Antonio Crespo Martínez

An oil spill monitoring system based on SAR images

Abstract Oil pollution produced by natural or human causes is of great importance to both the environment and the economy, and it is a subject of increasing public concern. This paper presents a project for the development of a low cost demonstrator system for the detection of marine oil spills. The system is based in the analysis of satellite SAR images. SAR images are presently the only reliable remote sensing data suitable for the purpose. The main functionalities of the system include SAR raw data preprocessing, quick-look image generation and analysis, full resolution image generation and analysis and report compilation.

Parallel algorithms for high-speed SAR processing

The mass production of SAR products and its usage on monitoring emergency situations (oil spill detection, floods, etc.) requires high-speed SAR processors. Two different parallel strategies for near real time SAR processing based on a multiblock version of the Chirp Scaling Algorithm (CSA) have been studied. The first one is useful for small companies that would like to reduce computation times with no extra investment. It uses a cluster of heterogeneous UNIX workstations as a parallel computer. The second one is oriented to institutions, which have to process large amounts of data in short times and can afford the cost of large parallel computers. The parallel programming has reduced in both cases the computational times when compared with the sequential versions.

PARSAR: Parallelisation of a Chirp Scaling Algorithm SAR Processor

A parallel SAR processor is presented in this paper. The target configuration is a cluster of UNIX workstations, available in most user sites. This fact allows to obtain an increased computing performance without the need of dedicated hardware investment.