introduction to wet-areas mapping (wam): creating new and...

Introduction to wet-areas mapping (WAM): creating new and innovative base layers for rural,

municipal and urban planning from digital elevation models (DEMs)

Jae Ogilvie, Charity Mouland, Mark Castonguay, Gustavo Moran, and Paul Arp

CONGRESS FOR SATELLITE SOLUTIONS ENGINEERING AND ENVIRONMENT

Mérida, VenezuelaSeptember 22, 2011

Wet Areas Mapping: The Principle

WAM: a cartographically correct topographic soil wetness index, or depth‐to‐water (DTW) index, to delineate/quantify:

‐ dry spots, moist spots, wet spots ‐ upland/lowland/wetland flow paths and transitions‐ soil type (organic soils to podzols)‐ soil drainage (very poor to excessively well), ‐ vegetation type (xeric to hydric) ‐ extent of flooding and water pooling‐ areas subject to drought

through digital elevation modellingand additional geomatic inputs as needed (e.g., surface images)

Predicted Depth-to-water Surface

DEM surface

Mapped LakesMapped Streams

1. Locate (map) open‐water features across the landscape (streams, shorelines)

2. Infer depth‐to‐water (DTW) from the elevation rise away from the nearest open‐water features

3. This can be done regardless of DEM source, but the precision increases with increasing resolution, and is best with bare‐earth DEMs

Wet Areas Mapping: The Principle

Digital DEM sources for WAM

SRTMhttp://srtm.usgs.gov90 m resolutionglobal, free;data quality generally goodelevations: canopy level

ASTERhttp://asterweb.jpl.nasa.gov30 m resolutionglobal, free;data quality still highly variable;elevations: canopy level

TerraSAR-Xhttp://www.infoterra.de10 m resolution, available for select areas, on demanddata quality goodaffordable at local to regional scaleselevations: bare-ground, through geophysical processing

Airborne LiDARhttp://www.wy.nrcs.usda.gov1 m resolutiondata generation project baseddata quality generally goodexpensive elevations bare-ground to canopy level:point cloud data; waveform data

Digital DEM sources for WAM

WorldView-2

Bare-ground DEM

Worldview 2

versus LiDAR

http://www.digitalglobe.com/downloads/case_studies/Case_Study_WV2_LIDAR_Comparison.pdf

Elevation difference

Cumulative frequency plot of the elevation differences

Digital DEM sources for WAM (rasters, centered on Mérida)

Geophysical interpretationof satellite stereo images

SRTMASTER

0 750 1,500 2,250 3,000375Meters

ASTER0 - 0.1

0.1 - 0.25

0.25 - 0.5

0.5 - 1

0 - 0.1

0.1 - 0.25

0.25 - 0.5

0.5 - 2

Wet Areas Mapping Overlays (Mérida and surroundings)

WAM:

Geophysical processing of satellite image(c/o PhotoSat, at center)

Preceding slide

Mérida airport

0 750 1,500 2,250 3,000375Meters

SRTM0 - 0.1

0.1 - 0.25

0.25 - 0.5

0.5 - 1

0 - 0.1

0.1 - 0.25

0.25 - 0.5

0.5 - 2

WAM:

Geophysical processing of satellite image(c/o PhotoSat, at center)

Wet Areas Mapping Overlays (Mérida and surroundings)

Note: ASTER and SRTM ridges and valleys are in general alignments, or slightly off-set

Mérida airport

Wet Areas Mapping along the Meta River with the SRTM DEM data + Google (Land SAT) images

Google image, hill-shaded with the SRTM DEM data

SRTM DEM corrected based on image-generated hydrography(image delineated rivers and streams)

Wet Areas Mapping along the Meta River

Main flow channel network network displayed on the hill-shaded surface image


Flow channel network extended towards seasonally affected flow initiation thresholds (example: 10 ha)


Cartographic depth-to-water index of DTW <1 m (red shading)along DEM-generated flow-channel network


Close-up of the WAM process, with 100 (drought) & 4 (normal, far right) ha as flow initiation thresholds

Surface image Image-recognized flow channels

DEM extended flow network and associated wet areas

100 ha 4ha


4 ha

1 ha

0.25 ha

Mapping the expansion and

contraction of flow channels

andassociated wet areas according

to weather and season,

by adjusting the flow-initiation threshold

Dryseason

Wetseason

Transitional

Wet Areas Mapping: San Cristóbal Study Area with a World View‐2 DEM sample

Predicted wet areas (blue) + terraced flood plains (light to green) overlying the hill‐shaded 2002 Google image

Wet Areas Mapping:2002 ‐ 2010Landscape change; San Cristóbal Study Area

2002 image 2010 image

2002 Main flow channel2010 Main flow channelFlood plain

2002 image

Wet Areas Mapping: Barcelona, using the free TerraSar‐X DEM sample

0 1,000 2,000 3,000500Meters

WAM0-0.1

0.1-0.25

0.25-0.50

0.5-1.0

Digitized roads

Processing details:

Roads and airport runways were feature‐extracted from ortho‐rectified images and classified by width.

Major roads were raised by 5 m.

Secondary/residential roads were raised by 2.5 m.

The airport was raised by 5 m.

WAM was applied to the infrastructure corrected DEM to approximate proper drainage along all major roads and around airport.

Map reliability (precision)

Using provincial DEMs: generally 40 m, 8 times out of 10

Using bare‐ground LiDAR DEMs: generally 4 m, 8 times out of 10

Management Applications

WAM application, forestry: cutblock lay‐out and access

Then

Road alignmentlocating saddle points

to increase roadbed stability

From rectangular to WAM contoured cutblocks

Now

Wet Areas Mapping, Wetland delineation, with LiDAR Point Cloud Exploitation

Looking at LiDAR-based point cloud data in relation to the DTW index: top and side views

Wet Areas Mapping: Alberta oils sands, Canada; using LiDAR DEMs

Predicted wet areas (blue) and wetland extensions (purple), GPS wetland boundaries (red).

Grey areas: non‐flat areas with DTW> 1m but no significant tree growth

Culverts in proper position and fully functioning

Using LiDAR DEMs for best possible culvert placement, to road washout avoidance;

Automated catchment area delineation above culvert location determines culvert size

WAM: automatically locating road stream crossings and culvert sizing

WAM: coastal flooding impacts on urban infrastructure, using LiDAR DEMs

In summary, WAM can (e.g.)…

provide enhanced information to inventorying land-based water-affected resources: forestry, agriculture, habitats, watersheds and water quality

assist in planning field-based operations, from field reconnaissance to day-to-day operations dealing with soil trafficability and local soil drainage

conditions as these vary with weather and season help to better define areas where roads and trails will have less disturbance impact on water flow across the landscape, and are also lest costly and more easily maintained

allow realistic assessments of hydrological risks regarding the development of new settlements and communities in view of potential flooding and other adaptation needs for climate change

while LiDAR DEMs are preferred, low resolution DEMs and WAMs are valuable for, e.g., region-wide watershed delineations and comprehensive assessments of inland & coastal flooding, slope instabilities, etc.

Already, WAM has…

• been successfully used across Canada by government and industry since 2001, with more than 200,000,000 ha already mapped using provincial DEMs, and about 10,000,000 ha already mapped using LiDAR DEMS;

• received many favorable reports from users regarding time and dollars saved in daily planning and subsequent field operations;

• allowed stakeholders to realistically assess matters of mutual interests, and plan accordingly.

For details, see: http: watershed.for.unb.ca

WAM-based services can be accessed:

by way of bilateral agreements (Carta Intención) between

La Foundación Instituo de Ingenería para Investigación Tecnológico (FIIDT), Venezuela

and the

The Forest Watershed Research Centre at the University of New Brunswick, Canada

with, hopefully, financial support of and in collaboration with

Venezuelan and international partners

(industries, governments, municipalities, universities, NGOs, foundations)

interested in

innovative and geomatically based

land-use planning.

Thank You!

WAM coverage forAtlantic Canada

Fredericton

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