L. Guild1, R. Armstrong2, B. Lobitz3, J. Goodman2, F. Gilbes2, R. Berthold1, J. Torres4, Y. Detres2, C. Zayas2, S. Williams2, O. Tzadik2, and J. Kerr5

CollaboratorsAVIRIS Team - JPL, Airborne Sensor Facility - Ames, Fireball Technology

Funding NASA Interdisciplinary Research in Earth Science NASA Ocean Biology and Biogeochemistry Program

AbstractNASA’s Twin Otter aircraft and imaging sensors have been used to fly over ongoing coral reef research sites in Southwestern Puerto Rico to collect high resolution imagery to support coral reef ecosystem research. The goal is to better understand how light scatters and reflects in shallow aquatic ecosystems. These results will lead to the optimization of current and future remote sensing sensors and data for ecosystem research in the coastal zone. Specifically, this airborne capability addresses the use of remote sensing and field data to interpret reef habitat variability and biodiversity in sites experiencing bleaching, disease, and intense wave action from hurricanes that may become more frequent due to climate change. The airborne sensors consist of a high resolution digital camera system (DCS, NASA Ames Airborne Sensor Facility) and the Airborne Visible Infrared Imaging Spectrometer (AVIRIS, NASA Jet Propulsion Laboratory). The project began with the Caribbean August/September 2005 coral reef bleaching event and a subsequent airborne mission in December 2005 over Puerto Rico and the U.S. Virgin Islands. This research focuses on the remote sensing data collected over Puerto Rico following the bleaching event. After AVIRIS preprocessing, two routes were followed to yield benthic-cover images: 1) an analytical inversion model and spectral unmixing and 2) Hydrolight model runs. Hydrolight results were benthic composition images. Field measurements of benthic types including spectral properties and species composition are integrated with the AVIRIS data to interpret coral reef ecosystem biodiversity. Science objectives for this study included using AVIRIS data and field measurements to assess reef ecosystem community structure following the 2005 coral bleaching event, as well as improve the interpretation of reef habitat variability and biodiversity from imaging spectroscopy (hyperspectral) data related to algorithms that could be used for future HyspIRI data.

Field Measurements• Reef benthic type spectra• Photogrids• GPS• Spectra of calibration targets• Aeronet station: aerosol

optical depth• Water optical profiler

– Upwelling radiance, Lu– Downwelling irradiance,

Ed– Surface Ed, Es

Coral RubbleCoral Rubble

Montastraea annularisMontastraea annularis Siderastrea sidereaSiderastrea siderea Porites spp.Porites spp.

Acropora cervicornisAcropora cervicornis

Thalassia testudinumThalassia testudinumDictyotaDictyota spp. spp.

Coral Reef Ecosystem Benthic Components

Acropora palmataAcropora palmata

GorgoniansGorgonians

Field Spectra

AVIRIS (Airborne Visible Infrared Imaging Spectrometer)• Operated by NASA Jet Propulsion Lab• NASA Wallops Twin Otter• 224 contiguous spectral channels (370-2500 nm)• Visible range: 410-700 nm (31 bands)• 10 nm nominal channel bandwidth• High signal to noise ratio• Altitude: ~3.5 km (Twin Otter)• AVIRIS spatial resolution: ~3m (Twin Otter)

Digital Camera Systems (DCSs) on low altitude aircraft• Cirrus: Operated by UC Santa Cruz Airborne Sensor Facility, NASA

Ames• Kodak: Operated by NASA Ames and Fireball Information

Technologies• Spatial resolution: 30cm at 6000ft

NOAA’s 4-m LiDAR bathymetry acquired in SW Puerto Rico in 2006-07

Airborne Data

AVIRIS Dec 2005, Mosaic of La Parguera, PR

3-m spatial resolution

InversionModel

Spectral Input Parameters

Aquatic Absorption Properties

Generic Bottom Reflectance

Image Preprocessing

Correct Stray Light Anomaly

Hedley Glint Removal

Tafkaa Atmospheric Correction

Raw AVIRIS Imagery

Image Geometry

Explicit pixel by pixel subsurface angles

View (AVIRIS) Illumination (solar)

Inversion Output

Water Properties

Bathymetry

Bottom Albedo (550 nm)

Inversion Model and Unmixing Approach

ForwardModel

Preprocessed AVIRIS Imagery

Spectral Input Parameters

Aquatic Absorption Properties

Generic Bottom ReflectanceImage Geometry

Explicit pixel by pixel subsurface angles

View (AVIRIS) Illumination (solar)

Inversion Output

Water Properties

Bathymetry

UnmixingModel

Hidden 0

0.1

0.2

0.3

0.4

0.5

400 500 600 700Wavelength, nm

Ref

lect

ance Sand

Algae

Coral

Spectral Endmembers

Unmixing Model

The first step of the image preprocessing is suppression of the near-infrared glow (i.e., anomalously large values) in low-light AVIRIS 2004 and 2005 imagery. This glow was caused by stray- light leakage following an upgrade to the instrument prior to the 2004 flight season. It is suppressed by calculating a correction based on the glow’s cross track profile and the difference between the central stripe of "good" data and the adjacent incorrect pixel values that include the contribution from the stray-light (Lobitz et al. 2009).

The second preprocessing step is atmospheric correction, performed using Tafkaa, a Naval Research Laboratory algorithm designed to address the confounding variables associated with shallow aquatic applications (Gao et al. 2000, Montes et al. 2003, Montes et al. 2001). Details of the atmospheric correction method used can be found in Lobitz et al. (2009).

The third preprocessing step, a spectral normalizing procedure based on Hedley et al.'s (2005) variation of Hochberg et al.'s (2003) method was used to reduce the effects of sun glint (i.e., specular reflection from the water surface).

Radiative Transfer Modeling Approach

Imaging Spectroscopy, Spectral Analysis, and Radiative Transfer Modeling in Support of Coral Reef Ecosystem Biodiversity Research for Coral Patch Reefs in Puerto Rico

A Hydrolight table-look-up procedure was developed using the expected domain of water components, depths, and field-measured benthic spectra. A large number of Hydrolight model outputs over the expected domain of water quality parameters (CDOM, chlorophyll concentration, minerals), spectral mixtures of coral, sand, and submerged aquatic vegetation (See field spectra graph), and depths were tabulated. Those results were then searched to find the best match to the pre-processed AVIRIS reflectance data.

The differences between the results for the two methods (inversion model and unmixing approach and Hydrolight radiative transfer modeling approach) for the three components (coral, SAV, and sand) were then examined; however, the inversion/unmixing approach included a shade component (scaling parameter), so the mixture types were not the identical. There is good agreement of spatial benthic structure between the two approaches. San Cristobal patch reef, La Parguera

Assessment of Inversion and Hydrolight Modeling Approaches

Summary• Based on field observations and knowledge of the areas, these

results overestimate the SAV component, overestimate the coral component slightly, and underestimate the sand component

• The interpretation of the benthic surface is complicated by the heterogeneous configuration of surface features resulting from the assortment of surface elements and their morphology, spatial arrangement, and mutual shading

• Substantial image preprocessing may have affected the modeling results

Spectra normalized to unity at 550nm show differences in spectral shape between benthic cover types, e.g., live coral has a broad peak between green and red wavelength and most features show a chlorophyll absorption feature at 680nm.

AVIRIS Imagery

AVIRIS Data Preprocessing

Preprocessed AVIRIS Image

Inversion and Unmixing Output Hydrolight Transformation Output

http://earthscience.arc.nasa.gov/sge/coral-health

AVIRIS ~3m res.DCS 30cm res.

1NASA Ames Research Center, Moffett Field, CA 94035, USA, 2University of Puerto Rico at Mayagüez (UPRM), Mayagüez, PR 00681, USA, 3University Corporation at Monterey Bay, NASA Ames Research Center, Moffett Field, CA 94035, USA4NASA Postdoctoral Program, NASA Ames Research Center, Moffett Field, CA 94035, USA, 5Nova Southeastern University, Dania Beach, FL, 33004, USA

Following image preprocessing corrections, a semi-analytical inversion model is used to retrieve estimates of bathymetry and water properties from measured surface remote sensing reflectance to correct for water column effects in the imagery. Aquatic absorption properties are a combination of absorption properties of pure water and empirical spectra derived from field data and Hydrolight runs (Lee et al. 1998, 1999). The generic bottom reflectance used in the model is an average sand spectrum from the study area. The Inversion Model is applied to derive water properties, bathymetry, and bottom albedo.

We then proceeded with defining spectral endmembers from measured field data and performed the benthic classification using unmixing techniques (Goodman and Ustin 2007, Goodman 2004).

Generic spectral endmembers of coral, sand, and algae are used together with the inversion model outputs (water properties, bathymetry, and bottom albedo) as well as the spectral input parameters and image geometry in the Forward Model. The next step is to take this information and run the unmixing model on the AVIRIS data to output a benthic composition image of coral, sand, and algae.

Unmixing Output

Benthic Composition

Sand

SAVCoral

Difference

Coral Sand SAV

Coral Sand SAV

Sand

SAVCoral

Values 0-100% using a rainbow color scheme from purple to red. A pure pixel corresponds to 100% of a given cover type.

Purple represents locations where the inversion model output values were lower than the Hydrolight values. Values increased through the rainbow to red where inversion model values are higher than the Hydrolight values. Yellow/green locations are where the output approaches were similar.

Inversion Model

Acropora cervicornis (staghorn coral)

20042004 20052005 20062006

20072007 20082008 20092009