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001-es BibID:	BIBFORM078729
Első szerző:	Balázs Boglárka (geográfus)
Cím:	Extracting water-related features using reflectance data and principal component analysis of Landsat images / Boglárka Balázs, Tibor Bíró, Gareth Dyke, Sudhir Kumar Singh, Szilárd Szabó
Dátum:	2018
ISSN:	0262-6667
Megjegyzések:	This study aimed to map water features using a Landsat image rather than traditional land cover. We involved the original bands, spectral indices and principal components (PCs) of a principal component analysis (PCA) as input data, and performed random forest (RF) and support vector machine (SVM) classification with water, saturated soil and non-water categories. The aim was to compare the efficiency of the results based on various input data. Original bands provided 93% overall accuracy (OA) and bands 4?5?7 were the most informative in this analysis. Except for MNDWI (modified normalized differenced water index, with 98% OA), the performance of all water indices was between 60 and 70% (OA). The PCA-based approach conducted on the original bands resulted in the most accurate identification of all classes (with only 1% error in the case of water bodies). We therefore show that both water bodies and saturated soils can be identified successfully using this approach.
Tárgyszavak:	Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban multivariate analysis principal component analysis remote sensing Landsat classification uncertainty analysis spectral index
Megjelenés:	Hydrological Sciences Journal. - 63 : 2 (2018), p. 269-284. -
További szerzők:	Bíró Tibor Dyke, Gareth J. Singh, Sudhir Kumar (1970-) (geográfus) Szabó Szilárd (1974-) (geográfus)
Pályázati támogatás:	TÁMOP 4.2.4.A/2-11-1-2012-0001 TÁMOP SROP-4.2.2.B-15/1/KONV-2015-0001 egyéb NKFIH 108755 egyéb RH/751/2015 egyéb
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001-es BibID:	BIBFORM076537
035-os BibID:	(WoS)000458299900007 (Scopus)85059086542
Első szerző:	Szabó Szilárd (geográfus)
Cím:	NDVI dynamics as reflected in climatic variables: spatial and temporal trends : a case study of Hungary / Szilárd Szabó, László Elemér, Zoltán Kovács, Zoltán Püspöki, Ádám Kertész, Sudhir Kumar Singh, Boglárka Balázs
Dátum:	2019
ISSN:	1548-1603 1943-7226
Megjegyzések:	Understanding climate change and revealing its future paths on a local level is a great challenge for the future. Beside the expanding sets of available climatic data, satellite images provide a valuable source of information. In our study we aimed to reveal whether satellite data are an appropriate way to identify global trends, given their shorter available time range. We used the CARPATCLIM (CC) database (1961-2010) and the MODIS NDVI images (2000-2016) and evaluated the time period covered by both (2000-2010). We performed a regression analysis between the NDVI and CC variables, and a time series analysis for the 1961-2008 and 2000-2008 periods at all data points. The results justified the belief that maximum temperature (TMAX), potential evapotranspiration and aridity all have a strong correlation with the NDVI; furthermore, the short period trend of TMAX can be described with a functional connection with its long period trend. Consequently, TMAX is an appropriate tool as an explanatory variable for NDVI spatial and temporal variance. Spatial pattern analysis revealed that with regression coefficients, macro-regions reflected topography (plains, hills and mountains), while in the case of time series regression slopes, it justified a decreasing trend from western areas (Transdanubia) to eastern ones (The Great Hungarian Plain). This is an important consideration for future agricultural and land use planning; i.e. that western areas have to allow for greater effects of climate change.
Tárgyszavak:	Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk climate change trend CARPATCLIM principal component analysis topographic variables MODIS
Megjelenés:	GIScience & Remote Sensing. - 56 : 4 (2019), p. 624-644. -
További szerzők:	László Elemér (1987-) (meteorológus előrejelző szakiránnyal) Kovács Zoltán (1988-) (geográfus) Püspöki Zoltán (1972-) (geológus) Kertész Ádám (1948-) Singh, Sudhir Kumar (1970-) (geográfus) Balázs Boglárka (1985-) (geográfus)
Pályázati támogatás:	TÁMOP-4.2.4.A/2-11-1-2012-0001 TÁMOP NKFIH 108755 Egyéb
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