Land cover/use change analysis and mapping of Borg El-Arab City, Egypt

Khafagy, Mohamed ElSaid; El-Sayed, Hossam M.; Darwish, Kh. M.

doi:10.1007/s12517-020-06115-x

Cited by 6 publications

(2 citation statements)

References 33 publications

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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].…”

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

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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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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

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“…Soil erosion is accelerated by human activities, and the impacts of climate change have become a global problem (Brodie & Catherine, 2020;Dang, 2021). Studies on soil erosion for implementation of land use and management practices (LUMPs) are considered one of the key components needed to provide early warnings to minimise the damage to people and property caused by erosion (Mohamed et al, 2020). According to Brodie & Catherine (2020), soil erosion commonly depends on factors such as weather conditions, the shape of the watershed, the soil texture, and land use management practices.…”

Section: Introductionmentioning

confidence: 99%

Potential risks of soil erosion in North-Central Vietnam using remote sensing and GIS

Ha,

Tuyen,

Sarzhanovna

et al. 2023

Rev. bras. eng. agríc. ambient.

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Unsustainable exploitation activities (UEAs), combined with the increasing impacts of global climate change are the key causes that lead to soil erosion in the North-Central Vietnam. Mountainous areas in the North-Central Vietnam commonly have steep slopes and sandy clay in the surface soil layer, which contribute to enhancing the soil erosion, resulting in a serious loss of life and property. This study investigates the land cover change (LCC) across the Thanh Chuong district by combining Remote Sensing Technique (RST) data with Geographic Information System (GIS) and further, establishing erosion risk hazard maps based on the RUSLE model simulation. To achieve these objectives, Sentinel and Landsat satellite images from the period 2010_2021 were acquired. It was verified that the forest area gradually decreased from 2010_2021, and the average annual soil loss was approximately 25 t per year. The amount of erosion that led to a soil loss of up to 18% of the total land area is related to weather conditions, terrain features, and the soil texture. The decline in the vegetation cover is expected to be the main cause of increasing trends in erosion and soil loss.

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Groundwater Investigation Using Electrical Resistivity Method at New Borg El-Arab City, Alexandria, Egypt

El-Sayed

Khafagy

Shagar

et al. 2023

Egyptian Journal of Aquatic Research

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Land cover/use change analysis and mapping of Borg El-Arab City, Egypt

Cited by 6 publications

References 33 publications

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

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

Potential risks of soil erosion in North-Central Vietnam using remote sensing and GIS

Groundwater Investigation Using Electrical Resistivity Method at New Borg El-Arab City, Alexandria, Egypt

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