Land resources assessment of El-Galaba basin, South Egypt for the potentiality of agriculture expansion using remote sensing and GIS techniques

The socio-economic development in Egypt is based on land resources. Recently, the Egyptian government is interested in developing low desert zone areas which are located between the recent Nile flood plain and the limestone plateau, from the east and west sides, and represent an important source of aggregate materials. Therefore, this study was carried out to investigate the potentiality of El-Galaba basin soils which are located in the western part of the Aswan Governorate and are characterized by Wadi El-Kubbaniya for the horizontal agricultural expansion and their optimum agricultural use. The investigated area was remotely sensed to identify the landscape and its land resources. Terrain units were identified using draped Landsat 8 satellite image over Digital Terrain Model (DTM) to express the landscape and the associated soil mapping units. Fifteen mapping units were identified and grouped. Land capability evaluation was performed using Cervatana capability model. The results of capability modeling revealed about 3.33% of land with good use capability, 76.06% land with moderate use capability, and 0.08% marginal or non-productive land. The main capability limitations were soil and erosion risks. The Almagra model was used to produce the optimum cropping pattern and limitations of soil units. Matching the crop requirements with soil characteristics, optimum cropping pattern was obtained for wheat, corn, melon, potatoes, sunflower, sugar beet, Alfalfa, peach, citrus, and olive. The results of the study revealed the potentiality of El-Galaba basin for agricultural uses

Application of near-infrared reflectance for quantitative assessment of soil properties

Beginning with a discussion of reflectance spectroscopy, this article attempts to provide a review on fundamental concepts of reflectance spectroscopic techniques. Their applications as well as exploring the role of Near-infrared reflectance spectroscopy that would be used for monitoring and mapping soil characteristics. This technique began to be used in the second half of the 20th century for industrial purposes. Moreover, this article explores the potentiality of predicting soil properties based on spectroscopic measurements .Quantitative prediction of soil properties such as; salinity, organic carbon, soil moisture and heavy metals can be conducted using various calibration models – such models were developed depending on the measured soil laboratory analyses data and soil reflectance spectra thereby resampled to satellite images - to predict soil properties. The most common used models are stepwise multiple linear regression (SMLR), partial least squares regression (PLSR), multivariate adaptive regression splines (MARS), principal component regression (PCR) and artificial neural networks (ANN). Those methods are required to quickly and accurately measure soil characteristics at field to improve soil management and conservation at local and regional scales. Visable-Near Infra Red (VIS-NIR) has been recommended as a quick tool for mapping soil properties. Furthermore, VIS-NIR reflection spectroscopy reduces the cost and time, therefore has a wonderful ability and potential use as a rapid soil analysis for both precision soil management and assessing soil quality. Keywords: Near infrared spectroscopy, Soil salinity, Soil moisture, Soil organic carbon, Soil surface features and soil contaminatio