight Center Earth Science Data and Information System (ESDIS) project.

Figure 1 in A comparison of image and observer based aerial surveys of narwhal

Figure 1. Survey strata and transects designed for the aerial survey in Melville Bay from 25 to 30 August 2014. Transects that were surveyed zero, two, or three times, are marked in blue, green or red, respectively. All black transects were surveyed once.

opencc-zeroNov 2022View details →

Using unoccupied aerial vehicles to estimate availability and group size error for aerial surveys of coastal dolphins

Aerial surveys are frequently used to estimate the abundance of marine mammals, but their accuracy is dependent upon obtaining a measure of the availability of animals for visual detection. Existing methods for characterizing availability have limitations and do not necessarily reflect true availability. Here, we present a method of using small, vessel‐launched, multi‐rotor Unoccupied Aerial Vehicles (UAVs or drones) to collect video of dolphins to characterize availability and investigate errors surrounding group size estimates. We collected over 20 h of aerial video of dive‐surfacing behaviour across 32 encounters with the Australian humpback dolphin Sousa sahulensis off north‐western Australia. Mean surfacing and dive periods were 7.85 sec (se = 0.26) and 39.27 sec (se = 1.31) respectively. Dolphin encounters were split into 56 focal follows of consistent group composition to which example approaches to estimating availability were applied. Non‐instantaneous availability estimates, assuming a 7-sec observation window, ranged between 0.22 and 0.88, with a mean availability of 0.46 (CV = 0.34). Availability tended to increase with increasing group size. We found a downward bias in group size estimation, with true group size typically one individual more than would have been estimated by a human observer during a standard aerial survey. The variability of availability estimates between focal follows highlights the importance of sampling across a variety of group sizes, compositions, and environmental conditions. Through data re‐sampling exercises, we explored the influence of sample size on availability estimates and their precision, with results providing an indication of target sample sizes to minimize bias in future research. We show that UAVs can provide an effective and relatively inexpensive method of characterizing dolphin availability with several advantages over existing approaches. The example estimates obtained for humpback dolphins are within the range of values obtained for other shallow‐water, small cetaceans, and will directly inform a government‐run program of aerial surveys in the region.

opencc-zeroApr 2023View details →

Large marine predator aerial survey data for Hauraki Gulf, New Zealand

Large marine predators, such as cetaceans and sharks, play a crucial role in maintaining biodiversity patterns and ecosystem health. Despite the recognised importance of these animals and their over-representation as threatened species, distribution data at appropriate temporal and spatial scales is often lacking or insufficient for effective conservation. Here, we present sightings of large marine megafauna recorded from a replicate systematic aerial survey undertaken in the Hauraki Gulf, Aotearoa New Zealand during a full year. Using flexible machine learning models (Boosted Regression Tree models), we use these sightings data to investigate relationships between large marine predator occurrence (Bryde's whales, common and bottlenose dolphins, bronze whalers, pelagic and immature hammerhead sharks) and spatially explicit environmental and biotic variables to predict species richness of large marine predators and investigate their fine-scale spatiotemporal distribution patterns. All models were considered informative (all, AUC > 0.78), and temporally dynamic variables, such as the distribution of prey, were important in predicting the occurrence of the study species and species groups. Our approach and data highlight the value of multi-species surveys and the importance of considering temporally variable abiotic and biotic drivers for understanding biodiversity patterns when informing ecosystem-scale conservation planning and dynamic ocean management. We provide data files of: <ul> <li>Locations of species presence / pseudo absence location over time (in .csv format) and associated environmental and biotic variables for Bryde's whales, common and bottlenose dolphins, bronze whaler, pelagic and immature hammerhead sharks.</li> <li>Monthly estimates of 14 high-resolution spatially explicit environmental and biotic variables (1 km grid resolution): Bathymetry; Slope; Distance from shore; Distance to 40m depth; Sand; Mud; Gravel; Seabed disturbance; Tidal current; Chlorophyll a; Sea surface temp; Distance to plankton; Distance to prey (saved as .R data)</li> <li>Model objects, R code, and model outputs of the Boosted Regression Tree modelling.</li> <li>Predicted monthly distributions (and associated spatially explicit uncertainty) of Bryde's whales, common dolphins, bottlenose dolphins, bronze whaler sharks, pelagic sharks, immature hammerhead sharks, and richness of large marine predators in the Hauraki Gulf, New Zealand, (January to December). Monthly richness estimates of large marine predators.</li> </ul>

publicJun 2025View details →

Spatial modelling of aerial survey data reveals an important European storm-petrel hotspot and its underlying drivers within the North-East Atlantic

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publicNov 2022View details →

Using unoccupied aerial vehicles to estimate availability and group size error for aerial surveys of coastal dolphins

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publicMay 2023View details →

Large marine predator aerial survey data for Hauraki Gulf, New Zealand

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opencc-by-4.0Nov 2019View details →

A curated dataset of aerial survey images over the central Congo Basin, 1958

This dataset contains a subset data from the Belgian Science Policy Office funded “Congo basin eco-climatological data recovery and valorisation" project (COBECORE, contract BR/175/A3/COBECORE). The data included is curated and pre-processed aerial survey imagery as used in a a land-use land-cover change analysis "Historical aerial surveys map long-term changes of forest cover and structure in the central Congo Basin".  The dataset includes: <ul> <li>the pre-processed images (aerial_images.tar.gz)</li> <li>the meta-data associated with the aerial images (flight_paths*)</li> <li>the final orthomosaic (yangambi_orthomosaic.tif)</li> </ul> For the full methodology we refer to the full paper: Hufkens K., et al. (2020) Historical Aerial Surveys Map Long-Term Changes of Forest Cover and Structure in the Central Congo Basin. Remote Sensing, 12, 638. Please cite the work as such.

opencc-byOct 2020View details →

Aerial survey - low res

Low resolution version of an aerial survey using a drone, data tied to OSGB36 using GPS Source: Objaverse 1.0 / Sketchfab

Table 4 in A comparison of image and observer based aerial surveys of narwhal

Table 4. Summary statistics of survey results and narwhal abundance estimates from surveys conducted in Melville Bay, West Greenland from 25 to 30 August 2014. Off-effort sightings by the aerial observers were only included in modeling of the detection function. Strata without narwhal sightings were excluded from this table (i.e., south and northwest). Abundance estimates are corrected for availability bias with â (0) being 0.257 for the aerial observer sightings and 0.22 for the image sightings. Aerial observer sightings were truncated at 1,300 m. CV values are given in parentheses. Ind. = individuals.<table><tbody><tr><th></th><th></th><th></th><th></th><th></th><th>Uncorrected</th><th></th><th></th><th>Abundance</th></tr></tbody><tbody><tr><th></th><td></td><td></td><td>Encounter</td><td>Mean</td><td>density</td><td>Uncorrected</td><td>Uncorrected</td><td>of individuals</td></tr><tr><th>Platform</th><td>Stratum</td><td>Encounter rate (groups/km)</td><td>rate (ind./km)</td><td>group size</td><td>of groups (groups/km2)</td><td>density of ind. (ind./km2)</td><td>abundance of individuals</td><td>corrected for availability bias</td></tr><tr><th>Aerial</th><td>Northeast</td><td>0.032 (0.86)</td><td>0.084 (0.78)</td><td>2.6 (0.20)</td><td>0.046 (0.93)</td><td>0.115 (0.90)</td><td>300.7 (0.89)</td><td>1,171.0 (0.90)</td></tr><tr><th>observers</th><td>Central</td><td>0.068 (0.50)</td><td>0.261(0.53)</td><td>3.8 (0.11)</td><td>0.046 (0.53)</td><td>0.177 (0.52)</td><td>366.5 (0.52)</td><td>1,426.1 (0.53)</td></tr><tr><th></th><td>All strata</td><td>0.053 (0.41)</td><td>0.187(0.44)</td><td>3.5 (0.10)</td><td>0.046 (0.58)</td><td>0.142 (0.50)</td><td>667.2 (0.50)</td><td>2,596.1 (0.51)</td></tr><tr><th>Images</th><td>Northeast</td><td>0.049 (0.94)</td><td>0.105(0.92)</td><td>2.1 (0.91)</td><td>0.049 (0.94)</td><td>0.105 (0.92)</td><td>217.8 (0.92)</td><td>990 (0.93)</td></tr><tr><th></th><td>Central</td><td>0.059 (0.70)</td><td>0.130(0.61)</td><td>2.2 (0.71)</td><td>0.059 (0.70)</td><td>0.130 (0.61)</td><td>340.0 (0.61)</td><td>1,545.5 (0.61)</td></tr><tr><th></th><td>All strata</td><td>0.055 (0.55)</td><td>0.119(0.50)</td><td>2.2 (0.78)</td><td>0.055 (0.55)</td><td>0.119 (0.50)</td><td>557.8 (0.50)</td><td>2,535.5 (0.51)</td></tr></tbody></table>

Table 2 in A comparison of image and observer based aerial surveys of narwhal

Table 2. Summary of sightings by image analysts and/or aerial observers, with and without truncation at 500 m. Where both aerial observer pairs had the same sighting with different group size or perpendicular distance estimates, an averaged value was used.<table><tbody><tr><th></th><th></th><th></th><th>Only</th><th></th><th>Sighted by</th><th>Sighted by</th></tr></tbody><tbody><tr><th></th><td>Sighted by</td><td></td><td>sight by</td><td>Only</td><td>image</td><td>image analyst</td></tr><tr><th></th><td>image</td><td>Sighted by</td><td>image</td><td>sighted by</td><td>analyst</td><td>and/or</td></tr><tr><th></th><td>analyst</td><td>observer</td><td>analyst</td><td>observer</td><td>and observer</td><td>observer</td></tr><tr><th>No truncation</th></tr><tr><th>No. of groups</th><td>62</td><td>63</td><td>34</td><td>35</td><td>28</td><td>97</td></tr><tr><th>No. of animals</th><td>135</td><td>227</td><td>62</td><td>124</td><td>88</td><td>274</td></tr><tr><th>Average group size</th><td>2.2</td><td>3.6</td><td>1.8</td><td>3.5</td><td>3.1</td><td>2.8</td></tr><tr><th>Average distance</th><td>227</td><td>580</td><td>237</td><td>839</td><td>329</td><td>454</td></tr><tr><th>Truncation = 500 m</th><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>No. of groups</th><td>62</td><td>36</td><td>34</td><td>8</td><td>28</td><td>70</td></tr><tr><th>No. of animals</th><td>135</td><td>126</td><td>62</td><td>24</td><td>88</td><td>173</td></tr><tr><th>Average group size</th><td>2.2</td><td>3.5</td><td>1.8</td><td>3.0</td><td>3.1</td><td>2.5</td></tr><tr><th>Average distance</th><td>227</td><td>269</td><td>237</td><td>329</td><td>234</td><td>247</td></tr></tbody></table>

Table 3 in A comparison of image and observer based aerial surveys of narwhal

Table 3. AIC values after fitting explanatory variables to the DS and MR models. The final model chosen, Model 1, is given in bold and ΔAIC indicates the difference between the chosen model and the specified model. HN indicates a half-normal form and HR indicates a hazard-rate form for the DS model. The explanatory variables are perpendicular distance (D), group size (S), group size as a factor with three classes (1, 2–5, and ≥ 6 narwhals) (S3), Beaufort (BF), side of airplane (SP), observer pair (O), and time to next observation ≤ 10 s (T). Appendix S3 provides an overview of all the models that were developed.<table><tbody><tr><th>Model</th><th>DS model</th><th>MR model</th><th>No. of parameters</th><th>AIC</th><th>ΔAIC</th></tr></tbody><tbody><tr><th>1</th><td>HN: D + BF</td><td>D + O + S 3</td><td>5</td><td>1,330.91</td><td>0</td></tr><tr><th>2</th><td>HN: D + BF</td><td>D + O + S</td><td>5</td><td>1,332.81</td><td>1.90</td></tr><tr><th>3</th><td>HN: D + BF + S3</td><td>D + O + T</td><td>6</td><td>1,333.10</td><td>2.19</td></tr><tr><th>4</th><td>HN: D + BF</td><td>D + O</td><td>4</td><td>1,333.50</td><td>2.59</td></tr><tr><th>5</th><td>HN: D + BF + S3</td><td>D + O</td><td>5</td><td>1,335.08</td><td>4.17</td></tr><tr><th>6</th><td>HR: D + BF</td><td>D + O + S3</td><td>5</td><td>1,336.97</td><td>6.06</td></tr></tbody></table>

Table 1 in A comparison of image and observer based aerial surveys of narwhal

Table 1. Summary of survey effort in the four strata during aerial surveys conducted in Melville Bay from 25 to 30 August 2014.<table><tbody><tr><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th>Aerial observers</th></tr></tbody><tbody><tr><th></th><td></td><td></td><td></td><td></td><td></td><td>Image</td><td></td><td>Aerial observers</td><td>(truncated 500 m)</td></tr><tr><th></th><td></td><td>Planned/</td><td>Length of</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th></th><td>Area</td><td>completed</td><td>surveyed</td><td>Analyzed</td><td>No. of</td><td>No.</td><td>Ave. group</td><td>No. of</td><td>No.</td><td>Ave. group</td><td>No. of</td><td>No.</td><td>Ave. group</td></tr><tr><th>Stratum</th><td>(km2)</td><td>transects (no.)</td><td>transects (km)</td><td>images a</td><td>sightings</td><td>of ind.b</td><td>size n (CV)</td><td>sightings</td><td>of ind.</td><td>size n (CV)</td><td>sightings</td><td>of ind.</td><td>size n (CV)</td></tr><tr><th>NW</th><td>6,376</td><td>5 / 4</td><td>226</td><td>2,066</td><td>0</td><td>0</td><td>0 (0)</td><td>0</td><td>0</td><td>0 (0)</td><td>0</td><td>0</td><td>0 (0)</td></tr><tr><th>NE</th><td>2,076</td><td>11 / 12</td><td>468</td><td>6,572</td><td>23</td><td>49</td><td>2.1 (0.95)</td><td>15</td><td>39</td><td>2.6 (0.77)</td><td>13</td><td>32.5</td><td>2.5 (0.76)</td></tr><tr><th>C</th><td>2,621</td><td>9 / 18</td><td>663</td><td>8,193</td><td>39</td><td>86</td><td>2.2 (0.73)</td><td>48</td><td>188</td><td>3.9 (0.69)</td><td>23</td><td>93.5</td><td>4.1 (0.61)</td></tr><tr><th>S</th><td>3,748</td><td>13 / 10</td><td>575</td><td>4,105</td><td>0</td><td>0</td><td>0 (0)</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><th>All strata</th><td>14,821</td><td>38 / 44</td><td>1,932</td><td>20,936</td><td>62</td><td>135</td><td>2.2 (0.77)</td><td>63</td><td>227</td><td>3.6 (0.72)</td><td>36</td><td>126</td><td>3.5 (0.69)</td></tr></tbody></table>a Including 180 off-effort images that were not used in the analysis. b Ind. = individuals.