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001-es BibID:	BIBFORM134107
Első szerző:	Daoud Abazar Mohamed Ahmed (földtudományi kutató, geológus, geográfus)
Cím:	Comprehensive hazard susceptibility assessment in Port Sudan city usingAHP: emphasizing flash flood risk, soil moisture, and salinity dynamics / Daoud, Abazar M. A. ; Abir, Mohammed Noor A. M. ; Kazem, Mahmoud M. ; Satti, Albarra M. N. ; Shebl, Ali ; Mohamed, Musaab A. A. ; Agyemfra, George Joel ; Elrasheed, Abdelmajeed A. ; Csámer, Árpád ; Rózsa, Péter
Dátum:	2025
ISSN:	1947-5705 1947-5713
Megjegyzések:	Natural hazards threaten ecosystems, societies, and infrastructure, especially in rapidly urbanizing areas. Port Sudan City, on the Red Sea coast near the Red Sea Hills, is vulnerable to flash floods, soil collapse from salinity, and variable soil moisture, affecting sustainable land use. This study develops a hazard susceptibility assessment using the Analytic Hierarchy Process (AHP) and geospatial analysis. Factors including elevation, slope, curvature, geology, land use/cover (LULC), drainage density, salinity, and soil moisture were integrated into an AHP-based multi-criteria framework. Satellite data (Landsat 8 OLI, Sentinel?2) provided indices such as NDVI, LSE, LST, and SMI. Four factor groups were analyzed: (i) hydro-meteorological factors driving floods; (ii) soil-related factors causing infrastructure damage; (iii) terrain factors increasing rockfall risk; and (iv) LULC and geology-related factors. An integrated hazard map was validated with field surveys and lab analyses. Flood risk had the highest AHP weight, followed by salinity and soil moisture. Southern areas, including the airport and Bashair Terminal, are highly flood-prone; the 2024 Arbaat Dam collapse increased northern flood risk. Shoreline areas face salinity and moisture hazards, while western steep terrain is prone to rockfalls. Results highlight the need for updated hazard maps, better drainage, and sustainable land-use planning.
Tárgyszavak:	Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk Analytic hierarchy process multi-hazard susceptibility mapping flash flood soil salinity soil moisture Port Sudan
Megjelenés:	Geomatics, Natural Hazards and Risk. - 16 : 1 (2025), p. 1-32. -
További szerzők:	Abir, Mohammed Noor A. M. Kazem, Mahmoud M. Satti, Albarra Shebl, Ali (1992-) (geológus) Mohamed, Musaab Adam Ahmed (1990-) (geologist) Agyemfra, George Joel Abdelmajeed, Adam Elrasheed Ali (1988-) (Geologist) Csámer Árpád (1976-) (geológus) Rózsa Péter (1956-) (petrográfus)
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001-es BibID:	BIBFORM131916
035-os BibID:	(Scopus)105013101506 (WoS)001559258400001
Első szerző:	Daoud Abazar Mohamed Ahmed (földtudományi kutató, geológus, geográfus)
Cím:	Machine Learning-Based Lithological Mapping and Mineral Prospecting Using Hyperspectral and Multispectral Remote Sensing in Wadi Halfa, North Sudan / Abazar M. A. Daoud, Ali Shebl, Mutwakil Nafi, Abdelmajeed A. Elrasheed, Arpád Csámer, Péter Rozsa
Dátum:	2025
ISSN:	1464-343X
Megjegyzések:	At present, the global demand for mineral resources is critical, leading nations to focus on exploration. Remote sensing is a cost-effective tool, especially in harsh terrains. This study conducted lithological mapping in Wadi Halfa, North Sudan, using algorithm-based remote sensing, field observations, and petrographical analysis to detect iron ore and barite deposits. Multisensor optical datasets (L9, L8, and S2) were integrated to effectively delineate the lithological units. In addition, PRISMA hyperspectral data, with its detailed spectral signatures, improved spatial distribution patterns of barite and iron oxides across the study area. Image processing techniques (false colour composites, principal component analysis, minimum noise friction, band ratios) detected hydroxyl-bearing minerals, ferric, and ferrous oxides. Support Vector Machine (SVM), Artificial Neural Network (ANN), and Mahalanobis Distance Classifier (MDC) achieved overall accuracies of 95.51 %, 94.59 %, and 98.99 %, respectively. The study helped interpret the spatial relationship between barite and iron oxides. Four types of iron ore with more than three distinct layers were identified, including (a) oolitic ironstone, (b) ferruginous sandstone, (c) ferruginous ironstone, and (d) Banded Iron Formation (BIF) during field investigations, petrographic examinations, and chemical analysis validated remote sensing findings, revealing iron ore (62.7 % Fe) and barite (63.9 % Ba) concentrations. An economic assessment confirmed the presence of economic reserves suitable for exploitation. This research is recommended for broader application, particularly in machine learning for delineating iron ore and barite deposits in complex sedimentary sequences. The realization of machine learning algorithms emphasizes their potential to enhance lithological mapping in sedimentary sequences, suggesting a promising direction for future research.
Tárgyszavak:	Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk Support vector machine Artificial neural network Mahalanobis Iron ore Barite Economic reserves
Megjelenés:	Journal Of African Earth Sciences. - 232 (2025), p. 1-22. -
További szerzők:	Shebl, Ali (1992-) (geológus) Nafi, Mutwakil Abdelmajeed, Adam Elrasheed Ali (1988-) (Geologist) Csámer Árpád (1976-) (geológus) Rózsa Péter (1956-) (petrográfus)
Pályázati támogatás:	Stipendium Hungaricum Scholarship Program Egyéb
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001-es BibID:	BIBFORM126013
035-os BibID:	(Scopus)85211072489 (WoS)001409273800001
Első szerző:	Daoud Abazar Mohamed Ahmed (földtudományi kutató, geológus, geográfus)
Cím:	Remote sensing and gravity investigations for barite detection in Neoproterozoic rocks in the Ariab area, Red Sea Hills, Sudan / Daoud, Abazar M.A.; Shebl, Ali; Abdelkader, Mohamed M.; Mohieldain, Ali Ahmed; Csámer, Árpád; Satti, Albarra M.N.; Rózsa, Péter
Dátum:	2024
ISSN:	2352-9385
Megjegyzések:	The increasing global demand for barite, driven by its geological importance and various industrial applications, advises the scientific community to improve attempts to identify and explore its deposits in different geological settings. This boost in interest aims to ensure sustainable supply by locating new sources and better understanding the conditions in which barite forms. This study presents an integrated approach using multispectral (Landsat 8 & 9, Sentinel-2, and ASTER) and hyperspectral (PRISMA) remote sensing data, along with geophysical gravity data, to improve the localization of barite deposits. Several image processing methods, including false colour composites, principal component analysis, band ratios, minimum noise fraction, and spectral analysis, were employed for the discrimination of barite deposits, revealing their association with felsic rocks (referred to as group C). Additionally, lineament extraction was performed using the recent and advanced different filters like Tilt Angle Horizontal Gradient (TAHG) and Enhanced Horizontal Gradient Amplitude (EHGA) on Bouguer anomalies, highlighting the structural control of barite deposits by the D3 deformation phase. Field investigations were conducted to validate our findings. Based on these field observations, the integrated methodology successfully mapped the distribution of barite and its host rocks, resulting in an updated geological map for barite distribution that can be used in further exploration phases. We strongly recommend the adopted approach and the newly proposed image combinations for preliminary explorations of barite in similar arid terrains.
Tárgyszavak:	Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk Barite Remote sensing Felsic rocks Enhanced horizontal gradient amplitude (EHGA) Bouguer anomalies
Megjelenés:	Remote Sensing Applications: Society and Environment. - 37 (2025), p. 1-27. -
További szerzők:	Shebl, Ali (1992-) (geológus) Abdelkader Mohamed Mostafa Ahmed (1993-) Mohieldain, Ali Ahmed Csámer Árpád (1976-) (geológus) Satti, Arshad Mehmod Rózsa Péter (1956-) (petrográfus)
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001-es BibID:	BIBFORM125954
Első szerző:	Daoud Abazar Mohamed Ahmed (földtudományi kutató, geológus, geográfus)
Cím:	Integrated Multi-Sensor Remote Sensing and Geophysical Data for Barite Potential Mapping in Ariab Districts, Northeast Sudan / Abazar Daoud, Ali Mohieldain, Mohamed Abdelkader, Ali Shebl, Aya Shereif, Albarra Satti, Péter Rózsa
Dátum:	2024
Megjegyzések:	Extensive scientific inquiries into barite have escalated due to increasing global demand, prompted by its resourceful applications in crucial industries and its association with mineralization of gold and copper. The current re-search utilizes a combination of multi-sensor approaches (Landsat 9 and PRISMA) along with the free satellite gravity data to optimize the detection and delineation of the barite deposit in the Sudanese part of the Nubian Shield. Techniques such as false color composites (FCC), principal compo-nent analysis (PCA), band ratios (BR), minimum noise fraction (MNF), Total Horizontal Gradient (THG), the Second Vertical Derivatives (SVD), and spectral analysis were utilized to distinguish lithological features, displaying the barite occur in association with acidic metavolcanic rocks within the Ari-ab district. Additionally, the gravity methods delineate structurally controlled barite mineralization associated with the north-east deformation phase. Our results were validated through comprehensive field investigations; the find-ings were exceptionally robust , enhancing the development of an updated map delineating additional prospective zones for barite deposits within the study area. The integrated geospatial, hyperspectral, and gravity data are strongly recommended for reconnaissance exploration of barite in other simi-lar regions.
Tárgyszavak:	Természettudományok Földtudományok előadáskivonat könyvrészlet Landsat 9 PRISMA Total Horizontal Gradient Second Vertical Derivatives Barite
Megjelenés:	Mediterranean Geosciences Union (MedGU) 4th annual meeting. - accepted for publication : - (2024), p. 1. -
További szerzők:	Mohieldain, Ali Ahmed Abdelkader Mohamed Mostafa Ahmed (1993-) Shebl, Ali (1992-) (geológus) Shereif, Aya S. (1994-) (Geologist) Satti, Albarra Rózsa Péter (1956-) (petrográfus)
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