부산대학교 도서관

In this article a new method is introduced for the automatic estimation of all the relevant parameters of oil storage tanks using a single high-resolution synthetic aperture radar (SAR) image. For a given storage tank, this method will estimate its maximum capacity and determine whether it has a fixed or a floating roof. For tanks with a floating roof, the amount of oil stored will also be estimated. If a SAR time series is available all the images can be processed jointly, exploiting the available temporal information to provide more accurate and robust estimates than those obtained from each individual image. The dimensions of each storage tank are derived from its semicircular double reflections, which are detected using the coherent scatterers in the SAR image. The classification between tanks with fixed and floating roofs is performed with a simple machine learning classifier using just three features related to the detected semicircular double reflections. The performance of the proposed method using a single image and a time series is evaluated with three TerraSAR-X images of the port of Rotterdam, containing 167 oil storage tanks of different sizes, and with both fixed and floating roofs.