Estimating of the depth in coastal and shallow waters plays an important role in management and exploration of marine natural resources. Collection and production of this geospatial information is the initial step in any planning and development activities. Direct measurement of water’s depth and physical parameters, using field methods in coastal areas is normally costly and relatively time consuming. As an alternative, remote sensing technology can collect the observations in a short time and in a large geographic extent. This subject, in a country like Iran, with vast offshore, has a particular importance.In the past decades, using satellite earth observations for bathymetry in shallow waters is significantly increased. This has been mainly because of the potential of remote sensing data provided by satellite sensors, with proper spectral, spatial and temporal resolution, satellite
The main purpose of this paper is to examine the capabilities of hyperspectral satellite imagery for bathymetry applications. To this end, one of the most well-known and frequently used empirical models,i.e.Stumpf is implemented and evaluated.
Stumpf (2003) proposed an algorithm to estimate the water depth from multi-spectral images. This algorithm is based on the relative amount of reflection in the visible bands and leads better results in comparison to other methods. The problem is caused by the different type of substrates and is applicable in areas with low reflectivity.
The proposed method is applied to a hyperspectral dataset acquired by Hyperion sensor on board of EO1 satellite. The image covers the shallow water in the north coast of Qeshm island. The results of experimental analysis show that the correlation between the image that are analyzed and the stumpf algorithm are applied on and the real depth values is 89.3% and the standard deviation is 1.38 meter for special applications which in coastal areas, according to the cost and processing time can be a suitable technique.
H. R. Avarideh, A. R. Safari, S. Homayouni, S. Khazaei. Nearshore bathymetry using hyperspectral remotesensing. GEJ 2015; 6 (1) :1-10 URL: http://gej.issgeac.ir/article-1-28-en.html