TY - CONF AU - Szász, Botond AU - Czimber, Kornél AU - Király, Géza ED - Czimber, Kornél TI - Digitális domborzatmodell-elemzés a Dudlesz-erdő területén a SoilSense projekt keretein belül T2 - Erdészeti Tudományos Konferencia Sopron, 2024. február 5-6. : Kivonatok Kötete PB - Soproni Egyetem Erdőmérnöki Kar C1 - Sopron PY - 2024 SP - 35 UR - https://m2.mtmt.hu/api/publication/34521718 ID - 34521718 LA - Hungarian DB - MTMT ER - TY - CONF AU - Gallai, Bence AU - Király, Géza AU - Czimber, Kornél ED - Czimber, Kornél TI - Domborzatmodell, felületmodell, illetve egyesfákra vonatkozó paraméterek előállítása UAV segítségével - a légifényképezés kiaknázatlan lehetőségei T2 - Erdészeti Tudományos Konferencia Sopron, 2024. február 5-6. : Kivonatok Kötete PB - Soproni Egyetem Erdőmérnöki Kar C1 - Sopron PY - 2024 SP - 34 UR - https://m2.mtmt.hu/api/publication/34521435 ID - 34521435 LA - Hungarian DB - MTMT ER - TY - CONF AU - Czimber, Kornél ED - Czimber, Kornél TI - Térbeli optimalizálás megerősítéses tanulással robot járművek irányításához precíziós erdészeti környezetben T2 - Erdészeti Tudományos Konferencia Sopron, 2024. február 5-6. : Kivonatok Kötete PB - Soproni Egyetem Erdőmérnöki Kar C1 - Sopron PY - 2024 SP - 29 UR - https://m2.mtmt.hu/api/publication/34518296 ID - 34518296 LA - Hungarian DB - MTMT ER - TY - CONF AU - Ács, Norbert AU - Czimber, Kornél ED - Czimber, Kornél TI - Fafajosztályozás eltérő időpontú és geometriai felbontású műhold-és légifelvételek alapján T2 - Erdészeti Tudományos Konferencia Sopron, 2024. február 5-6. : Kivonatok Kötete PB - Soproni Egyetem Erdőmérnöki Kar C1 - Sopron PY - 2024 SP - 28 UR - https://m2.mtmt.hu/api/publication/34518260 ID - 34518260 LA - Hungarian DB - MTMT ER - TY - CONF AU - Czimber, Kornél AU - Heil, Bálint AU - Illés, Gábor AU - Gribovszki, Zoltán AU - Veperdi, Gábor AU - Mészáros, Diána AU - Szász, Botond AU - Heilig, Dávid AU - Kovács, Gábor ED - Czimber, Kornél TI - Korszerű távérzékelési, geoinformatikai, terepi referencia adatgyűjtési módszerekkel támogatott termőhely és szénkészlet térképezés (SoilSense) T2 - Erdészeti Tudományos Konferencia Sopron, 2024. február 5-6. : Kivonatok Kötete PB - Soproni Egyetem Erdőmérnöki Kar C1 - Sopron PY - 2024 SP - 9 UR - https://m2.mtmt.hu/api/publication/34517299 ID - 34517299 LA - Hungarian DB - MTMT ER - TY - BOOK ED - Czimber, Kornél TI - Erdészeti Tudományos Konferencia Sopron, 2024. február 5-6. : Kivonatok Kötete PB - Soproni Egyetem Erdőmérnöki Kar C1 - Sopron PY - 2024 SP - 75 UR - https://m2.mtmt.hu/api/publication/34517129 ID - 34517129 LA - Hungarian DB - MTMT ER - TY - CHAP AU - Yasin, Emad Hassan Elawad AU - Ahmed, A.H. Siddig AU - Eiman, E. Deiab AU - Czimber, Kornél AU - Ahmed, Hasoba AU - Abubakr, Osma ED - Ling, Zhang ED - Shuli, Wang ED - Liangying, Liu TI - Forest Degradation in Dryland Ecosystems of Sudan: Review of the Causes, Consequences, Assessment Methods, and Potential Solutions T2 - Conservation, Exploitation and Restoration of Mountain Ecosystem [Working Title] PB - IntechOpen CY - London PY - 2023 SP - 1 EP - 27 PG - 27 UR - https://m2.mtmt.hu/api/publication/34491975 ID - 34491975 AB - 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. LA - English DB - MTMT ER - TY - CHAP AU - Yasin, Emad Hassan Elawad AU - Czimber, Kornél ED - Rifaat, Abdalla TI - Evaluating Satellite Image Classification: Exploring Methods and Techniques T2 - Geographic Information Systems - Data Science Approach [Working Title] PB - IntechOpen CY - London PY - 2023 SP - 1 EP - 33 PG - 33 DO - 10.5772/intechopen.1003196 UR - https://m2.mtmt.hu/api/publication/34491831 ID - 34491831 AB - 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. LA - English DB - MTMT ER - TY - CHAP AU - Yasin, Emad Hassan Elawad AU - Czimber, Kornél AU - Mohamed, Hemida ED - Ling, Zhang ED - Shuli, Wang ED - Liangying, Liu TI - Assessment and Mapping of Forest Cover Change in Dryland, Sudan Using Remote Sensing T2 - Conservation, Exploitation and Restoration of Mountain Ecosystem [Working Title] PB - IntechOpen CY - London PY - 2023 SP - 1 EP - 15 PG - 15 DO - 10.5772/intechopen.113222 UR - https://m2.mtmt.hu/api/publication/34491723 ID - 34491723 AB - 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. LA - English DB - MTMT ER - TY - JOUR AU - Elzaki, I. A. E. AU - Siddig, A. A. H. AU - Yasin, Emad Hassan Elawad AU - Attaelmnan, A. A. AU - Gadallah, N. A. H. AU - Hasoba, Ahmed AU - Nasreldeen, M. A. AU - Yagoub, Y. E. AU - Czimber, Kornél TI - Effect of Simulated Drought and Rainfall Fluctuation on Seedling Growth of Two Savannah Trees Species in Sudan: An Experimental Exploration JF - ACTA SILVATICA ET LIGNARIA HUNGARICA: AN INTERNATIONAL JOURNAL IN FOREST, WOOD AND ENVIRONMENTAL SCIENCES J2 - ACTA SILV LIGNARIA HUNG VL - 19 PY - 2023 IS - 1 SP - 37 EP - 50 PG - 14 SN - 1786-691X DO - 10.37045/aslh-2023-0003 UR - https://m2.mtmt.hu/api/publication/34406965 ID - 34406965 AB - 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. LA - English DB - MTMT ER -