Counts of Birds in Aerial Photos from Fall Waterfowl Surveys, Izembek Lagoon, Alaska, 2017-2019

Metadata:

Identification_Information:
Citation:
Citation_Information:
Originator: Weiser, Emily L. (ORCID: 0000-0003-1598-659X)
Originator: Flint, Paul L. (ORCID: 0000-0002-8758-6993)
Originator: Marks, Dennis K.
Originator: Shults, Brad S.
Originator: Wilson, Heather M.
Originator: Thompson, Sarah J.
Originator: Fischer, Julian B.
Publication_Date: 20220405
Title:
Counts of Birds in Aerial Photos from Fall Waterfowl Surveys, Izembek Lagoon, Alaska, 2017-2019
Geospatial_Data_Presentation_Form: tabular digital data
Publication_Information:
Publication_Place: Anchorage, Alaska
Publisher: U.S. Geological Survey, Alaska Science Center
Other_Citation_Details:
Suggested Citation: Weiser, E.L., Flint, P.L., Marks, D.K., Shults, B.S., Wilson, H.M., Thompson, S.J., Fischer, J.B., 2022, Counts of birds in aerial photos from fall waterfowl surveys, Izembek Lagoon, Alaska, 2017-2019: U.S. Geological Survey data release, https://doi.org/10.5066/P9ALG8MY
Online_Linkage: https://doi.org/10.5066/P9ALG8MY
Larger_Work_Citation:
Citation_Information:
Originator: U.S. Geological Survey, Alaska Science Center
Publication_Date: 2020
Title:
USGS and U.S. Fish and Wildlife Service Science Support (SSP) and Quick Response Program (QRP)
Geospatial_Data_Presentation_Form: website
Series_Information:
Series_Name: Alaska Science Portal
Issue_Identification: 421
Publication_Information:
Publication_Place: Anchorage, Alaska
Publisher: U.S. Geological Survey, Alaska Science Center
Other_Citation_Details:
This is a link to the broader USGS Alaska Science Center research project supported by these data. Users will find a description of the research project and links to associated reports, publications, and data products.
Online_Linkage: https://alaska.usgs.gov/portal/project.php?project_id=421
Description:
Abstract:
This dataset includes tables summarizing image information and bird counts from the aerial digital images taken over open water at Izembek Lagoon in Alaska in fall 2017-2019. These summaries list one record per image and provide the camera parameters, latitude, longitude, altitude, and automated and manual counts representing the total number of birds in each taxon (brant, white-cheeked geese, emperor geese, gulls, and other birds) identified in the image. The original images (.JPG format) and annotations are provided in an accompanying USGS data release (Weiser et al. 2022).
Purpose:
These data were collected to test a photographic survey design for monitoring the number of brant staging at Izembek Lagoon, Alaska, each fall. The photographic survey was tested as an option to potentially replace the traditional ocular aerial surveys that involve uncertainty around observer estimates of numbers of geese present. The count data were used to evaluate differences between automated and manual counts as well as to develop estimates of the total number of brant and white-cheeked geese on the lagoon during each annual survey period. Accuracy of the automated algorithm (assuming manual counts represent truth) can also be related to altitude or camera settings.
Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 20170930
Ending_Date: 20191011
Currentness_Reference: Observed
Status:
Progress: Complete
Maintenance_and_Update_Frequency: None planned
Spatial_Domain:
Description_of_Geographic_Extent: Izembek Lagoon, Alaska
Bounding_Coordinates:
West_Bounding_Coordinate: -163.1250
East_Bounding_Coordinate: -162.4658
North_Bounding_Coordinate: 55.4913
South_Bounding_Coordinate: 55.1381
Keywords:
Theme:
Theme_Keyword_Thesaurus: USGS Metadata Identifier
Theme_Keyword: USGS:ASC450
Theme:
Theme_Keyword_Thesaurus: ISO 19115 Topic Category
Theme_Keyword: Biota
Theme_Keyword: Environment
Theme:
Theme_Keyword_Thesaurus: NASA GCMD Earth Science Keyword Thesaurus
Theme_Keyword: Animals/Vertebrates
Theme_Keyword: Birds
Theme_Keyword: Ducks/Geese/Swans
Theme_Keyword: Waders/Gulls/Auks and Allies
Theme_Keyword: Estuarine habitat
Theme_Keyword: Photography
Theme:
Theme_Keyword_Thesaurus: USGS CSA Biocomplexity Thesaurus
Theme_Keyword: Waterfowl
Theme_Keyword: Migratory birds
Theme_Keyword: Aerial surveys
Theme:
Theme_Keyword_Thesaurus: USGS Thesaurus
Theme_Keyword: Wildlife
Theme_Keyword: Migratory species
Theme_Keyword: Tundra ecosystems
Theme_Keyword: Coastal ecosystems
Theme_Keyword: Wetland ecosystems
Theme_Keyword: Aquatic ecosystems
Theme_Keyword: Aerial photography
Theme_Keyword: Relative abundance analysis
Theme_Keyword: Image collections
Theme_Keyword: Population dynamics
Theme:
Theme_Keyword_Thesaurus: None
Theme_Keyword: Branta bernicla
Theme_Keyword: Branta hutchinsii
Theme_Keyword: Anser canagicus
Theme_Keyword: Izembek National Wildlife Refuge
Place:
Place_Keyword_Thesaurus: USGS Geographic Names Information System (GNIS)
Place_Keyword: Alaska
Place_Keyword: Alaska Peninsula
Place_Keyword: Izembek Lagoon
Taxonomy:
Keywords/Taxon:
Taxonomic_Keyword_Thesaurus: None
Taxonomic_Keywords: Branta bernicla nigricans
Taxonomic_Keywords: Branta hutchinsii
Taxonomic_Keywords: Branta
Taxonomic_Keywords: Anser canagicus
Taxonomic_Keywords: Anatidae
Taxonomic_Keywords: Laridae
Taxonomic_System:
Classification_System/Authority:
Classification_System_Citation:
Citation_Information:
Originator: ITIS Integrated Taxonomic Information System
Publication_Date: Unknown
Title: ITIS Integrated Taxonomic Information System
Geospatial_Data_Presentation_Form: online database
Publication_Information:
Publication_Place: online
Publisher: ITIS-North America
Other_Citation_Details:
Taxonomic details retrieved January 24, 2022 from the Integrated Taxonomic Information System online database: https://www.itis.gov
Online_Linkage: https://www.itis.gov
Classification_System_Modifications:
ITIS currently lists emperor geese in the genus Chen. However, the most current taxonomic designation by the American Ornithological Society's (AOU) Check-list of North American Birds considers emperor geese in the genus Anser http://checklist.aou.org/taxa
Here, we follow the current AOU designation as described in: Chesser, R.T., Burns, K.J., Cicero, C., Dunn, J.L., Kratter, A.W., Lovette, I.J., Rasmussen, P.C., Remsen, J.V., Jr., Rising, J.D., Stotz, D.F., Winker, K. 2017. Fifty-eighth supplement to the American Ornithological Society's Check-list of North American Birds. The Auk:134(3)751-773 https://doi.org/10.1642/AUK-17-72.1
Taxonomic_Procedures:
Species were identified by skilled observers based on general appearance.
Taxonomic_Completeness:
Taxonomy is complete for all samples. No vouchers were collected.
Taxonomic_Classification:
Taxon_Rank_Name: Kingdom
Taxon_Rank_Value: Animalia
Taxonomic_Classification:
Taxon_Rank_Name: Subkingdom
Taxon_Rank_Value: Bilateria
Taxonomic_Classification:
Taxon_Rank_Name: Infrakingdom
Taxon_Rank_Value: Deuterostomia
Taxonomic_Classification:
Taxon_Rank_Name: Phylum
Taxon_Rank_Value: Chordata
Taxonomic_Classification:
Taxon_Rank_Name: Subphylum
Taxon_Rank_Value: Vertebrata
Taxonomic_Classification:
Taxon_Rank_Name: Infraphylum
Taxon_Rank_Value: Gnathostomata
Taxonomic_Classification:
Taxon_Rank_Name: Superclass
Taxon_Rank_Value: Tetrapoda
Taxonomic_Classification:
Taxon_Rank_Name: Class
Taxon_Rank_Value: Aves
Taxonomic_Classification:
Taxon_Rank_Name: Order
Taxon_Rank_Value: Anseriformes
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Anatidae
Applicable_Common_Name: TSN: 174983
Taxonomic_Classification:
Taxon_Rank_Name: Subfamily
Taxon_Rank_Value: Anserinae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Branta
Applicable_Common_Name: TSN: 174998
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Branta bernicla
Applicable_Common_Name: Brant
Applicable_Common_Name: TSN: 175011
Taxonomic_Classification:
Taxon_Rank_Name: Subspecies
Taxon_Rank_Value: Branta bernicla nigricans
Applicable_Common_Name: TSN: 714723
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Branta hutchinsii
Applicable_Common_Name: TSN: 714068
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Anser
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Anser canagicus
Applicable_Common_Name: Emperor goose
Applicable_Common_Name: TSN: 175031
Taxonomic_Classification:
Taxon_Rank_Name: Order
Taxon_Rank_Value: Charadriiformes
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Laridae
Applicable_Common_Name: TSN: 176802
Access_Constraints: None
Use_Constraints:
It is requested that the authors and the USGS Alaska Science Center be cited for any subsequent publications that reference this dataset.
Point_of_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: U.S. Geological Survey, Alaska Science Center
Contact_Address:
Address_Type: Mailing and Physical
Address: 4210 University Drive
City: Anchorage
State_or_Province: Alaska
Postal_Code: 99508
Country: USA
Contact_Voice_Telephone: 907-786-7000
Contact_Electronic_Mail_Address: ascweb@usgs.gov
Data_Set_Credit:
These data were collected by the U.S. Fish and Wildlife Service in collaboration with the U.S. Geological Survey. We thank M. Laker, J. Wittkop, W. Larned, T. Zeller, D. Safine, C. Dau, P. Anderson, E. Mallek, K. Bollinger, D. Ward, C. Sowl, C. Monette, A. Ellsworth, A. Williams, T. Zeller, the staff at Dynamic Ventures, and Izembek National Wildlife Refuge for their contributions. Funding was provided by the USGS Science Support Program and USFWS Migratory Bird Management.
Cross_Reference:
Citation_Information:
Originator: Weiser, E.L.
Originator: Flint, P.L.
Originator: Marks, D.K.
Originator: Shults, B.S.
Originator: Wilson, H.M.
Originator: Thompson, S.J.
Originator: Fischer, J.B.
Publication_Date: 2023
Title:
Optimizing Surveys of Fall-Staging Geese Using Aerial Imagery and Automated Counting
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: Wildlife Society Bulletin
Issue_Identification: 47(1):e1407
Publication_Information:
Publication_Place: online
Publisher: The Wildlife Society
Other_Citation_Details:
Weiser, E.L., Flint, P.L., Marks, D.K., Shults, B.S., Wilson, H.M., Thompson, S.J., Fischer, J.B. 2023. Optimizing surveys of fall-staging geese using aerial imagery and automated counting. Wildlife Society Bulletin 47(1):e1407 doi:10.1002/wsb.1407
Online_Linkage: https://doi.org/10.1002/wsb.1407
Data_Quality_Information:
Attribute_Accuracy:
Attribute_Accuracy_Report:
Camera parameters were derived directly from the camera when each photo was captured. Latitude, longitude, and altitude were assigned to each photo by cross-referencing the photo sequence and timestamp with flight logs produced by Aviatrix, with a small subset spot-checked against satellite imagery to ensure locations were accurately assigned. Automated counts were implemented by an algorithm trained on a subset of our photos. Manually corrected counts were implemented through visual inspection and correction of the automated annotations; only one person evaluated each photo, so detection/identification accuracy was not assessed. The dataset typically refers to canada geese, most white-cheeked geese in the study area are expected to be Taverner’s cackling geese, but were not distinguishable in our photos.
Logical_Consistency_Report:
Attribute values fall within expected ranges and data were proofed for the presence of duplication and omission. Some survey replicates were not completed, so fewer than the expected number of photos are included (each replicate would have 15,028 photos if both cameras fired successfully at all planned trigger points within and outside the lagoon). Occasional photos may be missing latitude, longitude, or altitude if they were taken outside the survey area or if an associated metadata record could not be identified. Images not automatically identified as containing geese (of any species) were not manually evaluated, as indicated by "NA" values in the manual count columns for those photos; the exception was the 2017-10-03 survey, for which all photos were manually evaluated.
Completeness_Report:
One survey included in the image archive (2018-10-17) was not processed and is excluded here. For the other surveys, photos captured outside the open water of the lagoon were excluded. Some photos are missing metadata if they did not have a corresponding Aviatrix flight log record (i.e., if Aviatrix skipped a record). Photos were captured only at preset points over Izembek Lagoon, Alaska, and its immediate perimeter
Positional_Accuracy:
Horizontal_Positional_Accuracy:
Horizontal_Positional_Accuracy_Report:
Positions recorded by a ublox-7P GNSS module (expected horizontal accuracy ±5–10 m; expected vertical accuracy ±15 m).
Lineage:
Methodology:
Methodology_Type: Field
Methodology_Description:
Our photographic survey design was developed to provide maximum coverage of Izembek Lagoon on a single flight without having to refuel the aircraft, thus maximizing efficiency and minimizing the time window during which bird movement might confound the counts. We used a systematic sampling design with regularly spaced points taken along 49 transects over the open water of the lagoon. In 2017, we used 5,468 planned photo locations over the open water of the lagoon; in 2018 and 2019, we expanded some transects to cover the full width of the lagoon, resulting in 5,649 photo locations. We used a pair of cameras, described below, that were triggered automatically and simultaneously to obtain 2 non-overlapping images at each photo point, one on each side of the transect line. Our total potential sample was thus 10,944 (2017) to 11,298 (2018 and 2019) photos per survey replicate that would cover a combined footprint of 14.6–15.1% of the area of the lagoon. We aimed to center each replicate (spanning about 4 hours) on low tide, when we expected geese to be mostly stationary while feeding on exposed eelgrass beds. However, greater flexibility in timing could allow more replicates to be completed during suitable weather windows (which can be scarce in this study area), so we also completed one replicate at high tide to evaluate the consequences for the resulting population estimate.
Photo survey replicates were typically conducted on different days than the ocular replicates, but still within the fall staging period (late Sept to Oct). We conducted the photo flights in an amphibious Cessna 206, modified with dual belly camera ports, on days when the cloud ceiling was above 460 m with no more than occasional light rain to allow good views of the lagoon. Ground speed averaged 165 km/hr, and we chose a target altitude of 457 m ASL to avoid disturbing geese.
For each photo survey replicate, a camera operator was on board in addition to the pilot. We implemented our flight plan with the Aviatrix Flight Management System (AeroScientific, Blackwood, SA, Australia), which provided visual flight-line guidance to the pilot and automatically triggered cameras (through Aeroscientific Trigger Box 2018-011) when the aircraft passed within 150 m of preset locations. The system included a ublox-7P GNSS module to record latitude and longitude (expected accuracy ±5-10 m) and altitude (±15 m) in a log file when each photo was triggered. The camera operator monitored one screen showing the flight line and status of each camera trigger point, and another on which photos could be previewed to ensure camera settings were appropriate for the current light conditions.
Our camera setup consisted of two Canon EOS 5D R bodies equipped with 24 × 36 mm 50.6-megapixel sensors and either Canon EF 70-200mm f/2.8L IS III USM lenses (2017) or Canon EF 200mm f/2.8L II USM prime lenses (2018-2019). As part of the testing phase for this monitoring program, subsets of photos from 2017 were captured at nonstandard altitudes (<350 m or >550 m) or focal lengths (<200 mm), thus affecting the size and resolution of geese pictured in photos. We mounted the cameras inside the aircraft such that the distal ends of the lenses were just inside portholes in the aircraft body. We set the cameras to manual mode with focus set near infinity, aperture 2.8 to 4.0 depending on current conditions, shutter speed 1/5000 to 1/8000 sec, automatic ISO, and exposure compensation -2.0 to -2.3 to avoid overexposing birds against the dark water. Each camera saved .JPG images to a CompactFlash and/or SD card (about 200 GB per replicate). To avoid overlap among photos, we tilted each camera away from the vertical axis (plumb line) by approximately 5.6° and set camera trigger points at spatial intervals of 62 m, which corresponded to about one photo every 1.35 sec at our average ground speed of 165 km/hr. With the specifications of our camera sensors, 200 mm focal length, and our target aircraft altitude of 457 m, the expected footprint of each photo was 4555 m2 (83.1 m wide by 54.8 m parallel to the path of the aircraft).
Source_Information:
Source_Citation:
Citation_Information:
Originator: Weiser, E.L.
Originator: Flint, P.L.
Originator: Marks, D.K.
Originator: Shults, B.S.
Originator: Wilson, H.M.
Originator: Thompson, S.J.
Originator: Fischer, J.B.
Publication_Date: 2022
Title:
Aerial Photo Imagery from Fall Waterfowl Surveys, Izembek Lagoon, Alaska, 2017-2019
Geospatial_Data_Presentation_Form: aerial imagery
Series_Information:
Series_Name: USGS Data Release
Issue_Identification: doi:10.5066/P9UHP1LE
Publication_Information:
Publication_Place: online
Publisher: U.S. Geological Survey
Other_Citation_Details:
Weiser, E.L., Flint, P.L., Marks, D.K., Shults, B.S., Wilson, H.M., Thompson, S.J., Fischer, J.B., 2022, Aerial photo imagery from fall waterfowl surveys, Izembek Lagoon, Alaska, 2017-2019: U.S. Geological Survey data release, https://doi.org/10.5066/P9UHP1LE
Online_Linkage: https://doi.org/10.5066/P9UHP1LE
Type_of_Source_Media: digital database file
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 20170930
Ending_Date: 20191011
Source_Currentness_Reference: image acquisition date
Source_Citation_Abbreviation: Weiser et al. 2022
Source_Contribution:
Original imagery and annotations that are summarized in the count data presented here.
Source_Information:
Source_Citation:
Citation_Information:
Originator: Hogrefe, K.R.
Originator: Ward, D.H.
Originator: Donnelly, T.F.
Originator: Dau, N.
Publication_Date: 2014
Title:
Establishing a Baseline for Regional Scale Monitoring of Eelgrass (Zostera marina) Habitat on the Lower Alaska Peninsula
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: Remote Sensing
Issue_Identification: 6(12):12447-12447
Publication_Information:
Publication_Place: online
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Other_Citation_Details:
Hogrefe, K.R., Ward, D.H., Donnelly, T.F., Dau, N. 2014. Establishing a Baseline for Regional Scale Monitoring of Eelgrass (Zostera marina) Habitat on the Lower Alaska Peninsula. Remote Sensing 6(12):12447-12447 doi:10.3390/rs61212447
Online_Linkage: https://doi.org/10.3390/rs61212447
Type_of_Source_Media: publication
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2014
Source_Currentness_Reference: publication date
Source_Citation_Abbreviation: Hogrefe et al. 2014
Source_Contribution:
Raster data used to assign each photo to a habitat type (eelgrass, seaweeds, substrate [mud], water channel, or outside the lagoon).
Process_Step:
Process_Description:
Images were captured with Canon EOS 5D R cameras equipped with 24 x 36 mm 50.6-megapixel sensors and either Canon EF 70-200mm f/2.8L IS III USM lenses (2017) or Canon EF 200mm f/2.8L II USM prime lenses (2018–2019). Metadata have been added to the JPG file properties (e.g., EXIF tags), but the JPG images have otherwise not been altered. Accompanying GPS data were captured by a ublox-7P GNSS module (expected horizontal accuracy ±5–10 m; vertical ±15 m) via an Aviatrix Flight Management System (AeroScientific, Blackwood, SA, Australia). Automatic annotation of objects in photos was performed with the "Geese" template in CountThings (Dynamic Ventures, Inc., Cupertino, CA, USA). Manually corrected counts were evaluated and corrected through the CountThings interface by three technicians, where each photo was evaluated by one person.
Process_Date: Unknown
Process_Step:
Process_Description:
After each photo survey replicate, we cross-referenced the image EXIF data and the Aviatrix metadata log to geotag each photo based on photo sequence and timestamps. We verified the accuracy of the assigned location against satellite imagery for photos with visible landmarks such as shoreline or islands. We also assigned each photo to a habitat stratum (eelgrass, seaweeds, substrate [mud], water channel, or outside the lagoon) by cross-referencing the latitude and longitude with a GIS layer (Hogrefe et al. 2014) such that each photo was assigned to a single habitat type. We excluded photos from outside the lagoon from all further analysis.
Source_Used_Citation_Abbreviation: Hogrefe et al. 2014
Source_Used_Citation_Abbreviation: Weiser et al. 2022
Process_Date: Unknown
Process_Step:
Process_Description:
We worked with software developers to train an algorithm to automatically identify geese in our images through a commercial program called CountThings (Dynamic Ventures, Inc., Cupertino, CA, USA). We provided 1700 appropriately annotated images from one replicate (19 Oct 2018; all at standard altitude and focal length) to develop an automated identification and counting algorithm. The algorithm was trained to identify brant and white-cheeked geese as well as three other classes of non-target taxa: emperor geese (Anser canagicus), gulls (Larus spp.), and "other" birds (mostly ducks). This customized algorithm has been made commercially available by CountThings for use in other monitoring programs: https://countthings.com/en/counting-templates "Geese" template under "Animals & Wildlife;" ID:349 Ver:001).
Source_Used_Citation_Abbreviation: Weiser et al. 2022
Process_Date: Unknown
Process_Step:
Process_Description:
After running the automated algorithm on all images, we extracted the images in which geese of any species were detected and manually corrected counts in those photos through the CountThings user interface. We corrected false positives, false negatives, and mis-identifications for all five taxa. We also manually checked all photos from one replicate (3 Oct 2017), including photos in which no geese were detected by the automated algorithm, to assess accuracy of the algorithm in identifying presence vs. absence of brant and white-cheeked geese in the photos. Each photo was corrected by only one person, so we did not evaluate accuracy of the manual corrections. In this dataset, the total count for each taxon is provided for each photo; the annotations are provided separately in Weiser et al. (2022).
Source_Used_Citation_Abbreviation: Weiser et al. 2022
Process_Date: Unknown
Spatial_Data_Organization_Information:
Direct_Spatial_Reference_Method: Point
Spatial_Reference_Information:
Horizontal_Coordinate_System_Definition:
Geographic:
Latitude_Resolution: 0.00000001
Longitude_Resolution: 0.00000001
Geographic_Coordinate_Units: Decimal degrees
Geodetic_Model:
Horizontal_Datum_Name: World Geodetic System of 1984
Ellipsoid_Name: World Geodetic System of 1984
Semi-major_Axis: 6378137
Denominator_of_Flattening_Ratio: 298.257223563
Entity_and_Attribute_Information:
Detailed_Description:
Entity_Type:
Entity_Type_Label: goose_fallSurveyCounts_izembek
Entity_Type_Definition:
Folder (with sub-folders grouped by year) containing tables summarizing image information and bird counts from the aerial digital images taken over open water at Izembek Lagoon in Alaska in fall 2017-2019. These summaries list one record per image and provide the camera parameters, GPS location and altitude, and automated and manual counts representing the total number of birds in each taxon (brant, white-cheeked geese, emperor geese, gulls, and other birds) identified in the image. The dataset typically refers to canada geese, most white-cheeked geese in the study area are expected to be Taverner’s cackling geese, but were not distinguishable in our photos. Presented in Comma Separated Value (CSV) formatted tables.
The original images (JPG format) and annotations are provided in an accompanying USGS data release (Weiser et al. 2022)
File naming convention: Combined_counts_[YYYY-MM-DD]_[camera]; where [camera] is the specific camera ID (i.e., camera body) used to capture the image.
Entity_Type_Definition_Source: Author defined
Attribute:
Attribute_Label: JPG
Attribute_Definition:
Filename of the digital image as assigned by the camera. Sometimes, but not always, includes a prefix to indicate the camera number (CAM1-CAM4).
Attribute_Definition_Source: Author defined
Attribute_Domain_Values:
Unrepresentable_Domain: Filename of the digital image
Attribute:
Attribute_Label: Camera
Attribute_Definition:
ID of the specific camera (CAM1-CAM4) used to capture the image. Cameras are uniquely named across all years (e.g., CAM1 always refers to the same camera body), but capitalization varies.
Attribute_Definition_Source: Author defined
Attribute_Domain_Values:
Unrepresentable_Domain:
ID of the specific camera (i.e., camera body) used to capture the image
Attribute:
Attribute_Label: Date
Attribute_Definition: Date on which the image was captured
Attribute_Definition_Source: Author defined
Attribute_Domain_Values:
Range_Domain:
Range_Domain_Minimum: 2017-09-30
Range_Domain_Maximum: 2019-10-11
Attribute_Units_of_Measure: Date (YYYY-MM-DD)
Attribute:
Attribute_Label: Time
Attribute_Definition: Time at which the image was captured
Attribute_Definition_Source: Author defined
Attribute_Domain_Values:
Range_Domain:
Range_Domain_Minimum: 10:38:07
Range_Domain_Maximum: 17:51:14
Attribute_Units_of_Measure: Time (hh:mm:ss), local time
Attribute:
Attribute_Label: Latitude
Attribute_Definition:
Latitude at which the image was captured, in decimal degrees (WGS 84).
Attribute_Definition_Source: Author defined
Attribute_Domain_Values:
Range_Domain:
Range_Domain_Minimum: 55.163595
Range_Domain_Maximum: 55.46001667
Attribute_Units_of_Measure: Decimal degrees (WGS 84)
Attribute:
Attribute_Label: Longitude
Attribute_Definition:
Longitude at which the image was captured, in decimal degrees (WGS 84).
Attribute_Definition_Source: Author defined
Attribute_Domain_Values:
Range_Domain:
Range_Domain_Minimum: -163.0813133
Range_Domain_Maximum: -162.50175333
Attribute_Units_of_Measure: Decimal degrees (WGS 84)
Attribute:
Attribute_Label: Altitude
Attribute_Definition:
Altitude of the aircraft when the image was captured, in meters.
Attribute_Definition_Source: Author defined
Attribute_Domain_Values:
Range_Domain:
Range_Domain_Minimum: 147.8
Range_Domain_Maximum: 607.9
Attribute_Units_of_Measure: Meters
Attribute:
Attribute_Label: FocalLength
Attribute_Definition: Focal length of the camera when the image was captured, in mm.
Attribute_Definition_Source: Author defined
Attribute_Domain_Values:
Range_Domain:
Range_Domain_Minimum: 70
Range_Domain_Maximum: 200
Attribute_Units_of_Measure: Millimeters
Attribute:
Attribute_Label: PhotoArea
Attribute_Definition:
Total footprint covered by the image on the water’s surface, in square meters, as calculated from altitude, focal length, sensor size, and camera angle.
Attribute_Definition_Source: Author defined
Attribute_Domain_Values:
Range_Domain:
Range_Domain_Minimum: 476.4219825
Range_Domain_Maximum: 38583.52838
Attribute_Units_of_Measure: Square meters
Attribute:
Attribute_Label: Habitat
Attribute_Definition:
Habitat stratum to which the photo was assigned based on the latitude and longitude (eelgrass, seaweeds, substrate [mud], water channel, or outside the lagoon), from a raster layer developed by Hogrefe et al. (2014).
Attribute_Definition_Source: Author defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Eelgrass
Enumerated_Domain_Value_Definition: Eelgrass habitat stratum
Enumerated_Domain_Value_Definition_Source: Author defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Substrate
Enumerated_Domain_Value_Definition: Substrate [mud] habitat stratum
Enumerated_Domain_Value_Definition_Source: Author defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: WaterChannel
Enumerated_Domain_Value_Definition: Water Channel habitat stratum
Enumerated_Domain_Value_Definition_Source: Author defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Seaweeds
Enumerated_Domain_Value_Definition: Seaweeds habitat stratum
Enumerated_Domain_Value_Definition_Source: Author defined
Attribute:
Attribute_Label: Auto_Emperor
Attribute_Definition: Number of emperor geese automatically identified in the image.
Attribute_Definition_Source: Author defined
Attribute_Domain_Values:
Range_Domain:
Range_Domain_Minimum: 0
Range_Domain_Maximum: 3539
Attribute_Units_of_Measure: Count
Attribute:
Attribute_Label: Auto_Gull
Attribute_Definition:
Number of gulls (not identified to species) automatically identified in the image.
Attribute_Definition_Source: Author defined
Attribute_Domain_Values:
Range_Domain:
Range_Domain_Minimum: 0
Range_Domain_Maximum: 417
Attribute_Units_of_Measure: Count
Attribute:
Attribute_Label: Auto_Brant
Attribute_Definition: Number of brant automatically identified in the image.
Attribute_Definition_Source: Author defined
Attribute_Domain_Values:
Range_Domain:
Range_Domain_Minimum: 0
Range_Domain_Maximum: 1761
Attribute_Units_of_Measure: Count
Attribute:
Attribute_Label: Auto_Canada
Attribute_Definition:
Number of canada or cackling geese automatically identified in the image. While the dataset typically refers to canada geese, most white-cheeked geese in the study area are expected to be Taverner’s cackling geese, but were not distinguishable in our photos.
Attribute_Definition_Source: Author defined
Attribute_Domain_Values:
Range_Domain:
Range_Domain_Minimum: 0
Range_Domain_Maximum: 258
Attribute_Units_of_Measure: Count
Attribute:
Attribute_Label: Auto_Other
Attribute_Definition:
Number of other birds (usually ducks) automatically identified in the image.
Attribute_Definition_Source: Author defined
Attribute_Domain_Values:
Range_Domain:
Range_Domain_Minimum: 0
Range_Domain_Maximum: 1
Attribute_Units_of_Measure: Count
Attribute:
Attribute_Label: Manual_Emperor
Attribute_Definition:
Number of emperor geese manually identified in the image. If NA, the image was not manually corrected because the algorithm did not detect geese of any species.
Attribute_Definition_Source: Author defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: NA
Enumerated_Domain_Value_Definition: No Data
Enumerated_Domain_Value_Definition_Source: Author defined
Attribute_Domain_Values:
Range_Domain:
Range_Domain_Minimum: 0
Range_Domain_Maximum: 252
Attribute_Units_of_Measure: Count
Attribute:
Attribute_Label: Manual_Gull
Attribute_Definition:
Number of gulls (unidentified to species) manually identified in the image. If NA, the image was not manually corrected because the algorithm did not detect geese of any species.
Attribute_Definition_Source: Author defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: NA
Enumerated_Domain_Value_Definition: No Data
Enumerated_Domain_Value_Definition_Source: Author defined
Attribute_Domain_Values:
Range_Domain:
Range_Domain_Minimum: 0
Range_Domain_Maximum: 223
Attribute_Units_of_Measure: Count
Attribute:
Attribute_Label: Manual_Brant
Attribute_Definition:
Number of brant manually identified in the image. If NA, the image was not manually corrected because the algorithm did not detect geese of any species.
Attribute_Definition_Source: Author defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: NA
Enumerated_Domain_Value_Definition: No Data
Enumerated_Domain_Value_Definition_Source: Author defined
Attribute_Domain_Values:
Range_Domain:
Range_Domain_Minimum: 0
Range_Domain_Maximum: 4928
Attribute_Units_of_Measure: Count
Attribute:
Attribute_Label: Manual_Canada
Attribute_Definition:
Number of canada or cackling geese manually identified in the image. If NA, the image was not manually corrected because the algorithm did not detect geese of any species.
Attribute_Definition_Source: Author defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: NA
Enumerated_Domain_Value_Definition: No Data
Enumerated_Domain_Value_Definition_Source: Author defined
Attribute_Domain_Values:
Range_Domain:
Range_Domain_Minimum: 0
Range_Domain_Maximum: 636
Attribute_Units_of_Measure: Count
Attribute:
Attribute_Label: Manual_Other
Attribute_Definition:
Number of other birds (usually ducks) manually identified in the image. If NA, the image was not manually corrected because the algorithm did not detect geese of any species.
Attribute_Definition_Source: Author defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: NA
Enumerated_Domain_Value_Definition: No Data
Enumerated_Domain_Value_Definition_Source: Author defined
Attribute_Domain_Values:
Range_Domain:
Range_Domain_Minimum: 0
Range_Domain_Maximum: 4582
Attribute_Units_of_Measure: Count
Distribution_Information:
Distributor:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: U.S. Geological Survey, Alaska Science Center
Contact_Address:
Address_Type: Mailing and Physical
Address: 4210 University Drive
City: Anchorage
State_or_Province: Alaska
Postal_Code: 99508
Country: USA
Contact_Voice_Telephone: 907-786-7000
Contact_Electronic_Mail_Address: ascweb@usgs.gov
Resource_Description:
The U.S. Geological Survey, Alaska Science Center is the authoritative source and distributor of these data.
Distribution_Liability:
Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey, no warranty expressed or implied is made regarding the display or utility of the data for other purposes or on all computer systems, nor shall the act of distribution constitute any such warranty. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
Standard_Order_Process:
Digital_Form:
Digital_Transfer_Information:
Format_Name: CSV
Format_Information_Content:
Data are distributed in a Zip package containing data in CSV format and FGDC metadata in XML and HTML formats.
File_Decompression_Technique:
Compression applied by the 7-Zip utility using the default compression level [5]. The Zip package can be decompressed and unpacked by open source or commercially available unzip tools.
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Network_Resource_Name: https://doi.org/10.5066/P9ALG8MY
Fees: None
Metadata_Reference_Information:
Metadata_Date: 20230317
Metadata_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: U.S. Geological Survey, Alaska Science Center
Contact_Address:
Address_Type: Mailing and Physical
Address: 4210 University Drive
City: Anchorage
State_or_Province: Alaska
Postal_Code: 99508
Country: USA
Contact_Voice_Telephone: 907-786-7000
Contact_Electronic_Mail_Address: ascweb@usgs.gov
Metadata_Standard_Name:
FGDC Biological Data Profile of the Content Standard for Digital Geospatial Metadata (CSDGM)
Metadata_Standard_Version: FGDC-STD-001.1-1999

Generated by mp version 2.9.52 on Fri Mar 17 20:01:22 2023