Post on 23-Oct-2020
Geoffroy Lamarche – Shallow Survey 2012
Using remote-sensed data for quantitative shallow water habitat mapping in New Zealand
with substantial contribution from :
Jean-Marie Augustin2, Xavier Lurton2, Vanessa Lucieer3, Scott Nodder1, Arne Pallentin1, Anne-Laure Verdier1
1: NIWA; 2: Ifremer, Brest, France; 3: University of Tasmania, Hobart
Friday 24 February 2012
Geoffroy Lamarche
National Institute of Water and Atmospheric Research
Wellington
Geoffroy Lamarche – Shallow Survey 2012
Outline
I. Habitat Mapping - Rationale
II. The New Zealand Ocean Survey 2020 project
III. Segmentation & classification of biophysical datasets
IV. Quantitative use of Backscatter data
Geoffroy Lamarche – Shallow Survey 2012
What is an Habitat? The natural environment of an organism [Oxford Dic]
Localized surroundings to which an organism, species, or community is specially adapted and which provides for all its needs. [Google]
Geoffroy Lamarche – Shallow Survey 2012
Contribute to the sustainable management of critical ecosystems (Ecosystem-Based Management - EBM);
To support effective management of economic and biological resources;
To support scientific research as a foundation for sustainable management ;
To assess vast remote & isolated regions;
To increase certainty in decision making
Why Habitat Mapping?
http://www.forestandbird.org.nz
Defining the spatial domains of organisms, geology and environmental variables, that together constitute “habitat”
Geoffroy Lamarche – Shallow Survey 2012
C o
n f I d
e n
c e
The Habitat Mapping
Conundrum Can we develop a global quantitative
procedure to routinely and objectively characterize seafloor substrate, habitat and biodiversity
using remotely sensed data ?
Physical surrogates
+
+
=
Geoffroy Lamarche – Shallow Survey 2012
Habitat Mapping in New Zealand
Cook Strait : object-based BS image analysis
OS 2020 National initiative : Coastal
Bay of Island
170E
41S
36S
46S
51S
Subtropical Front
http://bathymetry.co.nz
Geoffroy Lamarche – Shallow Survey 2012
OS 20/20 Bay of Islands
Fate of sediments & pollutants
Conserve and manage sustainably its ocean resources
Involvement of indigenous &
environmental groups.
OS 20/20 is to provide NZ with knowledge of its ocean territory to demonstrate its stewardship
and exercise its sovereign rights
Provide baseline for estimating impacts of uses on ecosystems ;
http://www.os2020.org.nz/
Seabed Mapping
Offshore EM300 Multibeam 50-200 m. 5m grid resolution.
Inner Bay of Islands EM3000D for > 10 m Sidescan in < 10 m Aerial Photographs for Shallow 1m grid resolution.
• 10 classes derived from Backscatter Strength
• Classes used to define Phase 2 sampling plan for Deep Towed
Imaging System (DTIS)
Geoffroy Lamarche – Shallow Survey 2012
Direct sampling: Field teams - intertidal Coring - subtidal (incl by divers) Trawling - subtidal (fish, benthos)
Indirect sampling: Cameras (video/still; DTIS/BUV/Drop) Diver observations Multibeam/side-scan sonar/aerial photography
Sampling habitat & measuring biodiversity
-# taxa -# individuals -diversity indices
Geoffroy Lamarche – Shallow Survey 2012
imaged Holocene sediment to bedrock
→ up to 30 m of sediment
High sedimentation (& gas)
SW NE
Very-high resolution seismic reflection (boomer) profiles
Grain size • Muddy sand dominates the shelf with
increasing mud towards the south • BOI is predominantly sandy mud, with up
to 90% mud in the inlets
Sediments: Carbonate content
• Highest carbonate contents (60-80%) in gravel / very coarse sand in areas of high
backscatter reflectivity.
Biodiversity
Land use
Mean annual sediment loads by land-use Flood events can greatly exceed mean loads
0
50
100
150
200
250
300
Pasture
(Cattle)
Pasture
(sheep)
Pasture
(sub-soil)
Native
(broadleaf)
Kanuka
(scrub)
Pine
(clear-fell)
Se
dim
en
t y
ield
(k
t/y
)
2600000 2605000 2610000 2615000 2620000 2625000 6645000
6650000
6655000
6660000
6665000
6670000
6675000
-31
-30.1
-29.2
-28.3
-27.4
-26.5 C18:0 ? 13 C ‰ C18:0 ? 13 C ‰
3.7
7.5
10
0.8
Mean Annual Discharge (m3/s)
Stable isotopes indicate 3 major inflows with Kerikeri Riv. plume isolated from Waitangi and Kawakawa river plumes
Geoffroy Lamarche – Shallow Survey 2012
Pixel
Objects
*Limited with texture: ** e.g.: polarimetric, entropy, etc
Source: Daniel L. Civco, University of Connecticut
Parameters Pixel Object
Colour
Size -*
Shape -
Neighbors -
Hierarchy -
Sensor Specific** ~
Object-Based Image Analysis vs pixel-based segmentation (the human perception)
Segmentation and Classification
Integration of ecologically-significant biophysical variables to create classes
Lucieer, V.; Lamarche, G., 2011. Continental Shelf Research, 31: 1236-1247.
Geoffroy Lamarche – Shallow Survey 2012
Image Segmentation
• Refers to the process of partitioning an image into multiple homogeneous regions
• Locate objects and boundaries (lines, curves, …) in images
• Spatial homogeneity plays the most important role in segmentation.
• Objects or segments are formed because of their spatial correlation, not just because of their thematic similarity
2D feature space shows
that on Brightness and
Max difference the
classes separate well
Geoffroy Lamarche – Shallow Survey 2012
Classification
• Classes have an identifiable and consistent relationship from a combination of different physical parameters
• Unsupervised classification do not attach meaningful labels to the classes
Need to ground truth the classes
Habitat surrogate (proxy): %Gravel %mud %sand Log of slope
Other possible habitat/biodiversity physical surrogates • % Carbonate • Primary productivity • Seafloor temperature • Sheer bed stress • probability of ground shaking • current velocity •…
Geoffroy Lamarche – Shallow Survey 2012
Membership Result for each class
Uncertainty layer for entire image
Fuzzy C Means
Hard class map of Class Location
Quantifying uncertainty and progressive
transition from one class to the other
Geoffroy Lamarche – Shallow Survey 2012
Validation • Both maps detect continental shelf in water depths < 120 m as one class • Classes 1 & 2 gravel & sand with Class 2 small to moderate-sized bed forms. • Classes 3 and 4 silt and mud • Canyon floors well delineated, reflects bedforms and coarse-grained sediment • Neither approach separate many classes in the SE • 1 dominant class in trough is coherent with homogeneous seabed
Aim: develop a simple robust model that quantifies (parameterises) the angular response of the BS
θ
Modeling the BS Angular Response
Lamarche, G.; Lurton, X.; Verdier, A.-L.; Augustin, J.-M., 2011, Continental Shelf Research, 31: S93-S109.
Backscatter Strength Angular Response
A functional model aimed at:
- Fitting a variety of BS(θ) shapes - Depicting the dominant physical
processes - Quantitative BS description - Avoiding detailed modelling - Robustness and simplicity
The Generic Seafloor Acoustic Backscatter model (GSAB)
θ
BS(θ) = 10 log[ A.exp(-θ²/2B²) + C. cosDθ + E.exp(-θ²/2F²) ]
Geoffroy Lamarche – Shallow Survey 2012
3 physically significant components: Specular – Intermediate – Lambert
A
B
C
D
E
F
BS(θ) = 10 log[ A.exp(-θ²/2B²) + C. cosDθ + E.exp(-θ²/2F²) ]
C = Lambert Law Reference
sediment volume heterogeneities
D = Lambert Law Decrement (=2)
A : Specular Level
high for soft & smooth sediment
B : Specular Lobe width
Linked to seafloor roughness;
E: Transitory Regime Level (dB)
F: Transitory Lobe Width (°)
Backscatter Strength Angular Response
Geoffroy Lamarche – Shallow Survey 2012
BS(q) classification 8 homogeneous reference areas selected from BS level and texture in Cook Strait. e.g., sandwaves, flanks, smooth, roughed, shallow, deep…
Geoffroy Lamarche – Shallow Survey 2012
BS(q) classification
40˚ -40˚
One profile for each 8 areas.
Substrate Characterisation
BS Parameterization (A, B, C,… & BS40°)
Geoffroy Lamarche – Shallow Survey 2012
Classes BS Angular Profiles
Profiles have distinct shapes, relate to the grain size, volume heterogeneity & seafloor roughness.
Classes 1 & 3 ~ sand, higher specular amplitude (class 3) suggests stronger interface roughness.
Class 2 ~ gravel or high volume heterogeneity.
Class 4 ~ mud with underlying sediments
High BS
Low BS
Geoffroy Lamarche – Shallow Survey 2012
Conclusions Biodiversity mapping can be undertaken using biophysical relationship
to create maps of unsampled biodiversity on heterogeneous, difficult to sample features - OS2020 proved a successful integration of remote & direct sampling of biodiversity over a variety of environments
OS2020 showed requirement for continued monitoring to establish baselines, determine rates of change, and improve land-use & offshore resource management practices
Unsupervised classification is suitable to characterise habitats at multiple scales with ability to quantify uncertainties but there is a need to use other surrogates (seafloor velocity, disturbance, primary productivity) & validate classes
Backscatter Strength is a suitable tool to Qualitatively and Quantitatively characterise seafloor substrate but data processing is complex and requires good instrument calibration
Geoffroy Lamarche – Shallow Survey 2012
Geoffroy Lamarche – Shallow Survey 2012
Backscatter Strength (BS) angular response
BS
(d
B)
Mud
-20
-30
Incidence Angle
60° 0 60°
Sand
Gravel -10
Fluid sediments
Specular + volume Rock/coarse sedmts
Interface roughness
A
GR SL
SH
DR
EL
(BS)
TL TL
DT
Geoffroy Lamarche – Shallow Survey 2012
Sandwaves detection
Amplitude 3 - 7 dB
Amplitude < 1 m
Range 46-65°
BS variation is an excellent descriptor of sandwave
Better than bathymetry data (altitude or angle)
The BS variation over sediment-wave cannot be explained by the incidence angle alone it is controled by sediment type variation
Geoffroy Lamarche – Shallow Survey 2012
Habitat Mapping
• Defining the spatial domains of organisms, geology and environmental variables, that together constitute “habitat” from the perceptions of what organisms use as individual species or assemblages;
~5 km ~50 km ~500 km
• The classification and characterization of seabed benthos and substrate;
Snelder et al., 2005
Geoffroy Lamarche – Shallow Survey 2012
Habitat Mapping Programmes Worldwide
Canada’s National Marine Mapping Strategy Marine Biodiversity Hub, Australia Framework for Mapping European Seabed Habitats (MESH) MAREANO programme, Norway Coastal & Marine Ecological Classification Standard (USA) California Seafloor Mapping Program (CSMP)
CERF Habitat Mapping Surveys
~5 km
Tatuteranga Marine Reserve Substrate map