Experimental investigation of motion behavior in irregular wave and site selection analysis of a hybrid offshore renewable power station for Egypt

The majority of the population living in coastal remote areas does not have access to energy sources in Egypt. Development of living standards in such areas without infrastructure can be achieved through floating power stations. Novel cylindrical power station powered by hybrid marine renewable resources is proposed to overcome energy shortage in such areas. The objective of the present study is to experimentally evaluate the motion behaviour of the proposed concept in different load conditions for critical environmental loads in order to obtain model characteristic data which is critical in the structure's verification and other post-analysis study. Furthermore, selecting suitable deployment site for the proposed concept was performed based on integrated geographical information systems and multi-criteria decision model considering the potential of renewable sources in Egypt. The experimental test was conducted using 1:100 model-scale in irregular wave which is a more realistic condition in order to check the operational safety among critical conditions. The site selection analysis show that Marsa Alam area has the highest priority to place the proposed concept. Moreover, the time-domain analysis results indicate that the proposed concept can safely operate in the selected deployment area subjected to environmental loads

GIS AND REMOTE SENSING IN ESTIMATION OF THE AGRICULTURE LANDS INFRINGEMENT, CASE STUDY: KOM HAMADA, BEHIERA

The paper aims to assess agricultural land infringement using satellite images by applying three methods of classification: supervised (maximum likelihood), unsupervised and normalized difference vegetation index. To determine which sets of remote sensing satellite images were the best, they were compared. During the monitoring periods (2010–2011 and 2020–2021), Beban village is used as a study area. Landsat 8, Sentinel 2, Aster, and Modes satellite images are used to generate the remote sensing data. This period has been selected to classify images in order to assess land cover changes and the infringement of agricultural lands within Beban village and Kom Hamada center. The proposed methods employ the multi-spectral remote sensing data technique for land cover classification, with the selection of a satellite image dependent on the comparisons between the data quality of each satellite image downloaded for the study area. For land cover classification, some band combinations of the remotely sensed data are exploited, and the spatial distributions such as urban areas, agricultural land, and water resources are interpreted. The results give two important points: the Landsat 8 OLI/TIRS sensor is the best when compared with the other satellite, and the second point for the percentage of agricultural land in the study area in 2020, 2015, and 2010 was estimated to be 77.76%, 78.88%, and 84.04%, respectively. That is, agricultural land infringement accounted for 6.28% of Beban Village's total area