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CCFFR-2012 Society for Canadian Limnologists:

Science for Wetland Policy and Management

LiDAR-BASED DELINEATION OF WETLAND BORDERS

Jae Ogilvie, Hua Kim Wen, and Paul A. ArpDepartment of Forestry and Environmental Management, University of New

Brunswick, NB. January 5-7, 2012. Moncton, NB

AbstractThis presentation introduces a GIS-based method designed to sharpen the delineation ofwetland borders. This method utilizes LiDAR point-cloud data (1m resolution) in theESRI environment for systematic digital representations of bare-ground elevation, slope,mean of the standard deviation slope within a 20 m radius, vegetation height above bareground and depth-to-water (DTW).The criteria for an automatic delineation of wetlands borders are set as follows: DTW <1m, standard deviation of slope within a 20 m radius < 0.1, and vegetation height < 2 m.These criteria delineate GPS-tracked wetland borders within 4 m 8 times out of 10,conform well to high-resolution surface images, and tend to be more consistent in thisregard than image delineated wetland borders.Once the various LiDAR derived data layers are assembled, the results can be furtherscrutinized through image overlay and by way of line scanning, to obtain a vertical viewof the upland-wetland- wetland upland transitions.Applications of this methodology within the context of rural and urban development andrelated wetland conservation planning are also discussed.

Edited from: http://www.dot.state.oh.us/Divisions/ProdMgt/Aerial/Pages/LiDARBasicS.aspx

LiDAR

Distance from laser to ground and back again:

Determined as laser-pulse travel time taken between emission and return to the air-borne pulse sensor

Laser pulse emission rate: up to 500,000 per second

Elevation:

flying height and position of the aircraft are used to determine the location and elevation of the reflecting surfaces (roofs, leaves, ground, etc).

Point cloud data

Edited from: http://www.dot.state.oh.us/Divisions/ProdMgt/Aerial/Pages/LiDARBasicS.aspx

LiDAR Benefits

Much improved slope, flow channel, wet-areas and wetland mapping

Leading innovations towards precision forestry , agriculture and wetland conservation

Towards single-tree forest inventory and detailed vegetation classification

Many applications in natural resource management , from field operations to policy formulations

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Wet Areas or depth-to-water mapping: the concept

Cartographic depth-to-water (DTW)

DEM surface

Flow Channels

1. Prepare bare-ground DEM surface from LiDAR data (last returns)2. Predict locations of stream channels; decide on flow initiation area (e.g. 4 ha)3. Use the wet-areas delineation algorithms to determine the cartographic depth-to-water index (DTW)

across the landscape, using all flow channels and shorelines for the DTW = 0 reference4. Subtract DTW from DEM to get the cartographically referenced water table elevation5. Overlay the first LiDAR returns to obtain vegetation height.

Vegetation height

Hydrological risk show case: Grand Bay NB, Highway 7, LiDAR bare-ground DEM, hill-shaded

15 m drop

LiDAR bare-ground DEM, hill-shaded + cartographic depth-to-water (DTW) 0-1m

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LiDAR bare-ground DEM, hill-shaded + cartographic depth-to-water (DTW) 0-1m+ average tree height (moving average per 20 m circle) , with 2m contours

Focusing on the wetland: DEM-base slope derivation plus tree height (2 m intervals) + DTW (0 – 1 m)

Beaverdam

Cedar

Cedar

Cedar Cedar

Alder

Larch

Black spruce(raised bog)

FirSpruce

FirSpruce

FirSpruce

FirSpruce

FirSpruce

Using WAM: delineating watershed border (left, yellow line); flood risk mapping using the filled and unfilled DEM; watershed area combined with ppt during storm events determines max flow rate at culvert location, and matches that with existing or contemplated culvert capacity .

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0 40 80 120

Nearest distance between GPS track and selected DTW contour or air-photo wetland border, in m

0

20

40

60

80

100

Con

form

ance

(%)

Probability of wetland border 'x' meters away from DTW=0.5m contour

LiDAR-WAMAir-photo

Prov. DEM WAMUsing provincial DEMs:

generally ± 40 m, 8 times out of 10

Using bare-ground LiDAR DEMs:

generally ± 4 m, 8 times out of 10

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Another development example

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Wet areas mapping: DTW according to municipal drainage infrastructure (blue shading)

460

480

500

520

540

Ele

va

tio

n (

m)

460

480

500

520

540

0.0 0.2 0.4 0.6 0.8 1.0

Ele

va

tio

n (

m)

NormalizedDistance

9113m

9472m

10P110P2

10P310P4

10P5 10P6 10P710P8

10P9 10P10

10P11 10P1210P13 10P14

10-1

Road 1AP

Road 1TRAIL

470

480

490

500

Ele

va

tio

n (

m)

470

480

490

500

0.0 0.2 0.4 0.6 0.8 1.0

Ele

va

tio

n (

m)

Normalized Distance

7174m

7115m

SP15SP2 SP3 SP4 SP5 SP7SP6 SP8 SP9 SP10

SP11SP12 SP13SP1 SP14

S1S3S2 S4 S5 S6 S7 S9S8

Road 3AP

Road 3TRAIL

Using TRAIL to optimize proposed forest road locations (black)

Alternative

Alternative

Proposed

Proposed

Wet-areas mapping, across the maritimes region

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New Brunswick:

Coastal floodingand cliff erosion risk map

Risk levels:low (green), high (red)

Sackville, NB – Hillshade of LiDAR DEM (1m Resolution)

Sackville, NB –LiDAR DEM (1m Resolution)Digitized Mapped Water & Prov. Stream Network

Sackville, NB –LiDAR DEM (1m Resolution)Drainage Ditches, Breaches, Dykes & Municipal Infrastructure

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Sackville, NB –LiDAR DEM (1m Resolution)Wet-Areas-Map & Flood Potential

+7.78m

+8.03m

+6.88m+7.16m

+7.13m

+8.81m

+5.17m

+9.09m

Sackville, NB –LiDAR DEM (1m Resolution)Trans-Canada Highway Potential Flooding – Tantramar Marsh Area

Inland + coastal flooding, with outline of the Saxby Gale surge

Tantramar Marsh: Coastal flooding

Moncton LiDAR DEM + prov. water atlas + 0-7 m coastal flood+ 0-1 m wet-areas next to flow channels and shorelines,

with storm-water management

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Moncton LiDAR DEM + prov. water atlas + 0-7 m coastal flood+ 0-1 m wet-areas next to flow channels and shorelines,

no storm-water drainage

St. Stephen: flooding Dec. 13., 2010, centered on Charlotte Mall

Milltown Boulevard, coastal flooding (red)

Charlotte Mall,Irving Gas Station

0

100

200

300

400

500

600

0 1 2 3 4 5Depth-to-water (m) associated with flood claim locations

Frequency of NB flood claims, December 2010

ETF DTW project

Pipeline

Northwest

Containmentberms

Oil retrieval:Temporary road

with two tanks to retrieve spilled oil

(drum storage)

Temporary road with two tanks

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Spill source.

Oil spill: extent controlled by (i) hydraulic gradients (white contour lines), (ii) amount of water flow (broad arrows, proportional to upslope area), (iii) natural blocks (beaver dams), (iv) presence of water: oil floats and backs up towards shallow areas with little flow. (v) Shown: hill-shaded DEM; DTW (0 25 cm contour lines <1m with a 4 ha flow initiation threshold

Block

Outlook. LiDAR-based wetland delineation leads to:

…improved field reconnaissance and detailed feature delineations;

…better and more informed wetland conservation practices;

…insightful rural, urban and industrial wetland planning.

The wetland data layers so generated are:

… cartographically correct and numerically stable (+/- 4 m, eight times out of ten);

… cut across scales, from small to regions;

… provide many high-resolution dimensions for wetland risk assessments and related functional a

… are complementary to other geospatial data layers;

… facilitate communications, and promote wetland impact awareness, from private to regulatory;

…require ground work for final adjustments and legal verifications.

Many thanks to

Lee Swanson Robert Hughes Nelda Craig Lori MoffatSabine DietzNB Env.NB ETFRACEMODTOASRD

Calgary, October 2011