GISdevelopment.net ---> AARS ---> ACRS 1992 ---> Water Resources Bathymetry in clear waters from Landsat-5 Satellite Data Dr. Mohd Ibrahim Seeni Mohd, Samsudin Ahmad, Mohamad Yem Centre Remote Sensing Faculty of Surveying Universiti Teknology Malaysia Locked Bag 791 80990 Johor Bahru Malaysia Abstract The coastal waters of the world are o importance to navigation. However, the sea bottom topography in these areas undergo frequent changes due to coastal process such as erosion and siltation. As a result , hydrographic charts in these areas have to be updated frequently for safe navigation. Satellite remote sensing techniques can be used together with limited water depth measurements from conventional methods to chart the coastal areas in a cost-effective manner. This paper reports on a study to obtain water depths in the coasts! Waters of Pulau Tioman, Malaysia using the Landsat-5, Thematic Mapper data that were acquired on 1 April 1990. Band 1 ( 0.45 – 0.52 mm ) of the data was used since it has the best depth penetration capability in the relatively clear waters of Pulau Tioman. A computer program was written to correct the satellite data for atmospheric effects prior to computation of water depths. An algorithm which expresses the exponential relationship between water depth and pixel intensities were used together with a few in-situ calibration depths that were taken at the time of satellite pass. Comparisons of calculated depths with in-situ measured depths at some check points indicate an error of 0.5. – 2.0 m in depths of up to about 50 m of water. 1. Introduction Hydrographic surveying by conventional shipborne sounding techniques is slow, hazardous and expensive. As a result , interest has been generated in the application of remote sensing techniques at last in the critical shallow areas which are frequently used by ships approaching or leaving ports or harbours. Satellites can provide an extremely effective means of carrying out preliminary surveys over wide areas, especially in remote regions. Ships need then be used only in those areas where closer investigation is indicated and in this way the sending of ships on unproductive surveys may frequently be avoidea. In the preparation of hydrographic charts satellite data may be used to fill in contours between lines of ship soundings and may reduce the number of soundings required and hence the cost. Furthermore, because of the frequent over flights satellites provide an effective means of monitoring changes to the coast and seabed. The possibility of using remote sensing technology was addressed as early as the late 1960s (Brown et al. 1971) These studies led to the NASA/ Cousteau Ocean Bathymetry Experiment in 1975 which demonstrated the feasibility of using Landsat high-gain multispectral scanner (MSS) data in bathymetry ( Polcyn 1976 ). Since then, a number of studies have been carried out. 2. Case Study – Pulau Tioman The study was carried out on the coastal waters of Pulau Tioman, Malaysia Using the Landsat-5, Thematic Mapper data. The waters in this areas is very clear with Secchi disk readings of about 40 m. The study area is as shown in Figure 1. The image was acquired on 1 April 1990 at about 02.50 GMT by the Landsat-5, satellite when the height of the tide was 1.5 m above lowest astronomical tide. The satellite data on abn 1 ( 0.45 – 0.52mm) was used to compute water depths since it has the best depth penetration capability. Figure 1. Location map of study area In the following sections, geometrical rectification of satellite data, depth algorithm used and some results that were obtained are presented. 2.1 Geometrical Rectification of Satellite Data The satellite data used in the study was geometrically rectified to enable quantitative comparison to be made between the remotely – sensed image and existing maps and charts. This was achieved by carrying out an image-to-image registration on the Dipix ARIES-III Image Analysis System between a scanned hydrographic chart of Pulau Tioman and the corresponding Landsat-5 TM image at the Centre for Remote Sensing, UTM. The rectification was carried out to subpixel accuracy. 2.2 Method of Depth Determination and Depth Algorithms For the remotely-sensed data used in the study, pixel intensities ( digital numbers ) were extracted at some points of known depth ( calibration depths ) in order to fit algorithms relating pixel intensities to the depth. The depths at the calibration points were determined on-site by lead-line measurements at the time of satellite pass while the positions of these points were obtained by sextant resection to some ground control points. These points were plotted on the hydrographic chart prior to scanning on the Dipix ARIES-III System so that upon registration to the Landsat-5 image, it was possible to extract the pixel intensities at these points. A simple algorithm based on the model of Polcyn and Lyzenga ( 1975) was used , i.e. I – A1 + A2 Exp ) A3Z) (1) Equation ( 1) can usefully be expressed in the alternative form as follows. Z = [ In(A2) – In ( I – A1)] A3 (2) These equations express the expected exponential relationship between pixel intensity I and depth Z. The coefficients A1, A2 and A3 describe the parameters outlined by the model of Polcyn and Lyzenga ( 1975). The coefficient A1 in particular, describes the effects due to the atmosphere which in most cases contribute about 50-80% of the total signal received by the satellite sensor. Therefore, a program was written specifically to calculate and correct the satellite data from the effects. The coefficient of Markham and Barker ( 1986). Equation (2) can now be written as follows, A=[In (A2) – In ( Icorr )] / A3 (3) Where Icorr are the pixel intensities corrected for atmospheric effects. A least-squares minimization was carried out relating the corrected pixel intensities Icorr to depth at nine calibration points in order to obtain the best values of the coefficients A2, and A3 in equation (3) Table 1 lists the values of depths and their corresponding corrected pixel intensities at the nine calibration points used in the least squares minimization. Having determined the coefficients, the depth at any point on the image was obtained by using the values of these coefficients and the corrected pixel intensity values at this point from the relevant spectral band, i.e. band 1 of the satellite data. 3. Results A plot of corrected pixel intensity ( band 1) versus depth as shown in Figure 2 gives an exponential relationship. This shows that is a good correlation between the pixel intensities and water depths for hydrographic charting in the study area. Comparisons of calculated depths with in – situ measured depths at seven check points indicate an error of 0.5 – 2.0 m in depths of up to 50 m of water ( refer Table 2). Figure 3 and 4 show the hydrographic charts obtained from conventional techniques and from the Landsat-5 TM digital satellite data respectively. Figure 2. Plot of corrected pixel intensity versus depth Figure 3. Hydrographic chart from conventional techniques (1960) Figure 4. Hydrographic chart derived from Landsat-5 TM satellite data (1990) Table 1: Least Squares Minimization at Depth Calibration Points Meas. Depths (m)(Z) Corrected Pixel Intensities( Icorr) 50 2.5 12 23 46 38 28 34 3 35 60 51 43 36 39 41 40 59 Table 2: Comparison Between Measured and Calculated Depths at Check Points Points No. Meas. Depth(m) Calc. Depth(m) 1 3 4 6 8 14 16 28 32 35 47 33 30.5 2 28 34 37 46 34 30 1 4. Discussions and Conclusions The root-means-square deviation value of the calculated depths is 1.287 m in about 50 m of water which is about 2.5% of the water depth. The depth accuracy requirement are 30 cm for depths up to 30 m , 1 m for depths from 30 m to 100 m and 1% of the depth for deeper than 100 m according to the accuracy standards recommended for hydrographic surveys by the International Hydrographic Organization. The results obtained in this study and other studies ( Ibrahim 1989) indicate that these accuracy requirements are difficult to achieve by remote sensing techniques. However, the hydrographical chart derived from the Landsat-5, TM satellite data show many similities with the corresponding hydrographic chart derived from the Admiralty hydrographic charts despite the large difference in the dates of field survey and satellite data acquisition ( 1960 and 1990 ). This shows that in areas where the water clarity is good, satellite data can be used to obtained some general idea on the depth contours. Acknowledge The authors wish to thank the Research and Consultancy Unit of Universiti Teknologi Malaysia for providing the funds to conduct this research work. References Brown, W.L., Polcyn, F.C., and Stewart, S.R., 1971, A Method for Calculating Water Depth, Attenuation Coefficients, and Bottom Reflectance Characteristics. Proceedings of the 7th International Symposium on Remote Sensing of Environment, ERIM, Ann Arbor, Michiga, 663-682. Ibrahim, M., 1989 Water Depth Determination From Satellite Data. Proceedings of the 10th Asian Conference on Remote Sensing, Kuala Lumpur. Markham, B.L., and Barker, J.L. 1986, Landsat MSS and TM Post Calibration Dynamic Ranges, Exoatmospheric Reflectances and At-Satellite Temperatures. EOSAT Landsat Technical Notes No. 1, EOSAT, Lanham, Maryland. Polcyn, F.C. , 1976, Final Report on NASA/ Cousteau Ocean Bathymetry Experiment : Remote Bathymetry Using High-gain Landsat Data. NASA-CR-ERIM Report No. 119500-1-F. Polcyn, F.C., and Lyzenga, D.R., 1975, Remote Bathymetry and Shoal Detection With ERTS: ERTS Water Depth. ERIM Report No. 193300-51-F.