Találati lista | Tudóstér

001-es BibID:	BIBFORM088332
035-os BibID:	(cikkazonosító)2786 (Scopus)85092708721 (WoS)000585255400001
Első szerző:	Mohammed Safwan (agrármérnök)
Cím:	Estimating Human Impacts on Soil Erosion Considering Different Hillslope Inclinations and Land Uses in the Coastal Region of Syria / Safwan Mohammed, Hazem G. Abdo, Szilard Szabo, Quoc Bao Pham, Imre J. Holb, Nguyen Thi Thuy Linh, Duong Tran Anh, Karam Alsafadi, Ali Mokhtar, Issa Kbibo, Jihad Ibrahim, Jesus Rodrigo-Comino
Dátum:	2020
ISSN:	2073-4441
Megjegyzések:	Soils in the coastal region of Syria (CRoS) are one of the most fragile components of natural ecosystems. However, they are adversely affected by water erosion processes after extreme land cover modifications such as wildfires or intensive agricultural activities. The main goal of this research was to clarify the dynamic interaction between erosion processes and different ecosystem components (inclination, land cover/land use, and rainy storms) along with the vulnerable territory of the CRoS. Experiments were carried out in five different locations using a total of 15 erosion plots. Soil loss and runoff were quantified in each experimental plot, considering different inclinations and land uses (agricultural land (AG), burnt forest (BF), forest/control plot (F)). Observed runoff and soil loss varied greatly according to both inclination and land cover after 750 mm of rainfall (26 events). In the cultivated areas, the average soil water erosion ranged between 0.14 ? 0.07 and 0.74 ? 0.33 kg/m2; in the BF plots, mean soil erosion ranged between 0.03 ? 0.01 and 0.24 ? 0.10 kg/m2. The lowest amount of erosion was recorded in the F plots where the erosion ranged between 0.1 ? 0.001 and 0.07 ? 0.03 kg/m2. Interestingly, the General Linear Model revealed that all factors (i.e., inclination, rainfall and land use) had a significant (p < 0.001) effect on the soil loss. We concluded that human activities greatly influenced soil erosion rates, being higher in the AG lands, followed by BF and F. Therefore, the current study could be very useful to policymakers and planners for proposing immediate conservation or restoration plans in a less studied area which has been shown to be vulnerable to soil erosion processes.
Tárgyszavak:	Agrártudományok Növénytermesztési és kertészeti tudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk soil management land cover changes Syria soil erosion hillslopes
Megjelenés:	Water. - 12 : 10 (2020), p. 1-25. -
További szerzők:	Abdo, Hazem Ghassan Szabó Szilárd (1974-) (geográfus) Pham, Quoc Bao Holb Imre (1973-) (agrármérnök) Linh, Nguyen Thi Thuy Anh, Duong Tran Alsafadi, Karam Mokhtar, Ali Kbibo, Issa Ibrahim, Jihad Rodrigo-Comino, Jesús
Pályázati támogatás:	Tématerületi Kiválósági Program (ED_18-1-2019-0028) Egyéb
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
Borító:
Saját polcon:

001-es BibID:	BIBFORM087876
035-os BibID:	(cikkazonosító)2529 (Scopus)85090981264 (WoS)000581970800001
Első szerző:	Mohammed Safwan (agrármérnök)
Cím:	Soil Management Effects on Soil Water Erosion and Runoff in Central Syria : A Comparative Evaluation of General Linear Model and Random Forest Regression / Safwan Mohammed, Ali Al-Ebraheem, Imre J. Holb, Karam Alsafadi, Mohammad Dikkeh, Quoc Bao Pham, Nguyen Thi Thuy Linh, Szilard Szabo
Dátum:	2020
ISSN:	2073-4441
Tárgyszavak:	Agrártudományok Növénytermesztési és kertészeti tudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk
Megjelenés:	Water. - 12 : 9 (2020), p. 1-19. -
További szerzők:	Al-Ebraheem, Ali Holb Imre (1973-) (agrármérnök) Alsafadi, Karam Dikkeh, Mohammad Pham, Quoc Bao Linh, Nguyen Thi Thuy Szabó Szilárd (1974-) (geográfus)
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
Borító:
Saját polcon:

001-es BibID:	BIBFORM115323
035-os BibID:	(WoS)001086503900002 (Scopus)85174061140
Első szerző:	Phinzi, Kwanele
Cím:	Understanding the role of training sample size in the uncertainty of high-resolution LULC mapping using random forest / Kwanele Phinzi, Njoya Silas Ngetar, Quoc Bao Pham, Gashaw Gismu Chakilu, Szilárd Szabó
Dátum:	2023
ISSN:	1865-0473 1865-0481
Megjegyzések:	High-resolution sensors onboard satellites are generally reputed for rapidly producing land-use/land-cover (LULC) maps with improved spatial detail. However, such maps are subject to uncertainties due to several factors, including the training sample size. We investigated the effects of different training sample sizes (from 1000 to 12,000 pixels) on LULC classification accuracy using the random forest (RF) classifier. Then, we analyzed classification uncertainties by determining the median and the interquartile range (IQR) of the overall accuracy (OA) values through repeated k-fold cross-validation. Results showed that increasing training pixels significantly improved OA while minimizing model uncertainty. Specifically, larger training samples, ranging from 9000 to 12,000 pixels, exhibited narrower IQRs than smaller samples (1000-2000 pixels). Furthermore, there was a significant variation (Chi2 = 85.073; df = 11; p < 0.001) and a significant trend (J-T = 4641, p < 0.001) in OA values across various training sample sizes. Although larger training samples generally yielded high accuracies, this trend was not always consistent, as the lowest accuracy did not necessarily correspond to the smallest training sample. Nevertheless, models using 9000-11,000 pixels were effective (OA > 96%) and provided an accurate visual representation of LULC. Our findings emphasize the importance of selecting an appropriate training sample size to reduce uncertainties in high-resolution LULC classification.
Tárgyszavak:	Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk High-resolution sensor LULC Training sample size Random forest Classification uncertainty
Megjelenés:	Earth Science Informatics. - 16 : 4 (2023), p. 3667-3677. -
További szerzők:	Ngetar Njoya Silas Pham, Quoc Bao Chakilu, Gashaw Gismu Szabó Szilárd (1974-) (geográfus)
Pályázati támogatás:	K138079 Egyéb K138503 Egyéb
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
Borító:
Saját polcon: