Találati lista | Tudóstér

001-es BibID:	BIBFORM083957
035-os BibID:	(cikkazonosító)106234
Első szerző:	Molnár Vanda Éva (környezetkutató)
Cím:	Air pollution induced vegetation stress : The Air Pollution Tolerance Index as a quick tool for city health evaluation / Molnár Vanda Éva, Simon Edina, Tóthmérész Béla, Sarawut Ninsawat, Szabó Szilárd
Dátum:	2020
ISSN:	1470-160X
Megjegyzések:	Air Pollution Tolerance Index (APTI) is used to assess how tolerant plant species are of air pollution; it also serves to identify tolerant plant species that can be useful for pollution removal. APTI is calculated from parameters that are affected by air pollutants, such as ascorbic acid content, total chlorophyll content, relative water content and pH of leaf extract. In this study we report APTI values of two common tree species (Celtis occidentalis and Tilia sp.) in Debrecen, Hungary. We also ran a meta-analysis to compare APTI values among various global cities and land use types (industrial, roadside and urban) using robust ANOVA. APTI's relationship with city population and PM10 (particulate matter with aerodynamic diameter smaller than 10 ?m) was analysed using regression modelling and Principal Component Analysis. We applied Random Forest Regression for statistical model building. We demonstrated that the tolerance of tree species is higher in industrial areas and in cities with high pollution levels than in control areas. We found a strong positive correlation between APTI and the size of cities. The cities showed a separation along the first principal component, which was also correlated with APTI and the size of cities. Our results show that APTI is an efficient tool in air pollution monitoring and in decision making during urban development and urban greening.
Tárgyszavak:	Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk biomonitoring pH of leaf extract Total leaf chlorophyll Ascorbic acid Water content of leaf Random Forest Regression
Megjelenés:	Ecological Indicators. - 113 (2020), p. 1-8. -
További szerzők:	Simon Edina (1981-) (ökológus) Tóthmérész Béla (1960-) (ökológus) Ninsawat, Sarawut Szabó Szilárd (1974-) (geográfus)
Pályázati támogatás:	TNN 123457 Egyéb OTKA-116639 OTKA KH 126481 Egyéb KH 126477 Egyéb
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
Borító:
Saját polcon:

001-es BibID:	BIBFORM047591
Első szerző:	Szabó Szilárd (geográfus)
Cím:	Factors biasing the correlation structure of patch level landscape metrics / Szilárd Szabó, Zoltán Túria, Sándor Márton
Dátum:	2014
ISSN:	1470-160X
Tárgyszavak:	Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
Megjelenés:	Ecological Indicators. - 36 (2014), p. 1-10. -
További szerzők:	Túri Zoltán (1980-) (geográfus) Márton Sándor (szociológus)
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
Borító:
Saját polcon:

001-es BibID:	BIBFORM082563
Első szerző:	Varga Orsolya Gyöngyi (geográfus)
Cím:	Intensity Analysis and the Figure of Merit's components for assessment of a Cellular Automata-Markov simulation model / Orsolya Gyöngyi Varga, Robert Gilmore Pontius, Sudhir Kumar Singh, Szilárd Szabó
Dátum:	2019
ISSN:	1470-160X
Megjegyzések:	Some popular metrics to evaluate land change simulation models are misleading. Therefore, land change scientists have called for the development of methods to evaluate various aspects of modelling applications. This article answers the call by giving novel methods to compare three types of land change: 1) reference change during the calibration time interval, 2) simulation change during the validation time interval, and 3) reference change during the validation time interval. We compare these changes by using Intensity Analysis' three levels and the Figure of Merit's four components: Misses, Hits, Wrong Hits and False Alarms. We illustrate the concepts by applying a Cellular Automata - Markov land change model to a case study in northeast Hungary. We used reference maps of five land categories to calibrate the model during 2000-2006, then to validate the simulation during 2006-2012. Intensity Analysis' time interval level shows that the simulation change and the reference change decelerated from 2000-2006 to 2006-2012. Intensity Analysis' category level shows that the simulation losses were less than what a pure Markov chain would have dictated. Intensity Analysis' transition level shows that the model's Markov algorithm simulated correctly that the gain of Forest targeted Agriculture and Wetland. The Figure of Merit's components reveals more allocation error than quantity error. Our collection of metrics show that more error derived from the Cellular Automata algorithm than from the Markov algorithm. We recommend that scientists use Intensity Analysis and the Figure of Merit's components to reveal various fundamental aspects of modelling applications.
Tárgyszavak:	Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk cellular automata CA-Markov Figure of Merit Intensity analysis land change validation
Megjelenés:	Ecological Indicators. - 101 (2019), p. 933-942. -
További szerzők:	Pontius, Robert Gilmore Singh, Sudhir Kumar (1970-) (geográfus) Szabó Szilárd (1974-) (geográfus)
Pályázati támogatás:	EFOP-3.6.1-16-2016-00022 EFOP TNN 123457 Egyéb
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
Borító:
Saját polcon: