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Using SPOT-LANDSAT images for mapping, inventory and monitoring of reefs - Serge Andréfouët - Remote Sensing/ Biological Oceanography University of South.

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Presentation on theme: "Using SPOT-LANDSAT images for mapping, inventory and monitoring of reefs - Serge Andréfouët - Remote Sensing/ Biological Oceanography University of South."— Presentation transcript:

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

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

4 20/30 meters

5

6 40/60 meters

7 300 meters

8 1500 meters Lagoon Ocean Atoll Lagoon

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

10 Remotely sensed information Lw XS i = Lw XS b + Lw XS w (+ Lw a ) SPOT: XS1, XS2 LANDSAT: TM1, TM2, TM3 Lw XS b related to the “bottom” features Lw XS w related to the water column features

11 Spectral discrimination of organisms Lwb

12 Spectral discrimination Sensitivity TM1Sensitivity XS2Sensitivity XS1

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) CASI image: PixelSize= 1 meter 2 x 2 m : not enough 4 x 4 m : ok for training

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

19 Remotely sensed information Lw i = Lw b + Lw w (+ Lw a ) 2 or 3 known measurements: XS1 and XS2 TM1, TM2 and TM3 2 unknown variables Lw b and Lw w

20 Haraiki atoll (French Polynesia)

21 Bathymetric modeling (Lw w ) Computed depthReal depth Depth 8km

22 Image of the bottom Scale “Radiance” scale

23 “Bottom” reconnaissance (Lw b )

24

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

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

27 What type of habitat can you map with SPOT with a good accuracy (70%) ? Depth < 7-8 meters Definition: coarse Minimum Discernable Unit= 60 meters x meters Boundary analyses

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

29 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

30 Is this membership degree useful? Mapping Habitats boundary analyses Acanthaster planci outbreaks

31 Tiahura Ocean Land

32 Motu Ocean Fuzzy classification One map for each class of bottom. Mapping of the degree of membership. Coral Heterogeneous Dead structures 1010 Membership degree:

33 Tiahura Ocean Land

34 Motu Ocean Fuzzy classification One map for each class of bottom. Mapping of the degree of membership. Coral Heterogeneous Dead structures 1010 Membership degree:

35 Tiahura Ocean Land

36 Motu Ocean Fuzzy classification One map for each class of bottom. Mapping of the degree of membership. Coral Heterogeneous Dead structures 1010 Membership degree:

37 Is this membership degree useful? Mapping Habitats boundary analyses Acanthaster planci outbreaks

38 Tiahura 2.5 km

39 Coral Isolated Patches Sand Transitions between bottom types Land 1010 Possibility measurement Land

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

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

42 0 meters depth What about change detection ?

43 Histograms of bottom-types in XS1 after bathymetric corrections for 2 atolls

44 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

45 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) !!!

46 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)

47 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

48 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

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

50 H_Topex (m) Flows (m 2 /s) Empirical relationships between flows of oceanic water and wave height for each type of rim

51 Residence time in atoll lagoons

52 Distribution of coral reefs Estimated 255.000 km 2 (Spalding & Grenfell, 1997) Global scale

53 Similarity field stations Pure Sand Sand/Rubble with Isolated-Patches Reef Soft Bottom Hard bottom Dead Living Pure Rubble Living coral

54 Global Coverage: NASA plans to collect ~200 LANDSAT 7 images per day worldwide: Long-Term Acquisition Plan (LTAP)

55 Present coverage of reefs by LTAP Expected: one cloud-free image per year

56 Present coverage of prioritized reefs by LTAP (research activities) Expected: 4-6 cloud-free images per year

57 Global coverage Estimation of global distribution of reefs, without ground-truth, 2 classes (soft and hard-bottom), 80% accuracy A basis for extension of monitoring worldwide, 6 classes (gradient of soft and hard-bottom), with ground-truth, 70% accuracy Interface with monitoring organizations is required to get training data for image processing

58 Conclusions Using SPOT-LANDSAT images for mapping, inventory and monitoring of reefs? Pragmatic point of view Mapping: Yes: - Coarse habitats with ground truth Bathymetric and atmospheric corrections required - Soft/hard bottoms without ground-truth and corrections - Boundary analyses Inventory: Yes % of soft/hard bottoms: global scale (LTAP): % of coarse habitats: reef-scale

59 Conclusions Using SPOT-LANDSAT images for mapping, inventory and monitoring of reefs? Monitoring: Not directly Change detection generally not possible Coarse-habitats level not generally a relevant parameter Water quality generally not directly available But provide: Geophysical parameters ( exposure, bathymetry, residence time, geomorphology ) Habitat mapping to stratify monitoring and establish new sites Generalize species indicator at reef scale Timing: once or variable (catastrophic event)


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