Abstract
The bathymatric mapping is very important in various coastal studies such as biotrops inventory, animal or vegetation resources management, and pollution impact assessment. However, bathymetric surveying at shallow water areas by conventional shipboard sounding techniques is slow and dangerous and needs expensive devices such as a sonar and a ship with very shallow draught. Since the solar radiation penetrates to about 50 m in depth, particularly in clear water such as in coral reefs ecosystem or clear oceanic water, it is possible to extract the bathymertric information by using remote sensing data.
This study describes the application of satellite remote sensing data for estimation and mapping of water depth. Remotely sensed bathymetry in the vicinity of the Kin Bay, Okinawa Main Island, Japan is performed and compared by using single, multi and bottom feature models. In these models, it was assumed that the ratio of bottom reflectance is the same for all points in the scene. For depth estimation, the constants values in the used models are computed by means of a multiple linear regression. Depth data ranged between 1 and 34 m at total of 377 and 374 points of Landsat-5 TM and SPOT-1 HRV imageries, respectively are extracted from a smooth sheet of survey charts received by JODC (Japan Oceanographic Data Center). The bottom feature model proposed in this paper yields a root mean square (r. m. s.) error of 3.07 and 2.67 m for TM and HRV, respectively. Based on this model, the 3-dimensional color imageries for TM and HRV sensors are derived and mapped by personal computer techniques.
