590 likes | 734 Views
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.
E N D
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
5km Anaa Atoll (French Polynesia) SPOT XS-3,2,1 Lagoon Ocean Rim
5km Marquesas Key (Florida, USA) LANDSAT 5 TM-3,2,1
20/30 meters 20/30 meters
20/30 meters 20/30 meters
40/60 meters 40/60 meters
300 meters 300 meters
Atoll Lagoon 1500 meters Ocean 1500 meters Lagoon
XS3 XS1 XS2 SPOT IMAGES Pixel P XS3 XS3 XS2 XS1 XS2 Spectral space P XS1
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
Spectral discrimination Sensitivity TM1 Sensitivity XS1 Sensitivity XS2
Spectral discrimination 0 meters depth
Under-water Spectral discrimination 5 meters depth
Under-water Spectral discrimination 20 meters depth
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
Minimum Discernable Unit (MDU) 2 x 2 m : not enough CASI image: PixelSize= 1 meter 4 x 4 m : ok for training
Minimum Discernable Unit (MDU) MDU= 3 x 3 m MDU= 60 x 60 m
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
Computed depth Real depth Depth 8km Bathymetric modeling (Lww)
Image of thebottom Scale “Radiance” scale
“Bottom” reconnaissance (Lwb)
Branching Massive Laminar Foliaceous Columnar Encrusting Free-living Architecture (forms and dimensions) Source: Veron (1986)
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
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
Spatial structure of a reef system Transition Fragmented Gradient Abrupt boundaries Patches
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
Is this membership degree useful? • Mapping • Habitats boundary analyses • Acanthaster planci outbreaks
Tiahura Ocean Land
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
Tiahura Ocean Land
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
Tiahura Ocean Land
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
Is this membership degree useful? • Mapping • Habitats boundary analyses • Acanthaster planci outbreaks
Tiahura 2.5 km
Transitions between bottom types Coral Isolated Patches Land Sand Land Land Land 1 0 Possibility measurement
Is this membership degree useful? • Mapping • Habitats boundary analyses • Monitoring and sampling designs (Acanthaster planci outbreaks)
Ocean Land Location of A. planci infestations in the 80’s (Faure, 1989)
What about change detection ? 0 meters depth
What about change detection ? Histograms of bottom-types in XS1 after bathymetric corrections for 2 atolls
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
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) !!!
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)
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
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
Atoll rims typology Structure Wave Exposure Hydrodynamic aperture aperture 33 % aperture > 70 % South
Empirical relationships between flows of oceanic water and wave height for each type of rim H_Topex (m) Flows (m2/s)