REMOTE SENSING OF BENTHIC HABITATS IN SOUTHWESTERN PUERTO RICO

Transcription

1 REMOTE SENSING OF BENTHIC HABITATS IN SOUTHWESTERN PUERTO RICO Fernando Gilbes Santaella Dep. of Geology Roy Armstrong Dep. of Marine Sciences University of Puerto Rico at Mayagüez

2 Center for Subsurface Sensing and Imaging Systems (CenSSIS) Mission: to revolutionize the existing technology for detecting and imaging biomedical, environmental, and civil objects or conditions that are underground, underwater, or embedded in the human body. Core Academic Partners: Northeastern University (Lead Institution) University of Puerto Rico at Mayaguez Renssalaer Polytechnic Institute Boston University Founded in 2000 with NSF support.

3 What is Remote Sensing? "It is the technique of deriving information about an object without actually coming in contact with it."

4 What is a Benthic Habitat? The term benthic refers to anything associated with or occurring on the bottom of a body of water. The animals and plants that live on or in the bottom are known as the benthos. Benthic habitats can best be defined as marine bottom environments with distinct physical, geochemical, and biological characteristics. Benthic habitats vary widely depending upon their location and depth, and they are often characterized by dominant structural features and biological communities. From

5 MAIN GOAL: Benthic Habitat Assessment Estimate: Atmospheric constituents Aquatic optical properties Aquatic constituents Benthic composition Bathymetry (water depth) Detect: Healthy/unhealthy coral Unexploded ordinance Human induced changes Classify: Coral distribution Seagrass density Benthic habitat maps Understand: Environmental stressors Seasonal/annual changes System productivity The Sun Detectors at Different Wavelengths Airborne or Satellite Multi/Hyperspectral Upwelling Photons Measured as Radiance Adapted from James Goodman

6 Southwestern Puerto Rico

7 NOAA Benthic Classification

8 Enrique Reef

9 SeaBED: Enrique Reef CONCEPT: Assemble a multi-level array of optical measurements, field observations and remote sensing imagery describing a natural reef system Hyperspectral Image Data Surface Measurements Water Column Measurements Benthic Measurements OBJECTIVE: Provide researchers with data from a fully-characterized test environment for the development and validation of subsurface aquatic remote sensing algorithms LEGACY: Utilize scientific publications and web-based distribution to establish Enrique Reef and its associated data as a lasting community standard for algorithm assessment

10 Challenges for monitoring benthic habitats in Southwestern Puerto Rico

11 Issues in benthic habitat mapping 1. Sensor Characteristics: Signal to Noise (S/N) Ratio Spatial and Spectral Resolution 2. Atmospheric Conditions: Scattering and Absorption Gases and Aerosols 3. Signal from the Water Column: Surface Conditions Light Penetration Bio-Optical Properties 4. Signal from the Bottom: Water Depth Bottom Type Size of the Community 5. Signal Processing

12 WHAT IS THE BEST RESOLUTION? EVALUATE THE SPECTRAL VS SPATIAL RESOLUTION SENSOR BANDS SPECTRAL RANGE (µm) PIXEL SIZE (m) IKONOS 4 PAN HYPERION

13 Image interpretation and classification HYPERION IKONOS

14 IMAGE PROCESSING Ikonos Hyperion Atmospheric correction Destripe algorithm Glint Removal algorithm Atmospheric correction Water column correction Glint Removal algorithm Supervised Minimum Distance Classification Accuracy Assessment Image Validation Analysis of Results

15 Change Detection I 1 Change Detection Process Change Understanding Sea Grass Carbonate Sand I 2 B(x)= { 1 if pixel x has significant change from I 1 (x) to I 2 (x) 0 Otherwise B(x) Fore-reef Reef-flat Mangrove Change Mask Reef-flat Carbonate Sand Mangrove 2002 Deep water Sea Grass 2003 Work by Vanessa Ortiz Rivera, UPRM

16 Spectral Unmixing Unconstrained Sum To One 2002 HYPERION Unconstrained Non Negative Sum Less Than or Equal to One Non Negative Work by Samuel Rosario, UPRM

17 Opportunities for monitoring benthic habitats in Southwestern Puerto Rico

18 Seagrass Mangrove Gorgonians Fore Reef Reef Crest Dead Coral + Sand Sand Deep Water

19 Field Data Coral Rubble A. cervicornis M. annularis Field Measurements: Aquatic optical properties Georeferenced benthic reflectance Spectral library (species) Benthic Composition Detailed habitat map Gorgonians S. siderea T. testudinum Pump CTD AC-9 Data Logger HS-6 Reflectance Battery Pack Fluorometer OCR-200 OCR Wavelength, nm Coral: Porites compressa

20 Multi-Sensors Data HYPERION: August 15, 2002 January 15, 2003 March 13, 2004 March 29, 2004 September 5, 2004 AVIRIS: August 19, 2004 Multi/Hyperspectral Data: IKONOS HYPERION AVIRIS AISA IKONOS:

21 Spectral Unmixing AVIRIS Color Composite Benthic Habitat Composition Sand 8/19/2004 9:36 am W-E Coral Algae 8/19/ :18 am E-W Work by James Goodman, UPRM

22 HYPERSPECTRAL REMOTE SENSING OVER PUERTO RICO

23 HYPERION IMAGES Georeferenced raw data Destriped image Atmospherically corrected, destriped and deglinted image

24 Hyperion raw image Minimum distance classified image

25 AVIRIS MISSION OVER PUERTO RICO AUGUST 19, 2004

26 HYPERSPECTRAL MISSION NOV 28-DEC 21, 2007 AISA SENSOR Data collected at: 1, 2, 4, 8 meters 128 bands nm

27 FIELD ACTIVITIES FOR VALIDATION OF REMOTE SENSORS

28 Why we perform field work?? 1. Validate the classification procedures 2. Understand the remote signal 3. Develop site-specific algorithms

29 Field sampling for validation of image classification

30 Data Collection Effort GPS points (153 stations) GER Spectrometer (6 measurements/station) Bathymetry Photos

31

32 Above Water Measurements Rrs Sand Rrs Algae Rrs Coral Remote Sensing Reflectance (sr-1) Wavelength (nm) GER 1500 Spectroradiometer

33 Below Water Measurements Transect Average for Seagrass and Sand Remote Sensing Reflectance (Sr-1) Wavelength (nm) seagrass sand Transect Average for Coral Remote Sensing Reflectaance (Sr-1) Wavelength (nm) coral

34 Variability of Light Attenuation Radiance (W/cm^2/nm/sr) Scan 010 Scan 011 Scan 012 Scan 013 Scan 014 Scan 015 Scan 016 Scan 017 Scan 018 Ave 26cm Ave 84+26cm Ave cm Wavelength (nm) Kd (m-1) Kd for Cayo Enrique 8/19/ Wavelength

35 SPATIAL AND TEMPORAL VARIABILITY OF BIOGEO- OPTICAL PROPERTIES

36 Study Area

37 Sampled Stations El Mario Enrique Laurel Media Luna

38 Monthly Sampled Stations Station Reef Bottom Type Depth (m) 1 Media Luna Sand/Coral 3 2 Laurel Seagrass 2 3 Mario Shallow Sand/Coral Mario Deep Mod 18 5 Enrique West Seagrass Enrique East Sand 1.5

39 BIO-OPTICAL PACKAGE Pump CTD Data Logger OCR-200 (Ed) AC-9 HS-6 Battery Pack Fluorometer OCR-200 (Lu)

40 Temperature ( o C)

41 Salinity (RSU)

42 Fluorescence (RU)

43 Absorption (m -1 ) All Stations

44 Attenuation (m -1 ) All Stations

45 Fluorescence (RU) at Mario Deep

46 Absorption (m -1 ) at 440 nm in Mario Deep

47 Backscattering (m -1 ) All Stations

48 Backscattering (m -1 ) at Mario Deep Depth (m)

49 Hyperspectral profiling sensor

50 Hyperspectral profiling sensor

51 In Summary New remote sensing technology has great potential for developing accurate benthic maps. However, a better understanding of the biogeo-optical properties is required. And improved image processing techniques are needed. In the future

52 THANK YOU! QUESTIONS?