Many outdoor images contain sky. The sky detection and segmentation is important for image enhancement, horizon detection, and obstacle avoidance in unmanned air vehicles. Most researches in sky detection and segmentation are for blue sky only. Our work is proposed to detect and segment three categories of skies: blue sky, cloudy sky, and sunset sky. There are two types of sky detection methods: pixel based detection and block based detection. The main advantage of pixel based detection is the high correct detection ratio. There are many descriptors used in object detection such as color descriptors, color-shape descriptors, and shape descriptors. This work studies sky detection and segmentation with defferent descriptor types. The sky is classified into blue sky, cloudy sky, and sunset sky. For each sky type, the sky is detected using pixel based detection and block based detection. We improve the sky detection ratio using K-HSV descriptors. The sky detection with K-HSV descriptors has 86.16% correct ratio for blue sky. We decrease The number of keypoints used in sky segmentation to 200 random selected keypoints of all dense sampling keypoints. The sky segmentation based on 200 color moment invariant descriptors obtained 78.25% for blue sky, 61.63% for cloudy sky, and 62.27% for sunset sky.

The sky is an essential component in outdoor images. Sky and cloud type classification has applications in many areas such as image enhancement and sky image retrieval. In this paper, we improve the sky and cloud type classification rate over existing methods. Our work is based on two classification stages: sky image classification stage and sky cloud type classification stage. In sky classification stage, the image is classified into blue sky, cloudy sky, and sunset sky. Due to the impact of descriptor selection in the sky classification, we investigate ten descriptors; we show that the classifiers based on color descriptors are more accurate than the classifiers based on shape descriptors in sky type classification. We improve the sky image classification ratio using K-HSV descriptors. The sky classification with K-HSV descriptors has 77.3% correct classification rate. In cloud type's classification stage, the cloud is classified based on the sky type. For both the blue sky and the sunset sky, the cloud type is classified into six types: cloudless, thin-cirrus, cirrus, cirrocumulus, cumulus, and cumulonimbus. In cloudy sky, the cloud type is classified into three types: stratus, stratocumulus, and altostratus. The clouds are classified based on their shape and color using Gist minimum distance classification. The average correct classification rate of the clouds classifier is over 85% for cloudless, cumulus clouds, and stratus clouds and over 60% for thin-cirrus, cumulonimbus, stratocumulus, and altostratus clouds.

The sky is an essential component in outdoor images. Sky and cloud type classification has applications in many areas such as image enhancement and sky image retrieval. In this paper, we improve the sky and cloud type classification rate over existing methods. Our work is based on two classification stages: sky image classification stage and sky cloud type classification stage. In sky classification stage, the image is classified into blue sky, cloudy sky, and sunset sky. Due to the impact of descriptor selection in the sky classification, we investigate ten descriptors; we show that the classifiers based on color descriptors are more accurate than the classifiers based on shape descriptors in sky type classification. We improve the sky image classification ratio using K-HSV descriptors. The sky classification with K-HSV descriptors has 77.3% correct classification rate. In cloud type's classification stage, the cloud is classified based on the sky type. For both the blue sky and the sunset sky, the cloud type is classified into six types: cloudless, thin-cirrus, cirrus, cirrocumulus, cumulus, and cumulonimbus. In cloudy sky, the cloud type is classified into three types: stratus, stratocumulus, and altostratus. The clouds are classified based on their shape and color using Gist minimum distance classification. The average correct classification rate of the clouds classifier is over 85% for cloudless, cumulus clouds, and stratus clouds and over 60% for thin-cirrus, cumulonimbus, stratocumulus, and altostratus clouds.

A resistivity survey was conducted in the Nile Delta area to delineate ground-water contamination caused by an improper sewage and irrigation drainage system, leaching from old lagoonal deposits, and salt-water intrusion. Existing monitoring wells were used to measure the horizontal and vertical variations in water salinity. Vertical electrical sounding (VES) data for sounding points located near monitoring wells, together with the water salinity data of these wells, were used to obtain an empirical relationship between the inferred earth resistivity and the amount of total dissolved solids. This relationship was used together with the constructed apparent resistivity depth and geoelectric longitudinal sections to identify three zones of water-bearing formation (fresh-, brackish-, and salt-water zones). Along the studied profile, depth to the fresh-brackish interface exceeds 150 m at Tanta City and decreases northward to 40 m or less between Qutor and Kafr El-Sheikh. Depth to the brackish-saline interface exceeds 180 m south of Kafr-El-Sheikh and decreases northward to 70 m near Hadadi village.

A resistivity survey was conducted in the Nile Delta area to delineate ground-water contamination caused by an improper sewage and irrigation drainage system, leaching from old lagoonal deposits, and salt-water intrusion. Existing monitoring wells were used to measure the horizontal and vertical variations in water salinity. Vertical electrical sounding (VES) data for sounding points located near monitoring wells, together with the water salinity data of these wells, were used to obtain an empirical relationship between the inferred earth resistivity and the amount of total dissolved solids. This relationship was used together with the constructed apparent resistivity depth and geoelectric longitudinal sections to identify three zones of water-bearing formation (fresh-, brackish-, and salt-water zones). Along the studied profile, depth to the fresh-brackish interface exceeds 150 m at Tanta City and decreases northward to 40 m or less between Qutor and Kafr El-Sheikh. Depth to the brackish-saline interface exceeds 180 m south of Kafr-El-Sheikh and decreases northward to 70 m near Hadadi village.

A numerical time-dependent groundwater model of the Nubian Sandstone Aquifer in Egypt is presented. A complete database of the hydrogeological and drilling information of 850 water wells drilled in the period 1960-2000 was evaluated and used for the model parameter input as well as for its calibration. A steady-state condition is rejected even for the pre-development time as the subsurface inflow across the Egyptian/Sudanese borders is lower than discharge, and the observed hydraulic gradient is residual gradient and not due to steady-state flow. The results of the long-period simulation (10,000 years) indicated that the Nubian Sandstone Aquifer is still under the influence of the past humid period and has been in an unsteady deplenishing process. Therefore, groundwater development plans should be based on this concept. The calibrated model was used to investigate the hydrodynamic impacts of the present and planned groundwater extraction on the potentiometry of the aquifer. The simulation results indicate that there is a real danger of groundwater depletion, particularly in the shallow aquifer in some areas. In fact, if the planned extraction of 1,200 million m3/year in East Oweinat area is imposed, drawdown after 100 years could be as much as 200 m relative to1960s levels. By this time the cone of depression will extend to Dakhla and Kharga oases.