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Using SPOT-LANDSAT images for mapping, inventory and monitoring of reefs

Using SPOT-LANDSAT images for mapping, inventory and monitoring of reefs. - Serge Andréfouët - Remote Sensing/ Biological Oceanography  University of South Florida, St Petersburg, USA Laboratoire de Géosciences Marines et Télédétection Université Française du Pacifique, Tahiti. 5 km.

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Using SPOT-LANDSAT images for mapping, inventory and monitoring of reefs

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  1. Using SPOT-LANDSAT images for mapping, inventory and monitoring of reefs - Serge Andréfouët - Remote Sensing/ Biological Oceanography  University of South Florida, St Petersburg, USA Laboratoire de Géosciences Marines et Télédétection Université Française du Pacifique, Tahiti

  2. 5km Anaa Atoll (French Polynesia) SPOT XS-3,2,1 Lagoon Ocean Rim

  3. 5km Marquesas Key (Florida, USA) LANDSAT 5 TM-3,2,1

  4. 20/30 meters 20/30 meters

  5. 20/30 meters 20/30 meters

  6. 40/60 meters 40/60 meters

  7. 300 meters 300 meters

  8. Atoll Lagoon 1500 meters Ocean 1500 meters Lagoon

  9. XS3 XS1 XS2 SPOT IMAGES Pixel P XS3 XS3 XS2 XS1 XS2 Spectral space P XS1

  10. Remotely sensed information • LwXSi= LwXSb + LwXSw (+ Lwa) SPOT: XS1, XS2 LANDSAT: TM1, TM2, TM3 • LwXSbrelated to the “bottom” features • LwXSw related to the water column features

  11. Spectral discrimination of organismsLwb

  12. Spectral discrimination Sensitivity TM1 Sensitivity XS1 Sensitivity XS2

  13. Spectral discrimination 0 meters depth

  14. Under-water Spectral discrimination 5 meters depth

  15. Under-water Spectral discrimination 20 meters depth

  16. Minimum Discernable Unit (MDU) Size_MDU = PixelSize.(1+2.ErrorLocation) if ErrorLocation= 1 pixel (pretty good!!) SPOT MDU= 60 m x 60 m LANDSAT MDU = 90 m x 90 m

  17. Minimum Discernable Unit (MDU) 2 x 2 m : not enough CASI image: PixelSize= 1 meter 4 x 4 m : ok for training

  18. Minimum Discernable Unit (MDU) MDU= 3 x 3 m MDU= 60 x 60 m

  19. Remotely sensed information • Lwi= Lwb + Lww (+ Lwa) • 2 or 3 known measurements: XS1 and XS2 TM1, TM2 and TM3 • 2 unknown variables Lwb and Lww

  20. Haraiki atoll (French Polynesia)

  21. Computed depth Real depth Depth 8km Bathymetric modeling (Lww)

  22. Image of thebottom Scale “Radiance” scale

  23. “Bottom” reconnaissance (Lwb)

  24. Branching Massive Laminar Foliaceous Columnar Encrusting Free-living Architecture (forms and dimensions) Source: Veron (1986)

  25. Similarity Hierarchical clustering of the stations Reef Soft Bottom Hard bottom Sand/Rubble with Isolated-Patches Pure Rubble Pure Sand Living coral Living Dead field stations

  26. What type of habitat can you map with SPOTwith a good accuracy (70%) ?Depth < 7-8 metersDefinition: coarseMinimum Discernable Unit= 60 meters x metersBoundary analyses

  27. Spatial structure of a reef system Transition Fragmented Gradient Abrupt boundaries Patches

  28. A reef is a complex object, but any part of the reef has a membership degrees in each of the classes • This membership belongs to [0...1] • Mapping of membership degrees: fuzzy classification

  29. Is this membership degree useful? • Mapping • Habitats boundary analyses • Acanthaster planci outbreaks

  30. Tiahura Ocean Land

  31. Ocean Motu Land Ocean Membership degree: Motu Land 1 0 Ocean Motu Land Fuzzy classification Coral One map for each class of bottom. Mapping of the degree of membership. Heterogeneous Dead structures

  32. Tiahura Ocean Land

  33. Ocean Motu Land Ocean Membership degree: Motu Land 1 0 Ocean Motu Land Fuzzy classification Coral One map for each class of bottom. Mapping of the degree of membership. Heterogeneous Dead structures

  34. Tiahura Ocean Land

  35. Ocean Motu Land Ocean Membership degree: Motu Land 1 0 Ocean Motu Land Fuzzy classification Coral One map for each class of bottom. Mapping of the degree of membership. Heterogeneous Dead structures

  36. Is this membership degree useful? • Mapping • Habitats boundary analyses • Acanthaster planci outbreaks

  37. Tiahura 2.5 km

  38. Transitions between bottom types Coral Isolated Patches Land Sand Land Land Land 1 0 Possibility measurement

  39. Is this membership degree useful? • Mapping • Habitats boundary analyses • Monitoring and sampling designs (Acanthaster planci outbreaks)

  40. Ocean Land Location of A. planci infestations in the 80’s (Faure, 1989)

  41. What about change detection ? 0 meters depth

  42. What about change detection ? Histograms of bottom-types in XS1 after bathymetric corrections for 2 atolls

  43. What about change detection ? • Problems in calibration and correction of the images: • not enough accurate • Benthos: • Shifts in living communities : ?????? • Change in sediment cover (hurricanes) : ok

  44. Work in the field Moorea: 20 transects (60m x~1km) for training and control, 6 days, 2 investigators (Yannick Chancerelle, CRIOBE, Moorea), Semi-quantitative (5%, 15%, 25%, >50%) rapid assessment for 4 variables Atolls: 20 transects, 2 days, 2 investigators Caveat: Only assessment of the coarse level of habitat without hierarchical sampling (if not, time x 10) !!!

  45. Work in the image processing lab Bathymetric correction Fuzzy classification to output membership degrees Mapping of the membership degrees 3days - 1week Conditions: - user-friendly software does exist - good control of the software - good quality of the data (image and field data) - skilled analyst (if not, time x 10)

  46. Water parameters Few direct observations. Potentially interesting for atoll lagoons (phytoplanctonic biomass or suspended matter) Many indirect observations (the water body is not the target) rivers run-off, pollution, boundary characterization and residence time

  47. Spatial structure of a reef system and fluxes Reka-Reka Tepoto Sud Tekokota Boundary conditions controls: Nutrients limitations Residence time of lagoon waters Recruitment Community structure

  48. Atoll rims typology Structure Wave Exposure Hydrodynamic aperture aperture 33 % aperture > 70 % South

  49. Empirical relationships between flows of oceanic water and wave height for each type of rim H_Topex (m) Flows (m2/s)

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