Incidence of mayfly (Povilla sp.) infestation of wooden infrastructures of artisanal fishers in the lagoon and marine fisheries locations of Ogun State, Nigeria

A diagnostic survey of the incidence of mayfly (Povilla sp.) infestation of wooden infrastructures of the artisanal fishers in ten (10) lagoons and marine fishing villages of Ogun States (Nigeria) was carried out through the application of structured questionnaire and participatory Rural Appraisal interviews. The demographic, infrastructural and socioeconomic characteristics of the ten fishing villages sampled were derived and analyzed. The infestation which occurs all year round is found to be most prevalent (70%) in the wet season, increasing proportionally with salinity from 56% (brackish water); to 63% (marine water). The life-span of Povilla sp. is reduced from 55% to 62% (freshwater); 41% (brackish water) and 38% (marine water). Annual financial loss of N10,000.00 per fisher or N80,000,000.00 to the 8000 artisanal fishers affected in Ogun State is discussed. It is recommended that fishers should preferably use non-wood crafts and infrastructures while adopting appropriate management strategies for containing the existing infestation

Impacts of Climate Change on European Critical Infrastructures: The Case of the Power Sector

23 p.

Fast model based feature matching technique applied to airport lighting

The use of image processing techniques to assess the performance of airport landing lighting using images of it collected from an aircraft-mounted camera is documented. In order to assess the performance of the lighting, it is necessary to uniquely identify each luminaire within an image and then track the luminaires through the entire sequence and store the relevant information for each luminaire, that is, the total number of pixels that each luminaire covers and the total grey level of these pixels. This pixel grey level can then be used for performance assessment. The authors propose a robust model-based (MB) featurematching technique by which the performance is assessed. The development of this matching technique is the key to the automated performance assessment of airport lighting. The MB matching technique utilises projective geometry in addition to accurate template of the 3D model of a landing-lighting system. The template is projected onto the image data and an optimum match found, using nonlinear least-squares optimisation. The MB matching software is compared with standard feature extraction and tracking techniques known within the community, these being the Kanade–Lucus–Tomasi (KLT) and scaleinvariant feature transform (SIFT) techniques. The new MB matching technique compares favourably with the SIFT and KLT feature-tracking alternatives. As such, it provides a solid foundation to achieve the central aim of this research which is to automatically assess the performance of airport lighting.