Thesis Committee Dr. Nitin Kumar TripathiChairperson Prof. Seishiro KibeMember Dr. Wenresti GallardoMember 14-May-2008 MAPPING CHANGES IN THE MARINE ENVIRONMENT OF PHU QUOC ISLAND, VIET NAM Ton Binh Minh Remote sensing and GIS FoS

- Area 593 km 2, - 26 small islands - Phu Quoc Island; An Thoi - Tho Chau archipelagoes - Coastal Hydrologic condition for ecotourism Phu Quoc Island

Natural Resources Phu Quoc Island not only has potential for marine resources but also for ecotourism and relax

- Remote sensing and GIS are power tools for mapping and management of resources - Surface - Under Water - 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

Objective - To detect the changes in sea grass beds, coral reefs during and 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,

Bai Bon Aster 2004 An Thoi Landsat 2007 Study area - An Thoi - Bai Bon Data base - Ancillary data, - Remote sensing data, - Field data. - Ancillary data: + Previous reports. + Administration, transportation + Bathymetric depth + Sediment maps

Data Surveillance and Collection tools - GPS, - Tape measurement (30m), - Digital camera, - Data form, - Secchi disk, - Diving equipment - Boat Data base- Field data

Quadrats 20M + Field work techniques Linear transect Integration linear transect and quadrat for collecting data in seagrass area = 1m

Analyzing Image Mean DN value of coral, seagrass, sand in four bands Mean DN value of coral, seagrass, sand in band 1, 2, 3 Aster 2004 Landsat 2007

1. Image Registration - Image-to-image registration - Aster image in WGS 84, UTM 48 N. Digital image processing 2. Image masking - Segregating land and sea area - Near-infrared band ( μm) was used for masking

Water Column Correction

Water column corrected image An Thoi area Bai Bon area Landsat 2007 Aster 2004,

Image Enhance FCC, PCA, Band ratio

Landsat 2007 High OIF, as FCC (4,3,1) Landsat 2007 Low OIF as true color composite (321) Color composite - Optimum Index factor

Landsat 2007 low OIF as true color composite (3,2,1) Landsat 2007 High OIF as FCC (4,3,1) Optimum Index Factor

Accuracy Assessment - Site specific error matrix and Kappa analysis Image Classification - Maximum Likelihood classifier, field data, WCC image - Class hierarchies and definition

Classification in Bai Bon

Classification results in An Thoi using Aster 2004

Classification results in An Thoi using Landsat 2007

Map 2007: Overall accuracy = 70% KHAT = 64%, Map accuracy Map 2004 Overall accuracy = 77% KHAT = 74%

Change detection - Non site specific error matrix, - Map overlay

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 % Change detection analysis

Degeneration of live coral, seagrass in period , An Thoi. Decrease quality of live coral, seagrass in period in An Thoi

Degeneration of live coral, seagrass in period , An Thoi Decrease quality of live coral, seagrass in period in An Thoi

Degeneration of seagrass in Bai Bon

Regeneration of coral, seagrass in , An Thoi

Regeneration of coral, seagrass , An Thoi.

Regeneration of seagrass in Bai Bon

Comparing a part of Duong Dong town by using Landsat 25m, Aster 15m and Quick Bird 2.4m imageries Benthic Habitats Mapping Using Medium and High Resolution Image

Extending Quick Bird Imagery to Detect Bottom Type -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 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. Extending Quick Bird Imagery to Detect Bottom Type Data fusion technique for Quick bird imagery

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 Aster imagery because it lacks blue band. 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.

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)

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 and 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. Conclusion

Thank you for your kind attention! I also thank to my Advisor, Examination committees members, Wetland Alliance Program!