Bathymetry Acquisition Hydro-DEM Synopsis

S PAT I A L LY E N A B L I N G A U S T R A L I A & N E W Z E A L A N D
PROJECT 9.06
| U R B A N D I G I TA L E L E VAT I O N M O D E L L I N G R E P O RT S
Project Leader
Research Team
Dr G. Kernich [email protected], CRC for Spatial Information
Dr N. Quadros, Mr P. Tickle and Ms J. Keysers, CRC for Spatial Information,
[email protected], [email protected] and [email protected]
Project Participants
Sinclair Knight Merz
Australian Dept of the Environment, Geoscience Australia, Qld Dept of Natural Resources & Mines
Objectives
Bathymetry Acquisition To better understand the reasons for near shore bathymetry collection in Australia and ensure that appropriate technologies
are employed to satisfy user needs
Hydro-DEM Synopsis To evaluate the value of using different quality data for the generation of coastal and floodplain inundation modelling
Outcomes
Bathymetry Acquisition Data acquisition parameters which fit the needs of multiple users with different applications were identified. A standard specification for
bathymetry LiDAR acquisition was developed and a multi-sensor bathymetry acquisition strategy suggested.
Hydro-DEM Synopsis The quality of inundation products derived from DEMs vary depending on the complexity of the landscape, the degree of processing and
editing, the interaction between natural and man-made hydrological features, the scale of use, the DEM and hydro-model grid cell sizes and so on. The optimal
solution therefore depends very much on the situation and the specific needs of the user.
Bathymetry Acquisition
Technologies & Strategies
Spectral
Resolution
Radiometric
Resolution
Spatial
Resolution
Swath
Width
Cost
Per...
Cost
(Archive)
Cost
(New)
Metric
Accuracy
ENVISAT MERIS
15
12 bits
300m
1100km
Scene
Mid
N/A
70-225m
MODIS
36
12 bits
250m
2330km
Scene
Low
-
30-50m
LANDSAT7 ETM+
7
8 bits
30m
180km
Scene
Low
N/A
25-250m
EO1 HYPERION
220
12 bits
30m
7.75km
Scene
Mid
Mid
15-25m
ALOS AVNIR-2
4
8 bits
10m
70km
Scene
Low
N/A
20m
SPOT 5
4
8 bits
10m
60km
Scene
User Needs Analysis
IKONOS
4
QUICKBIRD
Airborne LiDAR and maritime vessel multi-beam
& single-beam echo sounders
Ports & Harbours
PLEIADES
11 bits
4
11 bits
4
11 bits
4m
2.6m
2m
To meet the needs of a multiple users with different applications, a new
bathymetry acquisition should be
Ÿ
10m point spacing
Ÿ
50cm vertical accuracy
Ÿ
A large area of mid to south Queensland coast or north-west Western
Australia
Ÿ
Ÿ
Capture features such as shipping channels, ports, harbours and reefs
ArcGIS or ASCII XYZ forma
Bathymetric features of interest per user group
Low
17-23m
Km
Mid
Low
4.5-7.5m
2
Mid
Mid
3.5-6.5m
High
High
3.5-6.5m
11 bits
2m
17.7km
Km 2
AHAB
Chiroptera
Riegl
VQ-820-G
USGS
EAARL-B
Bathy
Bathy
Bathy
Topo-Bathy
Topo-Bathy
Bathy
Bathy/Topo-Bathy
Topo-Bathy
Topo-Bathy
Topo-Bathy
Australia
2011
Yes
Green 532nm
Canada
2010
No
Green 532nm
Infra-Red
1064nm
Canada
2005
No
Green 532nm
Infra-Red
1064nm
Canada
2011
Yes
Green 532nm
Infra-Red
1064nm
Canada
2011
Yes
Green 532nm
Sweden
2009
No
Green 532nm
Infra-Red
1064nm
Sweden
2013
Yes
Green 532nm x 2
(Deep and Shallow)
Infra-Red 1064nm
Sweden
2012
Yes
Green 532nm
Infra-Red
1064nm
Austria
2011
Yes
Green 532nm
USA
2012
Yes
Green 532nm
Rectilinear
Fwd up to 80
Circular Arc
Fwd 22 0
Circular Arc
Fwd 200
Elliptic Arc
Fwd 70
Elliptic Arc
Fwd 200
Oscillating
Mirror
4mJ
Oscillating
Mirror
4mJ
Oscillating
Mirror
3mJ
Elliptical
Fwd and Aft 14 0
Sideways 20 0
Palmer Scanner
3mJ
Oscillating
Mirror
0.1mJ
Elliptical
Fwd and Aft 140
Sideways 20 0
Palmer Scanner
Elliptic Arc
Fwd or Aft 200
Oscillating
Mirror
7mJ
Circular
Fwd and Aft
200
Rotating Prisms
3mJ Deep (D)
0.1mJ Shallow (S)
0.1 mJ
Rotating MultiFacet Mirror
0.02mJ
Pulse Duration
6.5ns
5ns
5ns
2.0-2.2ns
7ns
4ns
4ns
1.2ns
Measurement
Frequency
1.5kHz@532
3kHz@532
1kHz@532
10kHz@532
70kHz@1064
33-70kHz
@532
4kHz@532
128kHz@1064
36kHz@532
400kHz@1064
Up to
512kHz@532
15kHz or 30kHz
532nm Nominal
Footprint Diameter
@ Water Surface
3m
2m
2m
2.4m
0.3-0.6m @
AGL Below
6m
4ns (D)
2.5ns (S)
10kHz@532 (D)
35kHz@532 (S)
400kHz@1064
3m (D)
1.5m (S)
1.5m
0.6m @
AGL Below
0.3m per
beamlet, 1.6m
apart
400-700m
AGL
585m@8x5m
360m@5x5m
[email protected].
5m
2x2m 8x5m
300-400m
AGL
160m@2x2m
300m@3x3m
300-400m
AGL
60m@2x2m
130m@3x3m
400-800m AGL
300-600m
AGL
up to 0.93 x
AGL
400-1000m AGL
250-600m AGL
300m @400m
AGL
Nominal 300m
AGL
230m @300m
AGL
2x2m 5x5m
0.2x0.2m 0.8x0.8m
1.5 x 1.5m
~80m
2.5-3 x Secchi
depth
290m
@400m AGL
730m
@1000m AGL
1.7x1.7 - 3.3x3.3m
(D)
0.4x0.4 - 0.8x0.8m
(S)
~50m
2-3 x Secchi depth
Nominal 600m
AGL
400m
2x2m 5x5m
250-500m
AGL
160m-260m
@400m AGL
100m
@250m AGL
0.5x0.5m 3.5x3.5m
~50m
~50m
~60m
~20m
~50m
~20m
~10m
2-2.5 x Secchi
2-2.5 x Secchi
2.5-3 x Secchi
1 x Secchi
2-3 x Secchi
1 x Secchi depth
1 x Secchi
depth
depth
depth
depth
depth
depth
The minimum water depth of most systems has improved substantially in recent years. The minimum depth is now less than 0.2m for most sensors.
All LiDAR systems have the capability to meet the required IHO accuracy standards. Vertical accuracy is dependent on survey design and processing.
Minimum Depth
Vertical Accuracy
Mid
2
8
AHAB
HawkEye III
Maximum Depth
Km
WORLDVIEW2
AHAB
HawkEye IIB
0.4x0.4m 1x1m
15m
Km
Optech ALTM
Aquarius
291m
@400m AGL
582m
@800m AGL
2x2m (Deep)
0.7x0.7m
(Shallow)
Low
15.5km
Optech
CZMIL
(1/e²)
Nominal Flying
Height
Swath Width
(as a function of
point spacing or
altitude)
Typical Bathymetric
Point Spacings
Low
2
2m
Scan Pattern Diagram
(Not to Scale)
Wreck
Km
11 bits
Optech
SHOALS
1000T
Laser Energy Per
Pulse (Green 532nm)
20km
15-25m
4
Optech
SHOALS
3000
Scan Shape
Scan Direction and
Angle From Nadir
Scan Method
18km
High
GEOEYE1
Fugro LADS
Mk3
Typical Sensor
Environment
Origin
Year Released
Still in Production
Laser Wavelength/s
11.3km
High
2
0.4x0.4m 1 x 1m
Elliptic Arc
Fwd 50
Sideways 22 0
Oscillating
Mirror
0.4mJ
0.13mJ per
beam
0.85ns
The User Needs Analysis
and Technologies &
Strategies research are
used to inform a strategy
for collecting bathymetry
over large, complex,
shallow water areas. A
multi-sensor acquisition
strategy is recommended
for cost-effective, large
area, near-shore
bathymetry acquisition.
~25m
1.5-2.5 x Secchi
depth
Bathy and topo-bathy LiDAR system parameter comparison
Hydro-DEM Synopsis
Purpose: Developing Hydro-DEMs is costly. This research reviewed how
different levels of processing meet specific user needs, to guide future
investment in standardised elevation products. Three research reports were
produced from which a number of conclusions may be drawn.
Conclusion: Local
interactions between the
natural and built environment
should be considered before
investing in the additional
costs of a Hydro-DEM or the
improved ground
classification accuracy of
CL3 (classification level 3)
LiDAR data.
Regular (LiDAR) DEM
Levee
Bank
Bathtub inundation fills all basins regardless of connectivity.
Sea
Data does not
comprise existing
culvert
Sink
Hydro-DEM (Hydro-enforced and conditioned DEM)
Levee
Bank
Bathtub inundation only fills basins connected to the sea.
Sea
Hydro-conditioned
i.e. sink filled
Hydro-enforced
i.e. culvert for
connectivity
Scale of Use
LiDAR Classification
Type of DEM
Type of
Level
modelling
Sub-LGA
CL3
Hydro-DEM + Supplementary Hydro-modelling
engineering data
LGA
CL3
Hydro-DEM
Hydro-modelling
Catchment &
CL3
Hydro-conditioned only
Bathtub or
State wide
Hydro-modelling
Regional &
CL3
Regular DEM
Bathtub
CL2
Regular DEM
Bathtub
State wide
Conclusion: Semi-automated (ie
with manual improvement)
Hydro-DEM generation methods
are necessary to reliably model
the stream network in low relief
landscapes such as floodplains.
Conclusion: Hydro-DEMs (for coastal inundation modelling) are likely to provide the greatest
benefit when used at the sub-Local Government Area (LGA) scale with hydro-modelling.
Conclusion: Where wave setup is likely to be a significant component
of storm tide, the use of high resolution LiDAR bathymetry is beneficial
to the accuracy of results
Automated Hydro-DEM generation
Semi-automated Hydro-DEM generation
Summary: The optimal solution, in terms of
Ÿ quality of LiDAR classification (CL2 or CL3)
Ÿ type of DEM (regular, auto/semi-auto Hydro-DEM)
Ÿ type of modelling (bathtub or hydro)
Ÿ DEM resolution (2m, 10m, 20m), etc
depends on the situation. From the conclusions, investment
should be assessed on a case by case basis.

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