US Army Corps of EngineersBUILDING STRONG®

Remote Sensing for Coastal Applications: Implications for Ecosystem Services

Molly ReifUSAE Research & Development CenterEnvironmental LaboratoryJoint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX), Kiln, MS

ACES December 2010

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USACE Navy

Operations

Coastal Measurements& Data Usage

Sensors & Systems NOAA

Technology Evolution

JALBTCX

Joint Airborne Lidar Bathymetry Technical Center of eXpertise

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•Funded by HQ• Initiated in FY2004•Collect lidar elevation and imagery to support regional sediment management/navigation

•Focus on sandy shorelines•5-year national cycle

USACE National Coastal Mapping Program (NCMP)

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CASI-1500Operator Console

SHOALS-3000Operator Console

Bottom Aircraft Port

Optech SHOALS Integrated Laser

SystemDuncanTech-4000

RGB camera Itres CASI-1500 Hyperspectral

Imager

System III Specifications3,000 Hz Pulse Rate (hydro)20,000 Hz Pulse Rate (topo)

RGB Digital camera (~20 cm pixel)CASI-1500 Hyperspectral Imager

1500 cross-track pixels380 – 1050 nm wavelength

1 m pixel w/ 36 spectral bands

CHARTS

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Bathymetric and Topographic lidarTopo 1 m postings, 500 m onshore, 200%Bathy 5 m postings, 1000 m offshoreGeographic coordinatesNAVD88 vertical datum

NCMP – Collection Scheme

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2004Post-hurricane 20042005Post-hurricane 20052006-2008Post-hurricane 20082009-2010

USACE NCMP Surveys and Products

Available data products:• ASCII xyz• RGB mosaics• Zero contour• 1-m bathy/topo DEMs• LAS format topo• 1-m bathy/topo bare

earth DEMs• Hyperspectral mosaics• Laser reflectance• Basic landcover

classification

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USACE NCMP Products

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EL and JALBTCX

EL has teamed up with JALBTCX to assist with the development and expansion of environmental data products

GOAL: identify/expand environmental data products, utilizing (1) imagery resources of JALBTCX and (2) environmental expertise in EL to address environmental/geospatial needs of the coastal districts.

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Ecosystem Restoration

Environmental Characterization

Wetlands

Navigation Dredging

Natural Resource Management

Invasive Species

Endangered Species

EL Research Focus Areas

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• MISSION: Identification, mapping, and modeling of environmental conditions in support of diverse military and civil requirements. Development of environmental sensing, characterization, and monitoring capabilities necessary to quantify environmental site conditions. Model development for the prediction and visualization of dynamic environmental characteristics for civil and military applications.

Environmental Systems Branch

350 400 450 500 550 600 650

10-3

10-2

Wavelength (nm)

Upw

ellin

g to

Dow

nwel

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io

Upwelling to Downwelling Ratio Interpolation

SM2SM3BAYN01BAY01FREDA01FREDA02FREDA03FREDA04FREDA05FREDA06FREDA07

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Geospatial Data Analysis Facility

FOCUS: Application of Geospatial Technologies TowardCivil and Military Environmental Applications

• Custom Geospatial Model Development• ESRI Model Builder Expertise

• Image Processing and Analysis• Unclassified to Top-Secret• Multispectral and Hyperspectral Platforms• Active and Passive Systems

• Custom Database Development• SDSFIE Experts

• Serving Geospatial Data Via Web Interface• Improvised Explosive Device Defeat Organization (SIPRNET)

• Development of Innovative Applications of Combined Lidar and Hyperspectral Imagery

• CHARTS system

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Wetland Environmental Technologies Research Facility (WETRF)

FOCUS: Application of geospatial technologies to address issues of specific concern to coastal Louisiana and northern Gulf of Mexico wetlands

Scope► Wetland science data integration ► Geospatial analyses

Impact ► Informs coastal restoration and protection planning and

management

Capabilities► Expert technical staff stationed at LSU campus► Relationship with USGS NWRC and LA OCPR► Interdisciplinary team

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Objective

• Target features spectrally with hyperspectral and structurallywith lidar through image fusion

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Considerations for Ecosystem Services

• Remote sensing can provide baseline data for assessing trends and conditions in ecosystem services

• Way to link ecosystem type/condition with service

• Spatially explicit data have proven useful for estimating values and associated changes in services

• Direct input into ecological models; proxy for complex ecosystem functions

• Image fusion provides way to analyze two aspects of ecosystem components at once: structural (canopy characteristics, diversity, volume) + thematic (type, condition)

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Landuse/Landcover and Species Composition

• Landuse/landcover, Species Composition/Distribution, Habitat/ Biodiversity Mapping and Species Richness• basic groups or categories of landcover• specific plant species or species assemblages/groups• critical habitats using standard classification systems• link landcover with value

Portsmouth Harbor, New Hampshire. (a) True color image extracted from

hyperspectral mosaic. (b) Basic image classification.

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Landuse/Landcover and Species Composition

Hyperspectral

Lidar

Combined

Wavelength (nm)500 1000 1500 2000 2500

Ref

lect

ance

(%)

0

5

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30

Chust, G. et al 2008. Coastal and estuarine habitat mapping, using lidar height and intensity and multi-spectral imagery. Estuarine, Coastal and Shelf Science. 78:633-643.

Coastal Habitats - Spain Barrier Island Habitats – Horn Island

Lucas and Carter. 2009. Decadal Changes in Habitat-Type Coverage on Horn Island, Mississippi, USA. Journal of Coastal Research, In Press.

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2005 2006 2007

Lidar

Imagery

Land Cover

Change Detection

• Habitat degradation, fragmentation, and loss – value change estimation

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Invasive Species Detection

• Mapping Invasive and Indicator Species• Spectrally and structurally target species of interest• Emphasize changes in composition, structure and function in ecosystems

caused by invasives

Common Reed

Gilmore, M.S. et al. 2008. Integrating multi-temporal spectral and structural information to map wetland vegetation in a lower Connecticut River tidal marsh. Remote Sensing of Environment. 112:4048-4060.

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Wetlands and Beach Characterization

• Mapping Wetland Habitats and Beach Morphology• Spectrally and structurally target wetland species (distribution and condition)• Emphasize species pattern characterization and zonation related to elevation

gradients• Characterize erosion/sedimentation and beach types for monitoring

Deronde, B. et al. 2006. Use of airborne hyperspectral data and laserscan data to study beach morphodynamics along the Belgian coast. Journal of Coastal Research. 22(5):1108-1117.

Sadro, S. et al. 2007. Characterizing patterns of plant distribution in a southern California salt marsh using remotely sensed topographic and hyperspectral data and local tidal fluctuations. Remote Sensing of Environment. 110:226-239.

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Forest Characterization and Metrics

• Forest/Woodland Structural Characterization and Metrics• Structure: canopy height, density, crown size/shape• Metrics: above-ground biomass, basal area, dbh, volume, quadratic mean

stem diameter, and leaf area index• Forest-related applications: fire fuel studies, etc.

Above Ground Biomass

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Ecosystem Characterization

• Mapping ecosystem characteristics • Identify unique characteristics in landscape parameters/attributes

• Model habitat for invasive/threatened/endangered species and restoration/conservation

• Model habitat changes to examine trade-offs

Ustin, S.L. and Hestir, E.L. Hyperspectral & Lidar Sensing of the Delta. (presentation). Center for Spatial Technologies & Remote Sensing (CSTARS). UC Davis.

Current DistributionPotential Distribution

Potential habitat for invasive species (Lepidium)

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Discrimination of Submerged Aquatic Vegetation Species

Purpose: Evaluate and demonstrate the use of fused airborne hyperspectral and bathymetric lidar data to detect and discriminate species of estuarine SAV and macroalgae in two representative small-craft dredged harbors

Phinn, S. et al 2008. Mapping seagrass species, cover and biomass in shallow waters: An assessment of satellite multi-spectral and airborne hyper-spectral imaging systems in Moreton Bay (Australia). Remote Sensing of Environment. 112:3413-3425.

Spectral seafloor reflectance

Lidar seafloor reflectance

Seafloor classification

Map

Wavelength (nm)

Refle

ctan

ce

ASD measurements of SAVs in Plymouth Harbor and Buttermilk Bay, MA., 13 July 2010

measured with artificial illumination (ASD ProLamp)

400 450 500 550 600 650 700 750 800 850 9000

0.15

0.3

0.45

0.6

0.75

0.9 Zostera (Plymouth)RockweedGreen Filamentous algaeRed epiphytic macroalgaeLeafy macroalgaeUlvaZostera w/ heavy epi."pink leaf", ButtermilkCodiumGrosalus"Portforia", branching macro.Zostera w/ heavy epi(2)

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Heavy-metal Stamp Sands Migration in Lake Superior

Purpose: Classify submersed lake bottom surfaces using hyperspectral and lidar bottom reflectance. Map stamp sands distribution and estimate movement and loss of stamp sands to lake.

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Limitations/Challenges

• System trade-offs (spatial vs. spectral resolution)

• Lack of temporal frequency for change detection

• Unknown accuracy and validation

• Ground truth needed for processing and interpretation

• Lack of data continuity makes data comparison difficult

• Weather and other factors affect aerial survey capabilities and image quality

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Questions?Molly ReifMolly.k.Reif@usace.army.milJALBTCXwww.jalbtcx.orgELhttp://el.erdc.usace.army.mil/