@CONFERENCE{MTMT:34521718,
	title = {Digitális domborzatmodell-elemzés a Dudlesz-erdő területén a SoilSense projekt keretein belül},
	url = {https://m2.mtmt.hu/api/publication/34521718},
	author = {Szász, Botond and Czimber, Kornél and Király, Géza},
	booktitle = {Erdészeti Tudományos Konferencia Sopron, 2024. február 5-6. : Kivonatok Kötete},
	unique-id = {34521718},
	year = {2024},
	pages = {35},
	orcid-numbers = {Király, Géza/0000-0003-0286-207X}
}

@CONFERENCE{MTMT:34521435,
	title = {Domborzatmodell, felületmodell, illetve egyesfákra vonatkozó paraméterek előállítása UAV segítségével - a légifényképezés kiaknázatlan lehetőségei},
	url = {https://m2.mtmt.hu/api/publication/34521435},
	author = {Gallai, Bence and Király, Géza and Czimber, Kornél},
	booktitle = {Erdészeti Tudományos Konferencia Sopron, 2024. február 5-6. : Kivonatok Kötete},
	unique-id = {34521435},
	year = {2024},
	pages = {34},
	orcid-numbers = {Király, Géza/0000-0003-0286-207X}
}

@CONFERENCE{MTMT:34518296,
	title = {Térbeli optimalizálás megerősítéses tanulással robot járművek irányításához precíziós erdészeti környezetben},
	url = {https://m2.mtmt.hu/api/publication/34518296},
	author = {Czimber, Kornél},
	booktitle = {Erdészeti Tudományos Konferencia Sopron, 2024. február 5-6. : Kivonatok Kötete},
	unique-id = {34518296},
	year = {2024},
	pages = {29}
}

@CONFERENCE{MTMT:34518260,
	title = {Fafajosztályozás eltérő időpontú és geometriai felbontású műhold-és légifelvételek alapján},
	url = {https://m2.mtmt.hu/api/publication/34518260},
	author = {Ács, Norbert and Czimber, Kornél},
	booktitle = {Erdészeti Tudományos Konferencia Sopron, 2024. február 5-6. : Kivonatok Kötete},
	unique-id = {34518260},
	year = {2024},
	pages = {28}
}

@CONFERENCE{MTMT:34517299,
	title = {Korszerű távérzékelési, geoinformatikai, terepi referencia adatgyűjtési módszerekkel támogatott termőhely és szénkészlet térképezés (SoilSense)},
	url = {https://m2.mtmt.hu/api/publication/34517299},
	author = {Czimber, Kornél and Heil, Bálint and Illés, Gábor and Gribovszki, Zoltán and Veperdi, Gábor and Mészáros, Diána and Szász, Botond and Heilig, Dávid and Kovács, Gábor},
	booktitle = {Erdészeti Tudományos Konferencia Sopron, 2024. február 5-6. : Kivonatok Kötete},
	unique-id = {34517299},
	year = {2024},
	pages = {9},
	orcid-numbers = {Heilig, Dávid/0000-0002-9690-9643}
}

@misc{MTMT:34517129,
	title = {Erdészeti Tudományos Konferencia Sopron, 2024. február 5-6. : Kivonatok Kötete},
	url = {https://m2.mtmt.hu/api/publication/34517129},
	editor = {Czimber, Kornél},
	publisher = {Soproni Egyetem Erdőmérnöki Kar},
	unique-id = {34517129},
	year = {2024}
}

@{MTMT:34491975,
	title = {Forest Degradation in Dryland Ecosystems of Sudan: Review of the Causes, Consequences, Assessment Methods, and Potential Solutions},
	url = {https://m2.mtmt.hu/api/publication/34491975},
	author = {Yasin, Emad Hassan Elawad and Ahmed, A.H. Siddig and Eiman, E. Deiab and Czimber, Kornél and Ahmed, Hasoba and Abubakr, Osma},
	booktitle = {Conservation, Exploitation and Restoration of Mountain Ecosystem [Working Title]},
	unique-id = {34491975},
	abstract = {Dryland forests are ecologically and socioeconomically important. They contribute to livelihood diversification, food security, animal feed and shelter, and environmental conservation in sub-Saharan Africa, particularly Sudan. Despite their importance, current findings show that multiple ecological, human, socio-economic, and policy factors have damaged these resources. As a result, undesirable consequences have been observed, such as food famine, land and water resource degradation, decline/loss of biodiversity, and contribution to global warming that affect the welfare of humans, plants, animals, and micro-organisms. This chapter briefly reviews the forest degradation in drylands Sudan with emphasis on its common causes, impacts, assessment methods, management intervention efforts, and potential future solutions. Given the current situation, there must be urgent combating efforts to manage Sudan’s dryland forest resources properly. On the one hand, following prevention measures to essentially deal with the current causes thus prevent any further degradation of forest resources in dryland Sudan. On the other hand, there is an urgent need to address current degradation following appropriate and timely rehabilitation interventions. We also recommend adopting a serious monitoring and evaluation system within these combating efforts by applying the five common indicators for measuring forest degradation: biodiversity, productive functions, carbon storage, forest health, and protective functions.},
	keywords = {Forest degradation; dryland ecosystems; management interventions; causes of degradation; assessment methods & indicators},
	year = {2023},
	pages = {1-27}
}

@{MTMT:34491831,
	title = {Evaluating Satellite Image Classification: Exploring Methods and Techniques},
	url = {https://m2.mtmt.hu/api/publication/34491831},
	author = {Yasin, Emad Hassan Elawad and Czimber, Kornél},
	booktitle = {Geographic Information Systems - Data Science Approach [Working Title]},
	doi = {10.5772/intechopen.1003196},
	unique-id = {34491831},
	abstract = {Satellite image classification serves a critical function across various applications,
		from land cover mapping and urban planning to environmental monitoring and
		disaster management. In recent years, significant advancements in machine learning
		and computer vision, coupled with increased accessibility to satellite imagery, have
		driven considerable progress in this field. Classification techniques for satellite imagery can be primarily divided into three key approaches: automatic, manual, and
		hybrid. Each approach offers unique advantages but also comes with its own set of
		limitations. While most methodologies gravitate toward automatic techniques, choosing an appropriate method should be a carefully considered decision based on specific
		needs. This paper provides an exhaustive review of cutting-edge classification algorithms, including Artificial Neural Networks (ANNs), Classification Trees (CTs),
		and Support Vector Machines (SVMs). It also offers a comparative analysis between
		these modern methods and traditional techniques, focusing on their respective performance metrics when applied to satellite data. This study examines key factors
		affecting remote sensing data classification, including classifier parameter adjustments and combining multiple classifiers. It reviews existing literature to enhance
		feature selection and classifier optimization for better accuracy. However, it also
		points out the continuous need for research in image processing to improve classification accuracy.},
	keywords = {machine learning; remote sensing; Classification techniques; Satellite image classification; summary of reviews},
	year = {2023},
	pages = {1-33}
}

@{MTMT:34491723,
	title = {Assessment and Mapping of Forest Cover Change in Dryland, Sudan Using Remote Sensing},
	url = {https://m2.mtmt.hu/api/publication/34491723},
	author = {Yasin, Emad Hassan Elawad and Czimber, Kornél and Mohamed, Hemida},
	booktitle = {Conservation, Exploitation and Restoration of Mountain Ecosystem [Working Title]},
	doi = {10.5772/intechopen.113222},
	unique-id = {34491723},
	abstract = {Forest resources in the arid and semi-arid of Sudan are experiencing significant
		fluctuations in tree cover and ecological functionality. This study aims to bridge this
		gap by utilizing multi-temporal Landsat imagery and mapping forest cover change
		in the Nabag Forest Reserve (NFR) in South Kordofan State, Sudan. For this assessment, two cloud-free images (TM from 2011 and OLI from 2021) were downloaded
		and analyzed using ArcMap 10.7 and ERDAS 2014 software. Supervised classification
		techniques were applied, corroborated by GPS point verification and field surveys, to
		quantify changes in forest cover over the decade. The results revealed that dense forest
		cover increased from 9% in 2011 to 38.9% in 2021, while light forest cover decreased
		from 34.4% in 2011 to 30.9% in 2021. Additionally, the area occupied by agriculture
		and barren land declined from 37.2% and 19.4% in 2011 to 18.7% and 11.5% in 2021,
		respectively. Rapid shifts were observed in all LULC categories during the study
		period. The primary causes of deforestation and forest degradation were tree felling, unsustainable grazing practices, and construction activities. These findings are
		crucial for guiding future forest rehabilitation and creating targeted management
		plans for the local communities reliant on these forests.},
	keywords = {remote sensing; Sudan; Land use and land cover (LULC); Forest degradation; Landsat imagery; forest rehabilitation; Nabag forest; South Kordofan state},
	year = {2023},
	pages = {1-15}
}

@article{MTMT:34406965,
	title = {Effect of Simulated Drought and Rainfall Fluctuation on Seedling Growth of Two Savannah Trees Species in Sudan: An Experimental Exploration},
	url = {https://m2.mtmt.hu/api/publication/34406965},
	author = {Elzaki, I. A. E. and Siddig, A. A. H. and Yasin, Emad Hassan Elawad and Attaelmnan, A. A. and Gadallah, N. A. H. and Hasoba, Ahmed and Nasreldeen, M. A. and Yagoub, Y. E. and Czimber, Kornél},
	doi = {10.37045/aslh-2023-0003},
	journal-iso = {ACTA SILV LIGNARIA HUNG},
	journal = {ACTA SILVATICA ET LIGNARIA HUNGARICA: AN INTERNATIONAL JOURNAL IN FOREST, WOOD AND ENVIRONMENTAL SCIENCES},
	volume = {19},
	unique-id = {34406965},
	issn = {1786-691X},
	abstract = {Climate change scenarios project that several regions, especially in dryland areas of sub-Saharan Africa, will undergo increasing aridity and, subsequently, expanding land degradation. The study aims to investigate the effect of two drying treatments on establishing and growing Hashab (Acacia senegal) and Boabab (Adansonia digitata) in nursery conditions. Through a 2×2 factorial experiment, seedlings grown in a mixture of silt and sand soil (2:3) were treated by irrigation intervals of one or two liters every three days for 14 weeks to simulate rainfall fluctuation patterns. Seedling germination rate, leaf number, stem height, and diameter were measured weekly; taproot length, shoot, and root dry weights were also assessed. The results showed that neither drying treatment significantly affected A. senegal and A. digitata seedling growth parameters. However, an interaction effect was found in the height and diameter for A. senegal and shoot dry weight for A. digitata. The study concluded that A. senegal and A. digitata seem tolerant to drying treatment. Therefore, the two species are recommended for afforestation programs in areas with relatively harsher conditions. Also, exposing the seedlings of these studied species to similar, extended periods of simulated drought (e.g., 6 – 12 months) is recommended for future studies.},
	keywords = {climate change; dryland; Sudan; savannah; Acacia senegal; Adansonia digitate},
	year = {2023},
	eissn = {1787-064X},
	pages = {37-50},
	orcid-numbers = {Siddig, A. A. H./0000-0002-8145-0964; Attaelmnan, A. A./0000-0002-0681-8570; Gadallah, N. A. H./0000-0003-3530-3653; Hasoba, Ahmed/0000-0002-7704-9385; Yagoub, Y. E./0000-0002-0938-654X}
}