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MAPPING CHANGES IN
THE MARINE ENVIRONMENT OF PHU QUOC
ISLAND, VIET NAM
Ton Binh Minh
Remote sensing and GIS FoS
Dr. Nitin Kumar Tripathi
Prof. Seishiro Kibe
Dr. Wenresti Gallardo
Thesis Committee
Chairperson
Member
Member
14-May-2008
Phu Quoc Island
- Area 593 km2,
- 26 small islands
- Phu Quoc Island; An Thoi
- Tho Chau archipelagoes
- Coastal Hydrologic condition for
ecotourism
Natural Resources
Phu Quoc Island not only has potential for marine
resources but also for ecotourism and relax
- Marine resource are:
 Over exhausted and none plan exploited
 Fish, turtles, dugong, dolphins are on the verge of
extinction.
- Unsustainable fishing techniques
(small mesh fishnets, cyanide, dynamite, flying raking,
and Increasing number of fishermen, fishing vessels with
close shore fishery activities).
- Detailed maps of marine habitats, changing rule of
environment for monitoring marine environment
management, conservation coastal ecosystems and
sustainable development
- Remote sensing and GIS are power tools for mapping and
management of resources
- Surface
- Under Water
Objective
- To apply remote sensing and GIS to monitor and evaluate
coastal resources in Phu Quoc Island.
Detail objectives
- To map benthic communities: sea grass, coral (live and
dead), sand, rubble around Phu Quoc Island,
- To provide data for environmental and management of
seagrass beds and coral reefs,
- To detect the changes in sea grass beds, coral reefs
during 2000-2004 and 1992-2007.
Study area
- An Thoi
- Bai Bon
Data base
- Ancillary data,
- Remote sensing data,
- Field data.
- Ancillary data:
+ Administration,
transportation
+ Bathymetric depth
+ Sediment maps
+ Previous reports.
Bai Bon
Aster 2004
An Thoi
Landsat 2007
Data base- Field data
Data Surveillance and
Collection tools
- GPS,
- Tape measurement
(30m),
- Digital camera,
- Data form,
- Secchi disk,
- Diving equipment
- Boat
Field work techniques
Linear transect
Quadrats
20M
+
1m
=
1m
20M
Integration linear transect and quadrat for collecting data in seagrass area
Analyzing Image
Landsat 2007
ASTER 2004
120
90
Coral
80
70
Sand
60
80
Landsat 2007
DN value
DN value
Coral
Seagrass
Sand
100
Seagrass
50
40
30
Aster 2004
60
40
20
20
10
0
1
2
3
4
Band
Mean DN value of coral, seagrass,
sand in four bands
0
1
2
Band
3
Mean DN value of coral, seagrass,
sand in band 1, 2, 3
Digital image processing
1. Image Registration
- Image-to-image registration
- Aster image in 2000.
- WGS 84, UTM 48 N.
2. Image masking
- Segregating land and sea area
- Near-infrared band (0.780.98μm) was used for masking
Water Column Correction
Landsat TM, Aster images
(atmospheric correction)
Band pairs selection
Training site selection
(uniform pixel, various in depth)
Extracting pixel value
Calculating VAR and COVAR
training site’s pixel in band i, j
Calculating coefficients
attenuation (ki/kj)
Implementation depth-invariance to whole image
(Water column correction image)
Water column corrected image
Bai Bon area
An Thoi area
Landsat 2007
Aster 2004,
Image Enhance
FCC, PCA, Band ratio
Color composite - Optimum Index factor
Landsat 2007 Low OIF as true
color composite (321)
Landsat 2007 High OIF, as
FCC (4,3,1)
Optimum Index Factor
Landsat 2007 low OIF as true
color composite (3,2,1)
Landsat 2007 High OIF as FCC
(4,3,1)
Image Classification
- Maximum Likelihood classifier, field data , WCC image
- Class hierarchies and definition
Accuracy Assessment
- Site specific error matrix and Kappa analysis
Classification in Bai Bon
500
50
50
400
00
00
350
00
Sand 3000
zone
2500
Dead 2500
coral
Sand zone
2000
Sand zone
2000
Live coral
cover 01-10%
1500
Dead coral
coral
Dead
Live coral cover 10-20%
1000
Live coral
coral cover
cover 01-10%
01-10%
Live
Rubble500
Live coral
coral cover
cover 10-20%
10-20%
Live
Seagrass
0 dens 70-80%
Rubble
Rubble
Seagrass dens 80-90%
Seagrass dens 70-80%
Seagrass dens 90-100%
Seagrass dens 80-90%
Sand zone
500
300
Hecta
50
3000
0
2004
250
500
Hecta
450
Hecta
00
00
3500
3500
1500
1000
2007
Classification results in An Thoi using Aster 2004
500
450
400
350
500
Hecta
300
250
200
450
100
50
400
Sand zone
150
Dead coral
Live coral cover 01-10%
0
Live coral cover 2004
10-20%
350
300
250
Rubble
Seagrass dens 70-80%
Seagrass dens 80-90%
Seagrass dens 90-100%
Classification results in An Thoi using Landsat 2007
500
450
400
Hecta
350
300
250
200
150
100
50
0
2007
Sand zone
Dead coral
Live coral cover 01-10%
Live coral cover 10-20%
Map accuracy
Map 2007:
Map 2004
Overall accuracy = 70%
Overall accuracy = 77%
KHAT = 64%,
KHAT = 74%
Change detection
- Non site specific error matrix,
- Map overlay
Landsat image
Dec -1992
Landsat image
Jan 2007
Aster image
Dec- 2000
Aster image
Nov- 2004
Reefs, seagrass
habitat map
1992
Reefs, seagrass
habitat map
2007
Reefs, seagrass
habitat map
2000
Reefs, seagrass
habitat map
2004
Overlay
Reef habitat change in
1992-2007
Seagrass habitat change in
1992-2007
Overlay
Reef habitat change
in 2000-2004
Seagrass habitat change
in 2000-2004
Change detection analysis
Non Site Post Classification Comparison
The overall accuracy = 42 % map 2007 agree 42%, with map 1992
Khat value = 29%  category of map 2007 is same with map 1992 29%
Degeneration of live coral, seagrass in period 2000-2004, An Thoi.
Decrease quality of live coral, seagrass
in period 2000-2004 in An Thoi
Degeneration of live coral, seagrass in period 1992-2007, An Thoi
Decrease quality of live coral, seagrass
in period 1992-2007 in An Thoi
Degeneration of seagrass in Bai Bon
Regeneration of coral, seagrass in 2000-2004, An Thoi.
56.20
Regeneration of coral, seagrass 1992-2007, An Thoi.
Regeneration of seagrass in Bai Bon
Benthic Habitats Mapping Using Medium and High Resolution Image
Comparing a part of Duong Dong town by using Landsat 25m, Aster 15m
and Quick Bird 2.4m imageries
Extending Quick Bird Imagery to Detect Bottom Type
Data fusion technique for Quick bird imagery
-The Gram Schmidt Spectral Sharpening
- Sharpen multispectral data of QB at 2.4 m to
panchromatic band at 0.6 m resolution.
- Gram-Schmidt techniques:
+ Not limited to the number of bands that can be
processed at one time.
+ Preserved the spectral characteristics of lower
spatial resolution multispectral data in the higher
spatial resolution
Extending Quick Bird Imagery to Detect Bottom Type
Data fusion technique for Quick bird imagery
Fused image with 0.6m
resolution. Using Gram-Schmidt
Spectral Sharpening band
combination band 3,2,1.
Fused image with 0.6m
resolution. Using Gram-Schmidt
Spectral Sharpening, band
combination 4,3,2.
Quick bird data potential for detail mapping benthic community
Comparing fusion image (2,4,3) with Aster(1,2,3)
fusion image and original image
Applying enhance technique to Quick bird data
True colour combine,
square root enhance,
various information
Band ratio: composite of 3/1, 3/2,
2/1 (RGB)
•. Several light yellow areas and
light green appeared in reefs
and terrestrial rock. Possible
these have developed of marine
algae or seagrass.
Aster imagery because it lacks blue band.
Conclusion
1. Remote sensing and GIS are powerful tools for
conservation and management marine resource.
• as they provide data of difficult location and powerful analysis
tools.
2. The coral reefs and seagrass beds map in 2007 and
2004 has been created using bands 1, 2 and 3 of Landsat
and bands 1, and 2 of Aster.
3. RS techniques and image processing were used to
enhance image reflectance and spectral characteristics.
4. Water column correction was employed to remove
suspended matter effect.
5. Maximum likelihood classification yielded high overall
accuracy =70% (Landsat 2007) and = 77 % (Aster 2004)
Conclusion
6. Live coral and seagrass changes were detected which
can be very useful for managing marine resources
7. The comparison of the change area between 19922007 and 2000-2004 was not significant.
8. Degeneration and regeneration were successfully
processed. Seagrass and coral reefs in study area are
degenerating. Possible, sea environment of PQ is
changing to worse status.
9. Quick Bird imagery with high resolution is better for
mapping benthic communities in detail;
• it is optical imagery thus, one scene covers small area,
• cloud effect,
• Image is more expensive than moderate resolution satellite image.
Thank you
for your kind attention!
I also thank to my Advisor,
Examination committees members,
Wetland Alliance Program!