Using Landsat imagery interpretation for underground water prospection around Qena Province, Egypt

Salman, Abdel Aty B.

doi:10.1080/01431168308948539

Cited by 16 publications

(3 citation statements)

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“…Though, because of considering lineament and drainage as a part of lithology some hydrogeologist (Edet et al 1998) neglected this factor. But others (Salman 1983;Shaban et al 2006;Magesh et al 2012;Acharya and Nag 2013) incorporate the lithology factor because of its strong influence on water percolation. It is because of this reason the present study considers lithology as an important factor to minimize the errors instead of using lineaments and drainage factors alone.…”

Section: Lithologymentioning

confidence: 99%

Mapping of groundwater potential zones in hard rock terrain using geoinformatics: a case of Kumari watershed in western part of West Bengal

Ghosh

Bandyopadhyay

Jana

2015

Model. Earth Syst. Environ.

162

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Groundwater is one of the world's most precious natural resources. But still now this valuable resource is largely unexploited for agricultural development in drought prone western region of West Bengal. In drought prone areas micro-watershed based development strategy may be considered as the best practice for integrated development. Keeping in view the above perspective, we select Kumari watershed of Purulia district, the westernmost and semi-arid district of West Bengal for better water resource management. Geologically the area consists of Chotanagpur granite gneiss complex while physiographically it is highly dissected pedimental landscape with lateritic upland and skeletal soil. As a result, cultivation of this area is predominantly mono-cropped and thus per hectare production is also low as compared to other regions of West Bengal. Supply of sufficient water resource in this region may offer more food security alternative to rain-fed subsistence farming. That's why the present study has been carried out to evaluate the potential zones for groundwater targeting in Kumari watershed of Purulia district using an integrated remote sensing data, Survey of India topographical sheets and field verification. Hydro-geological features (geomorphological and geological units, slope, drainage density, lineaments density etc.) that influence groundwater occurrence were extracted and integrated to evaluate the hydro-geomorphological characteristics of the study area. Thematic maps of the extracted features were prepared with the help of ERDAS Imagine 9.0 and Arc-GIS 9.3 software. Weightage values were assigned to the different parameters according to their relative importance to groundwater potentiality and integrated through Geographic Information System environment. Finally on the basis of grid-wise theme weight and class weights the groundwater potential map was prepared by overlay the thematic layers.

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Section: Lithologymentioning

confidence: 99%

Mapping of groundwater potential zones in hard rock terrain using geoinformatics: a case of Kumari watershed in western part of West Bengal

Ghosh

Bandyopadhyay

Jana

2015

Model. Earth Syst. Environ.

162

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“…Flood inundation areas may also be analysed, provided the data resolution is adequate (Ramamoorthi and Rao, 1985). Indeed it is also possible in some areas to infer likely underground water resources from such data (Salman, 1983). Nevertheless, visible and infrared data have been most commonly used to make estimates of rainfall, snowfall and soil moisture.…”

Section: Visible and Infrared Datamentioning

confidence: 99%

Satellite‐Based Remote Sensing

Collier

2016

Hydrometeorology

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“…Natural resource monitoring benefits from the use of satellite images, which provide a powerful source of information for detecting environmental processes [26]. Furthermore, identifying lithologic land surface structures and extracting extracted structural lineaments is possible using computer vision techniques [27][28][29]. For instance, research on mineral exploration can be supported using the classified satellite images to discriminate lithological units on the color composites of the images in various ratios [30].…”

Section: Introduction 1backgroundmentioning

confidence: 99%

Recognizing the Wadi Fluvial Structure and Stream Network in the Qena Bend of the Nile River, Egypt, on Landsat 8-9 OLI Images

Lemenkova

Debeir

2023

Information

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With methods for processing remote sensing data becoming widely available, the ability to quantify changes in spatial data and to evaluate the distribution of diverse landforms across target areas in datasets becomes increasingly important. One way to approach this problem is through satellite image processing. In this paper, we primarily focus on the methods of the unsupervised classification of the Landsat OLI/TIRS images covering the region of the Qena governorate in Upper Egypt. The Qena Bend of the Nile River presents a remarkable morphological feature in Upper Egypt, including a dense drainage network of wadi aquifer systems and plateaus largely dissected by numerous valleys of dry rivers. To identify the fluvial structure and stream network of the Wadi Qena region, this study addresses the problem of interpreting the relevant space-borne data using R, with an aim to visualize the land surface structures corresponding to various land cover types. To this effect, high-resolution 2D and 3D topographic and geologic maps were used for the analysis of the geomorphological setting of the Qena region. The information was extracted from the space-borne data for the comparative analysis of the distribution of wadi streams in the Qena Bend area over several years: 2013, 2015, 2016, 2019, 2022, and 2023. Six images were processed using computer vision methods made available by R libraries. The results of the k-means clustering of each scene retrieved from the multi-temporal images covering the Qena Bend of the Nile River were thus compared to visualize changes in landforms caused by the cumulative effects of geomorphological disasters and climate–environmental processes. The proposed method, tied together through the use of R scripts, runs effectively and performs favorably in computer vision tasks aimed at geospatial image processing and the analysis of remote sensing data.

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Using Landsat imagery interpretation for underground water prospection around Qena Province, Egypt

Cited by 16 publications

References 0 publications

Mapping of groundwater potential zones in hard rock terrain using geoinformatics: a case of Kumari watershed in western part of West Bengal

Mapping of groundwater potential zones in hard rock terrain using geoinformatics: a case of Kumari watershed in western part of West Bengal

Satellite‐Based Remote Sensing

Recognizing the Wadi Fluvial Structure and Stream Network in the Qena Bend of the Nile River, Egypt, on Landsat 8-9 OLI Images

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