DIGITAL AERIAL BASELINE
SURVEY OF MARINE WILDLIFE In Support of New York State Offshore
Wind Energy
• OSW represents an essential renewable energy resource for NYS toward achieving its State Energy Plan targets including meeting half of NYS electricity with renewable resources.
• NYS goal is to advance OSW in a manner that is sensitive to environmental, maritime and social issues in a cost effective manner that maximizes environmental and economic benefits
NYS Offshore Wind Energy (OSW)
Development
• Baseline data on potential wildlife exposure of NY Offshore Planning Area (OPA)
• Quarterly aerial digital surveys for three years
• Sample 5-10% of OPA
• Image resolution 1-2 cm GSD
Aerial Digital Survey
Requirements and Objectives
• High Level Summary and Discussion of Approach
• Review and feedback on timing of seasonal surveys
• Feedback on distribution and format of data
• Identify other potential collaborators to leverage the work for increased value
Feedback and suggestions should be sent to:
Webinar Goals
Image Analysis
Simon Warford
Ann Pembroke Project Manager
Stuart Clough Technical Director
APEM
Julia Robinson Willmott Technical Director
Normandeau
Data Management/
Reporting
Data Collection David Campbell
Survey Design Mark Rehfisch
Survey Execution Tracy Shaw John McCarthy
Simon Warford
Stephanie McGovern
Lauren Hooton
Melinda Sweeny
Stephanie McGovern Laura Jervis
Adam Kent
Crissy Sutter
Robert Kenney
Karen Gilland
Greg Forcey
Crissy Sutter
Mark Rehfisch
Preproccess Image ID QA/QC
Christian Newman Subcontract Manager
• Normandeau/APEM Team Proposal Framework
• Known Wildlife Distributions in OPA
• Approach
– Camera Sensor
– Flight Planning and Survey Design
– Data Output
– Adaptive Methods Consideration
– Survey Timing
• Data Distribution
• Opportunities for collaboration
Outline
• Confidence
– Species Identification
– Geospatial Accuracy
– Statistically and Scientifically Defensible
• Flexibility
– Offshore Planning Area (OPA) vs Wind Energy Area (WEA)
– Design
• Forward Thinking
– Change Detection
– Extra Data
– Potential Other Uses
Normandeau/APEM Team Proposal
Framework
KNOWN WILDLIFE
DISTRIBUTIONS IN OPA
Northwest Atlantic Seabird Catalog by USGS, BOEM, available at NOAA New England Aquarium using the North Atlantic Right Whale Consortium MARCO Mid-Atlantic Ocean Data Portal
Data Sources: Spatial Data
Spatial: Birds
Spatial: Birds
NY Offshore Planning Area
NY Wind Energy Area
Atlantic Offshore Seabird Dataset Catalog!( Roseate Tern
ROTE Probability
High
Low
Spatial: Roseate Tern
NY Offshore Planning Area
NY Wind Energy Area
Turtles Summer
Sightings Per Unit Effort
!( 1 - 100
!( 100 - 300
!( 300 - 800
!( 800 - 1,565
Relative Abundance
200 - 325
120 - 200
50 - 120
1 - 50
0
NY Offshore Planning Area
NY Wind Energy Area
Turtles Fall
Sightings Per Unit Effort
!( 1 - 40
!( 40 - 90
!( 90 - 180
!( 180 - 300
Relative Abundance
60 - 118
40 - 60
20 - 40
1 - 20
0
Spatial: Turtles
Showing sperm whale, sei whale, right whale, minke whale, humpback whale, fin whale
Spatial: Marine Mammals
APPROACH
Key Advantages to 1.5 cm Resolution
• More accurate measurements of head to tail and wingspan lengths
• Greater confidence in identification based on measurements (e.g., Flying shearwaters and sitting alcids and gulls)
• Greater confidence in identification of terns, bill colour visible at 1.5 cm
• High quality imagery resulting in more accurate flight height calculation
• Increased identification rates for most species
• Increased chance of identifying specific individual mammals based on their unique patterning
Key Advantages to 1.5 cm Resolution
• 1.5cm resolution is the same as a nickel at sea-surface
• More accurate measurements of head to tail and wingspan lengths
• Greater confidence in identification based on measurements (e.g., Flying shearwaters and sitting alcids and gulls)
• Greater confidence in identification of terns, bill colour visible at 1.5 cm
• High quality imagery resulting in more accurate flight height calculation
• Increased identification rates for most species
• Increased chance of identifying specific individual mammals based on their unique patterning
Bird Identification Rates: 2 cm v predicted 1.5 cm
Species Group / Species
% ID
(2cm)
% ID
(1.5cm)
Ducks
Black Scoter >85% >98%
Surf Scoter >75% >98%
White-winged Scoter >75% >98%
Red-breasted Merganser >80% >98%
Long-tailed Duck >85% >95%
Loons
Common Loon >90% >98%
Red-throated Loon >90% >98%
Petrels and Shearwaters
Wilson’s Storm Petrel >75% >85%
Great Shearwater >80% >90%
Cory’s Shearwater >80% >90%
Manx Shearwater >60% >80%
Audubon’s Shearwater >60% >80%
Sooty Shearwater >60% >80%
Jeagers and Skuas
Parasitic Jaeger >85% >95%
Pomarine Jaeger >85% >95%
Species Group / Species % ID
(2cm ) % ID
(1.5cm) Gulls and Terns
Great Black-backed Gull 100% 100%
Lesser Black-backed Gull 100% 100%
Herring Gull >90% >99%
Laughing Gull >85% >95%
Ring-billed Gull >50% >60%
Kittiwake >85% >95%
Bonaparte’s Gull >80% >90%
Caspian Tern >85% >95%
Royal Tern >85% >95%
Common Tern >60% >75%
Roseate Tern >60% >75%
Least Tern >60% >75%
Black Tern >60% >75%
Forster’s Tern >60% >75%
Black Skimmer >95% >95%
Alcids
Common Murre >95% Summer, <50% in Winter >98% Summer, <50% in Winter
Razorbill >90% Summer, <50% in Winter >99% in Summer, <50% in Winter
Dovekie >60% >90%
Atlantic Puffin >60% >90%
Bird Identification Rates: 2 cm v predicted 1.5 cm
• Twin Engine capable of flying less than 140 knots
• Proposed to fly at 1360 ft
– Safety
– Weather
– Resolution
– Coverage
Flight Planning
24
Low confidence – overlapping confidence intervals
High confidence – non-overlapping confidence intervals
Survey Design Confidence in Estimates
Without small confidence intervals it is impossible to assess if environmental change has had a significant impact on a population
- High confidence = small confidence intervals
- Low confidence = large confidence intervals
• OPA=43,650 km2
• 7% Transect of OPA (3073 km2)
584 m x 110 m ground sampling per image
• 10% Grid of WEA + 4 km buffer (128 km2)
330 m x 219 m ground sampling per image
• Rationale for Transect and Grid Design
Survey Design
Survey Design
Survey Design
Project Example: • Calculate the confidence intervals (and associated % coverage) of common scoter
abundance derived from grid and transect survey designs using Markov-Chain Monte Carlo simulations (MCMC) on data collected at Carmarthen Bay.
0
50000
100000
150000
200000
250000
300000
0 1 2 3 4 5 6 7 8 9 10
Sco
ter
spec
ies
esti
ma
te
Coverage (%)
Grid population estimate
Grid lower CL
Grid upper CL
Transect Population
estimateTransect lower CL
Survey Design: Confident Change Detection
Survey Design: Accommodating Glare
• Consideration will be given to:
• Sun angle (time of day / time of year)
• Sea state ( 4 or less aiming for 2 or less)
• Direction of flight in relation to the sun
• Camera angle
• Camera technicians continuously monitor the images collected for quality. And image acquisition will be stopped until suitable conditions occur
• Extra imagery is routinely collected to replace a few expected glint-affected images
Data Output: Geospatial Accuracy • Custom flight planning software pre-
programs the survey transects and grids
• System-specific, aircraft mounted GPS/GNSS systems ensure that surveys are flown as accurately as possible
• Automatic image acquisition over specified locations
• As data capture occurs, GPS data are automatically logged with each exposure including the xyz coordinate and heading of the camera at the point of capture
Data Output
• Identify wildlife to lowest possible taxonomic group
– Birds, marine mammals, turtles, sharks, rays, and fish
• Geo-rectified image snags with associated meta data including height and direction
• Other Anthropogenic Data- Boats
Camera
Surface Resolution
(known)
Bird Resolution
(Calculated from
average size)
Altitude of
Aircraft (known)
Bird Altitude
(calculated)
33
Data Output: Flight Height
• Individual wildlife are geo-
referenced
• Bearing is automatically
determined from head-tail
axis
• Extraction to GIS
• Rose diagrams produced for
defined areas
• Predominant flight/path
direction is detectable 34
Data Output: Flight/Path Direction
35
Data Output: Flight/Path Direction
• Goal Create best value for 3 year data set
• Do Year 1 and/or 2 data confirm historical hot spot and cold spots?
• Stratified by area and/or by target species
• More detailed data–sampling emphasis and/or resolution
Adaptive Methods Consideration
Northwest Atlantic Seabird Catalog by USGS, BOEM, available at NOAA
New England Aquarium using the North Atlantic Right Whale Consortium
MARCO Mid-Atlantic Ocean Data Portal
eBird
Data Sources: Temporal Data
MAR_APR JUL OCT_NOV
0
50
100
150
200
250
300
1 2 3 4 5 6 7 8 9 10 11 12
# an
imal
s
Beaked Whale (Mesoplodon sp.)
Beluga (Delphinapterus leucas)
Blainville's Beaked Whale (Mesoplodon densirostris)
Blue Whale (Balaenoptera musculus)
Bryde's Whale (Balaenoptera brydei)
Cuvier's Beaked Whale (Ziphius cavirostris)
Dwarf Sperm Whale (Kogia sima)
False Killer Whale (Pseudorca crassidens)
Gervais' Beaked Whale (Mesoplodon europaeus)
Killer Whale (Orcinus orca)
Long-finned Pilot Whale (Globicephala melas)
North Atlantic Right Whale (Eubalaena glacialis)
Northern Bottlenose Whale (Hyperoodon ampullatus)
Pygmy or Dwarf Sperm Whale (Kogia sp.)
Pygmy Sperm Whale (Kogia breviceps)
Sei Whale (Balaenoptera borealis)
Sowerby's Beaked Whale (Mesoplodon bidens)
Sperm Whale (Physeter macrocephalus)
True's Beaked Whale (Mesoplodon mirus)
Temporal: Marine Mammals
MAR_APR JUL OCT_NOV
0
500
1000
1500
2000
2500
3000
3500
4000
1 2 3 4 5 6 7 8 9 10 11 12
# an
imal
s
Fin Whale (Balaenoptera physalus)
Humpback Whale (Megaptera
novaeangliae)
Minke Whale (Balaenoptera
acutorostrata)
Pilot Whale (Globicephala sp.)
Marine Mammals
0
5000
10000
15000
20000
Winter
(Dec - Feb)
Spring
(Mar - May)
Summer
(Jun - Aug)
Fall
(Sep - Nov)
Sightings Per Unit Effort
Turtles
MAR MAY NOV
Temporal: eBird
• Population Sensitivity
– ROST
– COSH
– AUSH
Robinson Willmott, J. C., G. Forcey, and A. Kent. 2013. The relative vulnerability of migratory bird species to offshore
wind energy projects on the Atlantic Outer Continental Shelf. OCS Study BOEM 2013-207.
• Collision Sensitivity — ROST — HERG — Jaegers — BLKI
• Displacement Sensitivity
—ROST —ATPU —RAZO —RTLO —NOGA
Sensitive Species
Survey Timings: Winter
0
2
4
6
8
10
Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec
ATPU
0
2
4
6
8
10
12
Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec
RAZO
0
200
400
600
800
Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec
HERG
0 10 20 30 40 50 60 70 80 90 100
Surf Scoter
Black Scoter
Red-breasted Merganser
Common Loon
Northern Fulmar
Sooty Shearwater
Northern Gannet
Red-necked Phalarope
Great Skua
Parasitic Jaeger
Common Murre
Razorbill
Black-legged Kittiwake
Little Gull
Ring-billed Gull
Iceland Gull
Glaucous Gull
Feb_Mar
Survey Timings: Spring
0
1
2
3
4
5
6
7
Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec
ROST
N.B. Also one LETE record in May
0 20 40 60 80 100
Surf Scoter
Black Scoter
Red-throated Loon
Northern Fulmar
Great Shearwater
Manx Shearwater
Wilson's Storm-petrel
Band-rumped Storm-petrel
Double-crested Cormorant
Red-necked Phalarope
Great Skua
Parasitic Jaeger
Atlantic Puffin
Bonaparte's Gull
Ring-billed Gull
Iceland Gull
Glaucous Gull
Least Tern
Common Tern
Eastern Kingbird
Gray Catbird
Apr_May
Survey Timings: Summer
0 20 40 60 80 100
Common Loon
Northern Fulmar
Cory's Shearwater
Great Shearwater
Sooty Shearwater
Manx Shearwater
Audubon's Shearwater
Wilson's Storm-petrel
Leach's Storm-petrel
Band-rumped Storm-petrel
Northern Gannet
Double-crested Cormorant
American Golden Plover
Semipalmated Plover
Sanderling
Red-necked Phalarope
Red Phalarope
South Polar Skua
Pomarine Jaeger
Parasitic Jaeger
Laughing Gull
Ring-billed Gull
Herring Gull
Great Black-backed Gull
Sooty Tern
Bridled Tern
Roseate Tern
Common Tern
Arctic Tern
Barn Swallow
Jul_Aug
0
20
40
60
80
100
Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec
COSH
0
5
10
15
20
Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec
AUSH
Survey Timings: Fall
0 20 40 60 80 100
Canada Goose
Surf Scoter
Long-tailed Duck
Common Loon
Cory's Shearwater
Sooty Shearwater
Audubon's Shearwater
Leach's Storm-petrel
Double-crested Cormorant
Red-necked Phalarope
Great Skua
Pomarine Jaeger
Dovekie
Razorbill
Black-legged Kittiwake
Laughing Gull
Herring Gull
Lesser Black-backed Gull
Common Tern
Pine Siskin
Oct_Nov
0
500
1000
Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec
NOGA
0
10
20
Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec
RTLO
0
50
100
Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec
Jaegers and Skuas
0
200
400
Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec
BLKI
We propose
• WINTER Feb/Mar
• SPRING End Apr/May
• SUMMER End July/Aug
• FALL Oct/Nov
Collaborate with DEC marine mammal surveys
Survey Timing
Data Distribution AMAPPS program NOAA and USFWS
Northwest Atlantic Seabird Catalog
by USGS, BOEM, available at NOAA
North Atlantic Right Whale Consortium
MARCO Mid-Atlantic Data Portal
MA Marine Fisheries
NY DOS Geographic Information Gateway
Large Pelagics Research Center at UMass
• Dive and availability biases
• Beach or terrestrial colony counts
• Higher resolution for shorebirds
• Shark, Harbor Seal and Turtle Tags- tracking receivers
• Thermal surveys
• Other ideas?
Leveraging NYSERDA Data Collection
• Known Wildlife Distributions in OPA
• Approach
– Camera Sensor
– Flight Planning and Survey Design
– Data Output
– Adaptive Methods Consideration
– Survey Timing
• Data Distribution
• Leveraging NYSERDA Data Collection
Discussion