Nile River, the longest river in the world, 6,695 km long from its remotest headstream, the Luvironza River in Burundi, central Africa, to its delta on the Mediterranean Sea, NE Egypt. The Nile River islands form an attractive agricultural area characterized with its nightly fertile soils, easy source, and its suitability to a wide range of land use. The present use of these Nile islands does not reach the maximum capability of these resources due to improper land use of these areas.The current study aims at identifying the changes of the Nile course and its islands during the last three decades using remote sensing and GIS techniques in order to provide the scientific bases, which help in planning the most suitable programs of land use, soil management and conservation. Six MSS, eight TM and Eight ETM+ satellite images dated to 1972,1984 and 2002 respectively were used to study the changes occurred during the above-mentioned periods. The study area was divided into five sectors along the Nile River course i.e. Aswan – Qena, Qena - Assiut , Assiut - Qalubia , Qalubia - Damietta and Qalubia – Rosetta . The changes in Nile course from early seventieth to middle eighteenth were decreased by 51.34 Km<sup>2</sup>, from middle eighteenth to the millennium were decreased by 40.30 Km<sup>2</sup>. The overall change in Nile course area decreased by 91.64 Km<sup>2</sup> in the investigation period. Belonging to the islands number and their areas in the investigation period, the changes in islands number from early seventieth to middle eighteenth were increased by 171 islands, from middle eighteenth to the millennium were decreased by 86 islands. Meanwhile, the islands areas from early seventieth to middle eighteenth were decreased by 4512.39 Feddan., from middle eighteenth to the millennium were decreased by 5446.97 Feddan. The overall change in the investigation period for the total number of the islands was increased by 85 islands, meanwhile the islands areas were decreased by 9959.36 Feddan. Changes of soil characteristics of some islands were recognized. It is found that, there is no regular pattern of the changes that related to soil characteristics due to many reasons i.e. differences in human agricultural practices, differences in Nile deposition, which differ from year to year, and differences in Nile water levels. Conservation and management program was suggested for the optimum use of these islands.
The main objective of the current work is to recognize the dominant and predominant clay minerals of South Port Said plain soils, Egypt using the high advanced remote sensing techniques of hyperspectral data. Spectral analyses as one of the most advanced remote sensing techniques were used for the aforementioned purpose. Different spectral processes have been used to execute the prospective spectral analyses. These processes include 1-The reflectance calibration of hyperspectral data belonging to the studied area, 2- Using the minimum noise fraction (MNF) transformation. 3 -Creating the pixel purity index (PPI) which used as a mean of finding the most "spectrally pure", extreme, pixel in hyperspectral images. Making conjunction between the Minimum Noise Fraction Transform (MNF) and Pixel Purity Index (PPI) tools through 3-D visualization offered capabilities to locate, identify, and cluster the purest pixels and most extreme spectral responses in a data set. To identify the clay minerals of the studied area the extracted unknown spectra of the purest pixels was matched to pre-defined (library) spectra providing score with respect to the library spectra. Three methods namely, Spectral Feature Fitting (SFF),Spectral Angle Mapper (SAM) and Binary Encoding (BE) were used to produce score between 0 and 1, where the value of I equal a perfect match showing exactly the mineral type. In the investigated area four clay minerals could be identified i.e. Vermiculite, Kaolinite, Montmorillinite, and Illite recording different scores related to their abundance in the soils. In order to check the validity and accuracy of the obtained results, X-ray diffraction analysis was applied on surface soil samples covering the same locations of the end-members that derived from hyperspectral image. Highly correlated and significant results were obtained using the two approaches (spectral signatures and x-ray diffraction).
El-Qaa plain lies in the southern part of Sinai Peninsula extending along the Gulf of Suez. It occupies an area of about 3300 km2. El-Qaa plain is suffering from seasonal flashflood that can roll boulders, tear out trees, destroy local people buildings, and scour out new channels. Flashfloods are among the most frequent and costly natural disasters in terms of human hardship and economic loss. Terrain units of ElQaa plain were interpreted by draping satellite ETM+ image over Digital Terrain Model (DTM).These units could be categorized into sand sheet, outwash plain, inter-ridged sand flat, wadi bottom, wadi outlet, dry valley, delta,dry &wet sabkhas, ridge, rocky hill, cuesta, peniplain, rockoutcrop, footslope, bajada & alluvial fans, inclined lime stone, marine spits & heads and water bodies. On the other hand soils of ElQaa plain were classified into the following sub groups: Calcic Haplosalids, Gypsic Haplosalids, Lithic Haplocalcids, Lithic Torripsamments, Typic Aquisalids, Typic Haplodurids, Typic Torripsamments, and Typic Haplocalcids. Arc Hydro Model was used with the aid of DTM for deriving slope, flow direction, basins, flow length and flow accumulation. These derivations influence directly the flashflood behavior. Universal Soil Loss Equation (RUSLE) was used to estimate soil loss in ElQaa plain using GIS spatial analyses. The minimum mean soil loss belonging to water erosion was determined by 1.23 ton\hectare\year, meanwhile the maximum one was estimated by 5.08 ton\hectare\year. Alternative management and potential cropping system was suggested to adequate conservation measures in farm planning system of ElQaa plain. These measures could be grouped under 1-Selection of appropriate landuse. 2-Maintaining organic matter. 3-Reducing tillage. 4-Using zero tillage or direct seeding. 5-Growing forages and using crop rotations.