Classification of Tidal Wetland Communities Using Multi-temporal, Single Season

Quickbird ImageryEmily Wilson, Sandy Prisloe, James Hurd & Dan

CivcoCenter for Land Use Education and Research

University of Connecticut

Martha GilmoreDepartment of Earth and Environmental Sciences

Wesleyan University

ASPRS 2006 Reno, NV

© 2006 University of Connecticut 2

Project Participants

• Project Lead and Image Classification

• Collection and Analysis of Field Spectra

• Funding Support and Quickbird Image AcquisitionInstitute for the Application

of Geospatial Technology

© 2006 University of Connecticut 4

The Problem: A Highly Invasive Plant

• Very aggressive• Forms dense

monocultures• Displaces

indigenous vegetation

• Does not support rich mix of wildlife

• Spreads rapidly• Physically

changes marshes

Phragmites australis

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The Problem: A Highly Invasive Plant

1968 1994

Upper Island marsh, Old Lyme, Connecticut

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The Problem: A Highly Invasive Plant

1968 1994

Lord Cove marsh, Lyme, Connecticut

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Phragmites Eradication Efforts

• Connecticut DEP, The Nature Conservancy and others have undergone extreme and costly eradication efforts– Mulching or stomping

- Herbicide application

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Phragmites Eradication Example

Photo courtesy Joel Stocker

Lord Cove

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Phragmites Eradication ExampleTreated and Mulched

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Phragmites Eradication ExampleAfter Treatment

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Phragmites Eradication ExampleAfter Treatment

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Phragmites Eradication ExampleAfter Treatment

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The Problem

• Very little baseline information • No long-term monitoring, especially over large

areas

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The Need to Map and Monitor

• Where has P. australis been eradicated?• How much area has been treated?• Where does P. australis still grow?• Is P. australis reinvading areas?• What other plants can be classified from

imagery?

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High Resolution Imagery

DigitalGlobe QuickBird satellite imagery

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Project Location

Lower Connecticut RiverDrains to Long Island Sound

Lord Cove

Upper Island

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Quickbird Image Acquisition

• 2004– IAGT Ordered QuickBird imagery every 2 weeks from

May to October– Best case would be 13 images– Actually acquired 4 (due to weather conditions and competition)

• 2005– Acquisition extended to 2005 summer season– Collected 3 more images

• 2006– Acquisition extended to 2006 summer season

• Take home message: Satellite image acquisition can be unreliable

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Quickbird Image Acquisition

May 272004

June 22005

172005

July 22004

82003

202004

232005

August

Sept. 122004

BIG HOLE

4 images from 20043 images from 2005Collection continues in 2006

MO

NTH

DAY

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Measuring Spectral Differences

• Species change throughout the growing season

• Each species changes differently• Changes are unique and revealing

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Measuring Spectral Differences

A portable spectrometer has been used to measure the energy reflected from a variety of plant species at different times during the growing season.

May 27, 2004

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Measuring Spectral Differences

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GPS-referenced Field Observations

• Guide classification efforts

• Train image analysts

• Eventual accuracy assessment

S. patensS. alternifloraP. australisT. augustifolia

GPS Legend

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Image Data Preparation: Subset

• Important to isolate only marsh pixels to eliminate confusion

• Use LIDAR data as first cut• Still some confusion

White = UplandGray = WetlandDark Gray = Water

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Image Data Preparation: Subset

• Series of filters and edits to identify final study area

• Subset all imagery to this boundary

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Image Data Preparation

• Select images dates based on spread across growing season (ignore year) and high image quality– June 2, 2005– June 17, 2005– July 20, 2004– Sept. 12, 2004

• Select ratios and calculate for each image date– 4/3 (nir/red) ratio (stretch 0-255)

– 2/1 (green/blue) ratio (stretch 0-255)

– 4/2 (nir/green) ratio (stretch 0-255)

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Land Cover Classification Techniques

• Image Segmentation and Object-Oriented Classification– 1) Segment the image (group similar adjacent

pixels)– 2) Classify segments

• Advantages:– Closer to how we interpret imagery– Each segment has spectral and spatial

attributes

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Image Segmentation and Classification

• Create eCognition project with each ratio for each date along with raw bands from July 20 image

• Experiment and decide on segment size• Write rules based on a priori knowledge

and results from field spectrometry

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Image Segmentation and Classification

Ragged Rock Creek Marsh

LEVEL 4 LEVEL 3 LEVEL 2 LEVEL 1

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Development of Mapping Protocol

For Phrag• Use late

summer image• High 4/3 ratio

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Feature View:Blue areas indicate Phrag areas used in rule

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Development of Mapping Protocol

For Patens• Use mid-July

image• High 2/1 ratio

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Feature View:Blue areas indicate Patens areas used in rule

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Preliminary Results

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Preliminary ResultsTyphaPhragPatens

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Further Work

• Refine unclassified areas• Look more closely into ground data and

more refined rules• Check accuracy • Save hierarchy and apply to other areas

in the lower Connecticut River

Classification of Tidal Wetland Communities Using Multi-temporal, Single Season

Quickbird ImageryEmily Wilson, Sandy Prisloe, James Hurd & Dan

CivcoCenter for Land Use Education and Research

University of Connecticut

Martha GilmoreDepartment of Earth and Environmental Sciences

Wesleyan University

ASPRS 2006 Reno, NV