GEOMORPHOLOGICAL FEATURES OF KUALA TERENGANU SPIT FROM IKONOS IMAGERY AND AERIAL PHOGRAPHS USING SEGMENTATION METHOD

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1 GEOMORPHOLOGICAL FEATURES OF KUALA TERENGANU SPIT FROM IKONOS IMAGERY AND AERIAL PHOGRAPHS USING SEGMENTATION METHOD Aicha. Chalabi, H. Mohd-Lokman, I. Mohd-Suffian, M. Karamali Informatics Laboratory, Institute of Oceanography, Kolej Universiti Sains dan Teknologi Malaysia, Mengabang Telipot, Kuala Terengganu, Terengganu, Malaysia Keywords: shoreline, GIS, Remote Sensing, IKONOS, ERDAS, ArcInfo. ABSTRACT Coastal shoreline is defined as intersection of land and water. It changes rapidly under dynamic processes effect such as waves, tides, currents and winds. Consequently, shoreline change is an important issue in Malaysia due to its damaging impact. Remote sensing and GIS present new tools to analyse, display and visualize the changing shoreline. In this paper we proposed segmentation method to extract the shoreline.segmentation method is becoming increasingly more important in remote sensing field, particularly with the increasing spatial resolution of imagery. The shoreline of Kuala Terengganu was extracted from IKONOS data with 1 meter resolution acquired in 2004, and 25,000 scales of aerial photographs of 1966 and The aim of this paper is to present the resort of an extraction technique from remote sensing data using the segmentation algorithm. INTRODUCTION In recent literature, the coastal zone is defined as a narrow area of land adjacent to the shoreline where the sea and the land intersect [9]. This area is highly dynamic and complex environment characterized by a multitude of processes and activities [2].The coastal erosion is one of the natural phenomenons resulting from the interaction between natural processes and the system. Since 1984, coastal erosion became a serious problem in Malaysia which 29% of the coastline eroded. Remote sensing techniques have been employed to monitor shoreline changes using data from aerial photography [7] and satellite images [4] based on digitizing. Tracing the coastline manually is not practical where the coastline becomes very complex, such as the spit feature, and the rate of error is high [10]. Therefore it is necessary to develop new methods of shoreline extraction on the basis of different kinds of image processing methodologies [1]. Recently, scientists have developed many algorithms for extraction of shoreline. One of the methods is image segmentation which becomes more important and essential for high resolution remote sensing imagery such as aerial photographs, IKONOS images and Quikbird images. The aim of this paper is to test the ability of extraction technique from remote sensing data. STUDY AREA The study area is located on the East Coast of Peninsular Malaysia facing the South China Sea. It is located between latitudes 103 7` 44`` and ` 56` North, and longitude 5 21` 49``and 5 16` 39`` East. The shoreline is about 17 km from Tok Jembal North to Kuala Ibai south. The beach of this area is interrupted by mouth of kuala Terengganu estuary and Chendering. The climate of Kuala Terengganu is characterized by the northeast monsoon which prevails between November and March. The annual temperature is between 25.6 C to 27.8 C [8]. According to [6], the

2 study area is characterized by semi diurnal tides in the order of 1.0 to 2.0 m the wave height is less than 1.8m.The most prominent winds come from N-NE and SE-S direction [8]. Fig. 1. Study Area DATASET In this study we have two different type of data; IKONOS data imagery acquired in November 2004 and Aerial photography during 1966 and Table 1 identifies the images. Table. 1. Data acquisition Type of data Date of acquisition Spatial Resolution Scale IKONOS 25 November m Aerial Photography / GEOMETRIC CORRECTION OF IKONOS IMAGERY AND AERIAL PHOTOGRAPHY IKONOS data was collected from Malaysian center for Remote Sensing (MACRES) which acquired on 25 November In this study, we used Malaysia Rectified Skewed Orthomorphic (MRSO) as coordinate system.to correct the data geometrically, 36 ground control points (GCPs) were collected on the ground between Kuala Terengganu and Kuala Ibai using Differential Global Positioning System (DGPS). Geometric correction for IKONOS satellite imagery was done in PCI (GCP WORKS). RMS (Root Mean Square) error in X and Y are 0.37 and 0.29, respectively the error in location was less than half pixel (1 m). Aerial photographs during the 1966 and 1975 were corrected using digital topography maps of scale 1/ Geometric correction was done using ArcMap software.

3 Fig. 2. Geometric correction of Aerial photographs 1966 and 1975 and IKONOS 2004 METHODOLOGY Many semi-automatic or automatic segmentation techniques were applied to extract the shoreline from variety of remote sensing data [10, 5, 1]. The methodology proposed for the extraction of the shoreline is based on segmentation technique. This method is defined as a process of grouping on observed image into its homogeneous region, taking grey level aspect into account of image pixels. The partition of the land and sea boundary was done using pseudo color band (band 3 of IKONOS) which exhibits a strong contrast between land and water features due to the high absorption by water and strong reflectance by vegetation [5] as shown in figure 3. The pixels were classified into two categories: all pixels with grey level values greater than breakpoint (t ), we output a value of 1, and pixels with grey level values smaller than breakpoint (t ), we output a value of 0 (Figure 4), applying the formula: 0, f (x,y) < t g ( x,y) = 1, f (x,y) > t (1) Where t is breakpoint Image segmentation is able to generate a GIS readable vector format, therefore a raster to vector conversion was carried out using ERDAS imagine. From ArcInfo software, vector shoreline has been edited to meet the uniformity criteria (figure 5). The steps following in this study are summarized below in figure 6. Fig. 3. Image segmentation based on gray level histogramme (IKONOS data)

4 Fig. 4. Image classification from IKONOS image (a) (b) Fig. 5. (a) before editing, (b) after editing Grey Level Segmentation from band 3 Classification Vectorization Extraction of shoreline Fig.6. Flowchart of segmentation method

5 RESULTS AND DISCUSION The extraction of shoreline from IKONOS and Aerial photographs were done using segmentation technique. The coastline of Kuala Terengganu fronts the South China Sea is interrupted by Kuala Terengganu estuary and Chendering river. Both are the major rivers flowing to the South China Sea [3]. The topography of this area is low and flat. In this study, results of time series data were combined and compared to each other showing spatial changes of Spit. Erosion and accretion in this part of the area reveal the geomorphological changes that have been taken place over 38 years period (between ) which are identified with different vectors, as shown in figure7. (a) South China Sea River South China Sea River (b)

6 South China Sea River (c) Fig. 7. Spit changes; (a) between , (b) between , (c) between The figure 7 (a) shows changes in the shape, size and position of spit and indicating the shifting of the spit in the Northwest direction. This shifting is a result of dynamic and unstable of this area, therefore the changes of spit is clearer and we can distinguish the average rate from Table. 2. Table. 2. Average changes in spit Erosion (Hectares/year) Accretion (Hectares/year) It is clear that spit is formed under accumulation of sand near to the river due to the oceanic forces of the South China Sea, river system, wave and wind which control the direction and shape of spit. The growing of spit in the top between 1966 and 1975 is more important where it is facing the river. The average rate of accretion 3.23 hectare/year and 0.95 hectare per year as erosion. The spit in section (a) has a smaller wide, more narrow and complex in the bottom. it has been shifted down about m toward northwest. The length was increase to 75 m. In this section, the sedimentation is more dominant. In caption (b), the spit become more widely and fewer complexes in the side facing South China Sea. Here, the sedimentation still more dominant. As you can see from table2, no big difference between erosion and accretion. Spit in section (c) become more close to the river and extended from 75m to 255.5m in length. As result loss of sand in this part caused erosion and up the average of sand in the river, this phenomenon will block the river as can be seen with the spit taking more space around the mouth of the river. From the results, the changes of spit over 38 years show that the area is affected by both erosion and accretion involving many factors. The growing of spit between 1966 and 1975 was at the left side facing the river however, between 1975 and 2004 the spit grew to the right side towards the South China Sea. The accretion is more dominant over 38 years.

7 CONCLUSION Results obtained from IKONOS image and Aerial photographs were used to analyze the changes of spit over 38 years using segmentation method. Time series data with integration of remote sensing and GIS data can determine the erosion and accretion patterns. Choosing segmentation technique as method to extract the shape was useful and more accurate because of the high resolution. As conclusion we can consider segmentation method as a good technique for monitoring and mapping changes of the coast and understand the coastal dynamics related to the coastline. ACKNOWLEDGMENT The authors would like to thanks the Rector of Kolej Universiti Sains dan Teknologi Malaysia (KUSTEM), the Director of Institute of Oceanography (INOS) and the Director of Research Management Center for the financial support they provided and encouragement. REFERENCES [1] Dellepiane, S., De Laurentiis, R., Giordano, F Coastline extraction from SAR images and a method for the evaluation of the coastline precision. Pattern Recognition Letters 25 (2004) [2] Fabri, K. P A framework for structuring strategic decision situation in integrated coastal zone management. Netherlands Geographical Studies 310, Koninklijk Nederlands Aardrijkskundig Genootschap/ Faculteit der Economische Wetenschappen en Econometrie, Vrije Universiteit Amsterdam, Printed in the Netherlands by Labor Grafimedia b.v. Utrecht, pp. [3] Lokman, H.M., Rosnan,Y., Shahbudin, S Beach Erosion Variability during a Northeast Monsoon: The Kuala Setiu Coastline, Terengganu, Malaysia. Pertanika J. Sci. & Technol. Vol. 3 No. 2, 1995, pp. [4] Mazlan, H., Aziz.I., Abdullah, A Preliminary evaluation of photogrammetricremote sensing approach in monitoring shoreline erosion. Proceedings, Tenth Asian Conference on Remote Sensing, Kuala Lumpur, November Asian Society of Remote Sensing, Kuala Lumpur, F-5-1-F [5] Mohd-Suffian, I., Nor Antonina, A., Sulong, I., Mohd-Lokman, H., S. Suhaila,I Monitoring the Short-term Change of the KELANTAN DELTA using Remote Sensing and GIS applications. KUSTEM 3 rd Annual Seminar, on Sustainability Science and Management, Role of Environmental Science and Technology in Sustainable Development of Resources, Beach Resort, Kuala Terengganu, 4-5 May 2004, pp. [6] Muslim,M. S Shoreline Mapping Using Satellite Sensor Imagery, University of Southampton, Faculty of Engineering, Science and Mathematics, School of Geography, Thesis for the degree of Doctor of Philosophy, March 2004, 212 pp. [7] Raj, J.K Net Direction and Rates of present-day Beach Sediment Transport by Littoral Drift along the East Coast of Peninsular Malaysia. Geology. Social. Malaysia, Bulletin 15, December 1982, pp. [8] Rosnan,Y., Hussein, M.L., Tajuddin, A Variation of Beach Sand in relation to Littoral Drift Direction along the Kuala Terengganu Coast. Geol.soc.Malaysia, Bulletin 58, December 1995, pp. [9] Tjia,H. D., Mastura. S. A The coastal Zone Peninsular Malaysia, Penerbit Universiti Kebangsaan Malaysia, Bangi, Printed in Malaysia by Dicetak di Malaysia oleh, Percetakan Watan SDN BHD, 129 pp. [10] White, K., El Asmar. H. M Monitoring changing position of coastlines using Thematic Mapper imagery, an example from the Nile Delta. Elsevier Science B.V, Geomorphology 29 (1999) pp.