Detecting urban growth using remote sensing and GIS techniques in Al Gharbiya governorate, Egypt

Tanta and Quttour are the important districts in Al Gharbiya governorate, Middle of Nile Delta, Egypt. Urban sprawl is one of the main problems that reduce the limited highly fertile land in the Nile Delta of Egypt. Computational urban growth and computer hardware had made possible unprecedented increase in the availability and provide information inputs to planners. Remote sensing technology has shown its great capabilities to solve many earth resources issues. The aim of this study is to produce land use and cover map for the studied area at varied periods to monitor possible changes that may occurred, particularly in the urban areas and agriculture and subsequently predict likely changes. Two land sat images, Multispectral Scanner (MSS) in the 1972 and Enhanced Thematic Mapped (ETM) in the 2005 were used to assess the changes of agricultural lands, urban encroachment and water areas during this period with integration by GIS. The agricultural areas in Tanta and Quttour decreased by 7.17% and 5.84%, respectively from the year 1972 to 2005, while the urban areas increased by 7.17–5.84%, respectively. This urban expansion causes loss of productive agricultural lands. Finding data is useful for decision maker to investigate and monitoring illegal use of agricultural land in Nile Valley and Delta

Sustainability indicators for agricultural land use based on GIS spatial modeling in North of Sinai-Egypt

Sustainable agriculture focuses on production that renews resources. Egypt has a lot of sustainability constraints such as salinity and alkalinity, lack of infrastructure and credit utilization. The current study focuses on assessment of sustainability factors for agricultural utilization through integrated biophysical, economic viability and social acceptability in the North Sinai area. Sustainable agricultural spatial model (SASM) was developed using Arc GIS 10 to identify and classify the area, according to sustainability degree of agricultural utilization, where the factors of productivity, security, protection, economic viability, and social acceptability in the different mapping units were assessed. The investigated area is classified into three different classes, I, II, are covered in about 7% of the total area where land management practices are marginally below the threshold for sustainability located in the northern part of the study area, where the sustainability values are ranging between 0.1 and 0.3. The areas characterized as class III do not meet sustainability requirements where the sustainable values <0.1. The current work shows how the decision-makers can increase the land sustainability classes I, II to 10% of the total area by controlling just two factors: social and economic factors

Towards a Dynamic Optimal Alphabetic Tree

Binary trees have a wide variety of applications in computer science and information systems. Fast algorithms for building all kinds of binary trees in O(n log n) time do exist. However, no existing algorithm makes it possible to insert in (or delete from) the tree without losing its optimality. In this paper, we propose an algorithm to insert into or delete from a weighted binary alphabetic tree in linear time keeping the tree optimal after insertion or deletion. We show that both insertion and deletion of a node can be done in O(n) time provided its weight is not bigger than the higher weight of its two neighbouring nodes. This algorithm makes it possible to have a dynamic optimal alphabetic tree with reasonable complexity. Key words : Optimal alphabetic trees,insertion and deletion ,linear time alphabetic trees. 1 Introduction Binary trees have received a considerable attention in computer science research. It saves a lot of time to search for data stored in a binary tree structur..

Vis‐nir spectroscopy and satellite landsat‐8 oli data to map soil nutrients in arid conditions: A case study of the northwest coast of egypt

The mapping of soil nutrients is a key issue for numerous applications and research fields ranging from global changes to environmental degradation, from sustainable soil management to the precision agriculture concept. The characterization, modeling and mapping of soil properties at diverse spatial and temporal scales are key factors required for different environments. This paper is focused on the use and comparison of soil chemical analyses, Visible near infrared and shortwave infrared VNIR‐SWIR spectroscopy, partial least‐squares regression (PLSR), Ordinary Kriging (OK), and Landsat‐8 operational land imager (OLI) images, to inexpensively analyze and predict the content of different soil nutrients (nitrogen (N), phosphorus (P), and potassium (K)), pH, and soil organic matter (SOM) in arid conditions. To achieve this aim, 100 surface samples of soil were gathered to a depth of 25 cm in the Wadi El‐Garawla area (the northwest coast of Egypt) using chemical analyses and reflectance spectroscopy in the wavelength range from 350 to 2500 nm. PLSR was used firstly to model the relationship between the averaged values from the ASD spectroradiometer and the available N, P, and K, pH and SOM contents in soils in order to map the predicted value using Ordinary Kriging (OK) and secondly to retrieve N, P, K, pH, and SOM values from OLI images. Thirty soil samples were selected to verify the validity of the results. The randomly selected samples included the spatial diversity and characteristics of the study area. The prediction of available of N, P, K pH and SOM in soils using VNIR‐SWIR spectroscopy showed high performance (where R2 was 0.89, 0.72, 0.91, 0.65, and 0.75, respectively) and quite satisfactory results from Landsat‐8 OLI images (correlation R2 values 0.71, 0.68, 0.55, 0.62 and 0.7, respectively). The results showed that about 84% of the soils of Wadi El‐Garawla are characterized by low‐to‐moderate fertility, while about 16% of the area is characterized by high soil fertility. © MDPI AG. All rights reserved

Polychlorinated biphenyl, polychlorinated dibenzo-p-dioxin and polychlorinated dibenzofuran residues in sediments and fish of the River Nile in the Cairo region.

The levels of organohalogenated contaminants, i.e. PCBs, PCDDs and PCDFs were determined in sediment and fish samples collected from different locations in the River Nile, Egypt. Thirty-six sediment and eighteen fish samples were carried out during a period of 12 months from February 2003 to February 2004. Determination of PCBs and dioxins was carried out using a high resolution GC mass spectrometer. The results indicated that the PCB and PCDD/F mean concentrations in sediment samples ranged from 1461 to 2244 and from 240 to 775 pg g-1 dry wt basis, respectively. The mean concentration of PCBs and PCDD/Fs in fish samples were found to be in the range from 695 to 853 pg g-1 fresh wt for PCB congeners and from 27.7 to 121 pg g-1 lipid for total PCDD/Fs. Moreover, the concentrations of both PCBs and PCDD/Fs were found to be different at different locations along the River Nile. It could be concluded that the contamination of the River Nile is within the permissible limits set by the FDA and the Egyptian Standards for fish and shellfish

Wideband and flat-gain amplifier using high concentration Erbium doped fibers in series double-pass configuration

A wide-band and flat gain Erbium-doped fiber amplifier (EDFA) is demonstrated using a gain media of high concentration Silica-based erbium doped fiber (EDF). The amplifier has two stages comprising a 1.5 m and 9 m long EDF optimized for C-band and L-band operations respectively, in a double-pass series configuration. The CFBG is used in both stages to allow a double propagation of signal and thus increases the attainable gain in both C- and L-band spectra. At an input signal power of -30 dBm, a flat gain of 22 dB is achieved with a gain variation of ±3 dB within a wide wavelength range from 1530 to 1600nm. The corresponding noise figure varies from 4 to 8 dB within this wavelength region

Crop Yield Prediction Using Multi Sensors Remote Sensing (Review Article)

Pre-harvest prediction of a crop yield may prevent a disastrous situation and help decision-makers to apply more reliable and accurate strategies regarding food security. Remote sensing has numerous returns in the area of crop monitoring and yield prediction which are closely related to differences in soil, climate, and any biophysical and biochemical changes. Different remote techniques could be used for crop monitoring and yield prediction including multi and hyper spectral data, radar and lidar imagery. This study reviews the potentialities, advantages and disadvantages of each technique and the applicability of these techniques under different agricultural conditions. It also shows the different methods in which these techniques could be used efficiently. In addition, the study expects future scenarios of remote sensing applications in vegetation monitoring and the ways to overcome any obstacles that may face this work. It was found that using satellite data with high spatial resolution are still the most powerful method to be used for crop monitoring and to monitor crop parameters. Assessment of crop spectroscopic parameters through field or laboratory devices could be used to identify and quantify many crop biochemical and biophysical parameters. They could be also used as early indicators of plant infections; however, these techniques are not efficient for crop monitoring over large areas