Estimation of Wave Propagation
Distance in Swash Zone with Image
Analysis Results of CCTV-Coastal
Telemetry
M. Luqman Hakim
1, Endra Joelianto
2, Suprijanto
2Instrumentation and Control Research Group
1,2Agency for Meteorology, Climatology and Geophysics (BMKG)
1Faculty of Industrial Technology
Bandung Institute of Technology
Bandung 40132, Indonesia
E-mail: luqman.hakim@bmkg.go.id, ejoel@tf.itb.ac.id, supri@tf.itb.ac.id
Abstract—The paper presents an estimation method of wave propagation distance in swash zone using image analysis results from CCTV-coastal telemetry monitoring station installed on Seminyak beach and Kuta beach, Bali, Indonesia. Data are obtained from the BMKG, Indonesia. Wave propagation in swash zone is identified based on the bright foam edge which has maximum intensity. The data used in the paper are collected between 1 pm and 3 pm local time. Data are then analyzed in order to estimate of the wave propagation distance in swash zone for each beach. Results of estimation value are compared to data of change in sea level from tide gauge on Jembrana and Benoa, Bali. The purpose of comparison is to know the relationship between tidal on Seminyak beach, Kuta beach, Jembrana and Benoa. The results indicate the occurrence of low tides on Kuta beach, Seminyak beach, Jembrana and Benoa.
Keywords-wave propagation distance; image analysis, CCTV-coastal telemetry, swash zone, tide gauge.
I. INTRODUCTION
Indonesia is an archipelago which has a large sea region. It does not rule out a greater activity of Indonesia's population in the oceans. The phenomenon of sea wave changes in nearshore zone has an important role in influencing the activity and safety of local people [1][2]. The nearshore zone is divided into breaker zone, surf zone, and swash zone. Swash zone is a zone extending from the limit of uprush and backswash [6][9]. Bali has semi diurnal type of tidal [3]. CCTV-coastal telemetry as a video camera which provides visual information has become an alternative option to monitor the phenomenon of sea wave changes on the beach like a tidal wave, a tsunami and storm surge. The utilization of CCTV-coastal telemetry as a monitoring tool needs to be improved not only to provide visual information of sea waves propagation in the form of video but also to estimate sea waves propagation distance reaching
landward.
In this paper, it is considered an estimation of the wave propagation distance in swash zone using image analysis from video recording of CCTV-coastal telemetry. CCTV-coastal telemetry used in this study belongs to Agency for Meteorology, Climatology and Geophysics (BMKG) installed on Seminyak and Kuta beach, Bali, Indonesia. The data video from CCTV-coastal telemetry for each beach is transmitted via VSAT to BMKG on Jakarta, Indonesia. Wave propagation in swash zone based on the tracking of the bright foam edge formed on the sea surface after wave breaking.
Field observation is the first stage to support field analysis in order to determine the Ground Control Points (GCPs). The next step is to convert the digital video image to times tacks image with sampling rate 1 fps. After that, image pre-processing is used to analyze data packet loss of frame in transmission of the data via satellite networks. The final stage is done by conducting image processing. Image processing consists of reading the image of a blue color channel, median filter, texture analysis, image rectification, determination of the ROI, time stack, normalization of intensity and determination of the wave foam intensity. All of the stages is used to estimate of the wave propagation distance in swash zone. Furthermore, image analysis to estimate wave propagation distance in swash zone on Seminyak and Kuta beach obtained. In addition, the paper also considers the connection between the estimation of the wave propagation distance in swash zone on Seminyak and Kuta beach and data of sea surface height obtained from the tide gauge instrument on Jembrana and Benoa.
II. METHODS
Figure 1 shows the block diagram of the proposed estimation steps of the wave propagation distance in swash zone by using image analysis.
978-1-4673-7408-8/15/$31.00©2015 IEEE
Figure 1. Block diagram of the study methods.
Field Obsevation
The locations of CCTV-coastal telemetry installed on Seminyak and Kuta beach in Bali Island, Indonesia are shown in Figure 2. The CCTV is installed on top of a tower, the height of a tower is 18 meters. Jembrana and Seminyak beach are parallel with coastline of Kuta beach. Type of breaking waves on Seminyak and Kuta beach is spilling waves. Jembrana tide gauge is located to the west of Seminyak beach while Benoa tide gauge is located to the east of Kuta beach. Video data recording for each beach are gathered in the BMKG office in Jakarta, Indonesia.
Pre image processing is proposed in order to analyze data loss of frame based on parameters QoS (Quality of Service) in TIPHON systems [12][13]. The equation of the packet loss is given as follows:
����������=����������� − �������������� (1)
Packet received is given by:
(�����=�,�=�)≠(������+ 1,�=�+ 1)
Packet loss is given by:
(����� =�,�=�) = (����� =�+ 1,�=�+ 1)
Figure 2. location of study field, Seminyak and Kuta beach.
Pre image processing
In the field observation, it has been found, that due to the CCTV location, a rectangular shape formed by 4 points on the gound at the beach become a shifted rectangular as shown in Figure 3. Hence, it is necessary to determine 4 points of Ground Control Points (GCPs). The Ground Control Points (GCPs) are fixed targets in the field of view of each CCTV-coastal telemetry that are then used to calibrate the geometry solutions of each image. GCPs needed for mapping [5][11]. In this case, Seminyak beach has a width of 9 m and a length of 27 m and Kuta beach has a width of 6 m and a length of 27 m, shown in Figure 3.
Figure 3. GCPs (a) Seminyak beach (b) Kuta beach
Video image processing
Video image processing is employed to get data sampling at rate 1 fps. The data are taken from video recording on the 24th of January 2015 between 1 pm and 3 pm local time. Video recording obtained from BMKG in Jakarta. The next step is to extract the frames from video recording [8]. Number of frames for each experimental of time is 100 frame, 1 frame per 1 second. Levels of network degradation using TIPHON standard is shown in table 1 below.
Table 1. Levels of network degradation
No. Degradation Analyse loss data of frame
Image Graph of estimation distance
Image Processing
Original images are then represented as RGB format. Wave propagation in swash zone is identifed based on the tracking of the bright foam edge formed on the sea surface after wave breaking. The pixels of water area have the bluish color feature. Blue channel is then used to get intensity values of the bright foam edge. Intensity of blue channel [4] is given by
�= (0.1140 �) (2)
After that, noise is reduced and edges are preserved with median filter [4].
�(�,�) =������ {�(� − �,� − �), (�,�)∈ �} (3)
where g(x,y) is image result from median filter, f(x,y) is image input, and w is windows.
For detection of the bright foam edge, it is used entropy filter [10].
�(�,�) =������� {�(� − �,� − �), (�,�)∈ �} (4)
Rectification of image is used in supervised methods for transformation of pixels image coordinates (2D image coordinates) to be converted into spatial scales of units of meters or world coordinates (3D reference coordinates) [5][7][11][15]. Region of Ground control points has oblique shape as seen from the camera. Next step is to rectify an oblique image to horizontal plane image. Function of oblique transformation [16] is given by
[�′�′�′] = [� � �]∗ �42T (5)
(�′�′�′) is pixel image coordinates, (���) is world coordinates, T is transformation will be expressed as 3x3 matrix.
�=�� � �� � �
� � ��
(6)
After that, the resulted T is then applied to transform structure (T) to input image and copies the texture to the mapped locations. Mapped locations have new pixel image coordinates (u,v)
[� �] =��′
�′ �
′
�′� (7)
�=(��+��+�)
(��+��+�) (8)
�=(��+��+�)
(��+��+�) (9)
Not all direction of wave propagation in the image captured will be used in the analysis. Hence, the next step is the determination of the Region of interest (ROI). There are two criteria to determine of ROI. Firstly, the observation of reference points is based on sign of flags. The flags are used to mark shoreline and
swimming prohibition. The flag has ever caught on CCTV. Secondly, ROI is in the region of GCPs. the results of ROI are shown in figure 4.
(a)
(b)
Figure 4. (a) ROI of Seminyak beach (b) ROI of Kuta beach
After that, it is required to create a time stack image from a time sequence of ROI images [6][14][15]. Bright foam edge has the maximum intensity. The value of the maximum intensity for a time sequence of ROI images has variation. Ranges of values need to be normalized [9]. Intensity normalization is a process that changes the range of pixel intensity values from 255 to 0-1.
����������������������(�,�) =�(�,�)−����
����−���� (10)
�(�,�) is intensity of pixel coordinates, Imin is the value of minimum intensity of all pixels. Imax is value maximum intensity of all pixels.
After all set, a value of maximum intensity is obtained based on average values, for 13 pm is set a value to 0.8, 14 pm is set a value to 0.9 and 15 pm is set a value to 1. The final step of the image processing is to plot a graph of estimation of the wave propagation distance in swash zone.
III. EXPERIMENTAL RESULTS AND ANALYSIS
Normally, wave propagation distance in swash zone has variation in per unit of time, the graph of estimation of the sea wave propagation distance in swash zone looks fluctuation. But if it looks flat, it means the packet get lost over the networks as shown in figure 6 (b).
Tide gauge is an instrument to measure mean sea level trends. Tide gauge is used to obtain the tidal information. Tide gauge data on Jembrana is obtained from Indonesia Geospatial Information Agency (BIG) and tide gauge data on Benoa are obtained from Intergovernmental Oceanographic Commission (IOC). Tide gauge data on Jembrana and Benoa are then compared with the results of average distance value of wave propagation in swash zone on Seminyak and Kuta beach. Data tide gauge on Jembrana and Benoa are shown in figure 7. Data tide gauge on Jembrana and Benoa between 13-16 local time show occurrence low tides.
(a) (b)
Figure 7. (a) Data tige gauge on Jembrana (b) Benoa
Data of average distance value of wave propagation in swash zone on Seminyak and Kuta beach are shown in Figure 8. The data between 13-15 local time showed that it gets away from observation reference point. This means the occurrence of low tide on Seminyak and Kuta beach.
Figure 8. Cross shore distance againts time in swash zone on Seminyak and Kuta beach.
Packet loss of frame on Seminyak and Kuta beach for each time experimental is shown in Table 2.
Figure 5. (a) snapshot image of Kuta beach GCPs when surveyed (b) experimental image, blue channel (c) image results of median filter and entropy filter (d) image rectification (e) ROI (f) intensity 3D of ROI (g)
2D of ROI, before normalised pixel intensity (h) 2D of ROI, after normalised pixel intensity
(a) (b)
Tabel 2: Packet Loss
average of packet loss
33.33 Poor
Kuta, average of packet loss 6.67 Good
Packet loss on Seminyak beach is poor than on Kuta beach that has good category as shown in table 2. There can be many factors cause packet loss.
IV. CONCLUSION
Estimation of the wave propagation distance in swash zone with image analysis results of CCTV-coastal telemetry was considered in the paper. Wave propagation in swash zone based on the bright foam edge related to maximum intensity can be identified. The experimental results showed that between 13-15 local time on the Kuta and Seminyak beach has relation with Jembrana and Benoa, where low tides occur for each location. Packet loss can occur in the transmission the packet data via satellite network. The packet loss problems can come from device performances, link congestion, malfunction of the hardware and software. In the future research, the packet loss will be analyzed more detailed related to the real time performance of the estimation of wave propagation distances.
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