nach oben

Erschienen in:

2017 | OriginalPaper | Buchkapitel

Comparison of 2D & 3D Parameter-Based Models in Urban Fine Dust Distribution Modelling

verfasst von : Yahya Ghassoun, M. -O. Löwner

Erschienen in: Advances in 3D Geoinformation

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

In the present study two Land Use Regression Models for the estimation of urban fine dust distribution were established and compared. The first model used 2D parameters derived from an Open Street Map project data (OSM) and the second model used 3D parameters derived from a CityGML-based 3D city model. Both models predict fine-dust concentrations by using urban morphological (2D resp. 3D) and additional semantic parameters. The models were applied to a 2 km² study area in Berlin, Germany. The 2D-LUR model explained 84 % of the variance of TNC for the full data set with root mean square error (RMSE) of 3284 cm⁻³ while the 3D-LUR explained 79 % of the variance with an RMSE of 3534 cm⁻³. Both models are capable to depict the spatial variation of TNC across the study area and showed relatively similar deviation from the measured TNC. The 3D-LUR needed less parameters than the 2D-LUR model. Furthermore, the semantic parameters (e.g. streets type) played a significant role in both models.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Vorheriges Kapitel Cartographic Enrichment of 3D City Models—State of the Art and Research Perspectives

Nächstes Kapitel Investigating Semantic Functionality of 3D Geometry for Land Administration

Abernethy, R. C., Allen, R. W., McKendry, I. G., & Brauer, M. A. (2013). Land use regression model for ultrafine particles in vancouver, Canada. Environmental Science and Technology, 47, 5217–5225.CrossRef

Abhijith, K. V., & Gokhale, S. (2015). Passive control potentials of trees and on-street parked cars in reduction of air pollution exposure in urban street canyons. Environmental Pollution, 204, 99–108.CrossRef

Arain, A. M., Blair, R., Finkelstein, N., Brook, R. J., Sahsuvaroglu, T., Beckerman, B., et al. (2007). The use of the wind fields in a land use regression model to predict air pollution concentrations for health exposure studies. Atmospheric Environment, 41, 3453–3464.CrossRef

Burghardt, R. (2014). Development of an ArcGIS extension to model urban climate factors.

Brand, L., & Löwner, M.-O. (2014). Parametrisierung und Identifikation urbaner Straßenkreuzungen im Kontext der Feinstaubmodellierung. Parameterization an identification of street crossings in the context of fine dust modelling. Proceedings of the joint meeting of DGfK, DGPF, GfGI, and GiN, 26–28/03/2014, Hamburg, Germany.

Brauer, M., Hoek, G., van Vliet, P., Meliefste, K., Fischer, P., Gehring, U., et al. (2003). Estimating long-term average particulate air pollution concentrations: Application of traffic indicators and geographic information systems. Epidemiology, 14, 228–239.

Briggs, D. J., de Hough, C., Gulliver, J., Wills, J., Elliott, P., Kingham, S., et al. (2000). A regression-based method for mapping traffic-related air pollution: Application and testing in four contrasting urban environments. Science of the Total Environment, 253, 151–167.CrossRef

Burtscher, H., & Schüepp, K. (2012). The occurrence of ultrafine particles in the specific environment of children. Paediatric Respiratory Reviews, 13, 89–94.CrossRef

Chen, L., Du, S., Bei, Z., Kong, S., You, Y., & Han, B., et al. (2010). Application of land use regression for estimating concentrations of major outdoor air pollutants in Jinan, China. Journal of Zhejiang University Science A (Appl Phys & Eng), 11, 857–867.

Czerwinski, A., Gröger, G., Reichert, S., & Plümer, L. (2013). Qualitätssicherung einer 3D-GDI - EU-Umgebungslärmkartierung Stufe 2 in NRW. Quality management of a 3D-SDI – phase 2 of the EU ambient noise mapping in NRW. Zeitschrift für Geodäsie, Geoinformation und Landmanagement.

Gàl, T., & Unger, J. (2009). Detection of ventilation paths using high resolution roughness parameter mapping in a large urban area. Building and Environment, 44, 198–206.CrossRef

Geiser, M., Rothen-Rutishauser, B., Kapp, N., Schürch, S., Kreyling, W., & Schulz, H., et al. (2005). Ultrafine particles cross cellular membranes by nonphagocytic mechanisms in lungs and in cultured cells. Environmental Health Perspectives, 113, 1555–1560.

Ghassoun, Y., Ruths, M., Löwner, M.-O., & Weber, S. (2015a). Intra-urban variation of ultrafine particles as evaluated by process related land use and pollutant driven regression modelling. Science of the Total Environment.

Ghassoun, Y., Löwner, M.-O., & Weber, S. (2015b). Exploring the Benefits of 3D city Models in the Field of Urban Particles Distribution Modelling—a Comparison of Model Results. Breunig, M., Al-Doori, M., Butwilowski, E., Kuper, P. V., Benner, J., & Haefele, K.H. (2015) 3D Geoinformation Science, The 529 Selected Papers of the 3D GeoInfo, Lecture Notes in Geoinfmation and Cartography, 530, 193–205.

Gröger, G., Kolbe, T. H., Nagel, C., Häfele, K.-H. (2012). OGC City Geography Markup Language (CityGML) encoding standard, version 2.0, OGC Doc No. 12–019, Open Geospatial Consortium.

Haklay, M. (2009). Beyond good enough? Spatial data quality and OpenStreetMap data. In: State of the Map Conference 2009, Amsterdam. http://de.slideshare.net/mukih/beyond-good-enough-spatial-data-quality-and-openstreetmap-data?qid=1f655291-2d6c-48ce-9ced-1af8456dc713&v=qf1&b=&from_search=12 Published on 11. Juli 2009.

Heal, M. R., Kumar, P., & Harrison, R. M. (2012). Particles, air quality, policy and health. Chemical Society Reviews, 41, 6606–6630.CrossRef

HEI. (2013). Review Panel on Ultrafine Particles—Understanding the Health Effects of Ambient Ultrafine Particles. HEI Perspectives 3. Health Effects Institute, Boston, MA.

Henderson, S., Beckerman, B., Jerrett, M., Brauer, M. (2007). Application of land use regression to estimate long-term concentrations of traffic-related nitrogen oxides and fine particulate matter. Environmental Science and Technology, 41, 2422–2428.

Ho, C-C., Chan, C-C., Cho, C-W., Lin, H-I., Lee, J-H., Wu, C-F. (2015). Land use regression modeling with vertical distribution measurements for fine particulate matter and elements in an urban area. Atmospheric Environment, 104, 256–263.

Hoek, G., Beelen, R., de Hoogh, K., Vienneau, D., Gulliver, J., Fischer, P., et al. (2008). A review of land-use regression models to assess spatial variation of outdoor air pollution. Atmospheric Environment, 42, 7561–7578.CrossRef

Jerrett, M. (2011). Spatiotemporal Analysis of Air Pollution and Mortality in California Based on the American Cancer Society Cohort 2011; Final Report.

Jokar Arsanjani, J., Mooney, P., Helbich, M., & Zipf, A. (2015). An exploration of future of the contributions to OpenStraatMap and development of a Contribution Index. Transactions in GIS, volume and issue pending, pp. pending. Wiley. doi:10.111/tgis.12139.

Kaden, R., & Kolbe, T. H. (2013). City-Wide Total Energy Demand Estimation of Buildings using Semantic 3D City Models and Statistical Data. Kongress-/ Buchtitel: Proceeding of the 8th International 3D GeoInfo Conference. Band/ Teilband: II-2/W1. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2013.

Kashima, S., Yorifuji, T., Tsuda, T., & Doi, H. (2009). Application of land use regression to regulatory air quality data in Japan. Science of the Total Environment, 407, 3055–3062.

Kim, Y., & Guldmann, J.-M. (2011). Impact of traffic flows and wind directions on air pollution concentrations in Seoul. Korea. Atmospheric Environment, 45, 2803–2810.CrossRef

Li, X., Liu, W., Chen, Z., Zeng, G., Hu, C., León, T., et al. (2015). The application of semicircular-buffer-based land use regression models incorporating wind direction in predicting quarterly NO2 and PM10 concentrations. Atmospheric Environment, 103, 18–24.CrossRef

Löwner, M.-O., Casper, E., Becker, T., Benner, J., Gröger, G., Gruber, U., et al. (2013). CityGML 2.0 – ein internationaler Standard für 3D-Stadtmodelle, Teil 2: CityGML in der Praxis. CityGML 2.0 – an international standard for 3D city models, part 2: CityGML in practice. Zeitschrift für Geodäsie, Geoinformation und Landmanagement, 2, 131–143.

Mercer, D. L., Szpiro, A. A., Sheppard, L., Lindström, J., Adar, S., Allen, R., et al. (2011). Comparing universal kriging and land-use regression for predicting concentrations of gaseous oxides of nitrogen (NOx) for the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). Atmospheric Environment, 45, 4412–4420.CrossRef

Ming, W., Qingquan, L., Qingwu, H., & Meng, Z. (2013). Quality analysis of open street map data. International archives of the photogrammetry, remote sensing and spatial information sciences, Volume XL-2/W1, 2013. In: 8th International Symposium on Spatial Data Quality, 30 May-1 June 2013, Hong Kong.

Morawska, L., Ristovski, Z., Jayaratne, E. R., Keogh, D. U., & Ling, X. (2008). Ambient nano and ultrafine particles from motor vehicle emissions: Characteristics, ambient processing and implications on human exposure. Atmospheric Environment, 42, 8113–8138.CrossRef

Over, M., Schilling, A., Neubauer, S., & Zipf, A. (2010). generating web-based 3D city models from OpenStreetMap: The current situation in Germany. Computers, Environment and Urban Systems, 34, 496–507.CrossRef

Rivera, M., Basagaña, X., Aguilera, I., Agis, D., Bouso, L., Foraster, M., et al. (2012). Spatial distribution of ultrafine particles in urban settings: A land use regression model. Atmospheric Environment, 54, 657–666.CrossRef

Sabaliaukas, K., Jeong, C.-H., Yao, X., Reali, C., Sun, T., & Evans, G. (2015). Development of a Land-use Regression Model for Ultrafine Particles in Toronto. Canada. Atmospheric Environment,. doi:10.1016/j.atmosenv.2015.02.018.

Saraswat, A., Apte, S. J., Kandlikar, M., Brauer, M., Henderson, B. S., & Marshall, D. J. (2013). Spatiotemporal Land Use Regression Models of Fine, Ultrafine, and Black Carbon Particulate Matter in New Delhi. India. Environ. Sci. Technol., 47, 12903–12911.CrossRef

Tang, R., Blangiardo, M., & Gulliver, J. (2013). Using Building Heights and Street Configuration to Enhance Intraurban PM10, NOX, and NO2 Land Use Regression Models. Environmental Science and Technology, 47, 11643–11650.CrossRef

Vardoulakis, S., Gonzalez-Flesca, N., & Fisher, B. E. A. (2012). Assessment of trafic-related air pollution in two street canyons in Paris: implications for exposure studies. Atmospheric Environment, 36, 1025–1039.CrossRef

WHO. (2013). Review of evidence on health aspects of air pollution—REVIHAAP Project—Technical report. World Health Organization—Regional office for Europe, Copenhagen p. 300.

Wong, M. S., Nichol, J. E., NG, E. Y. Y., Guilbert, E., Kwok, K. H., & To, P. H., et al. (2011). GIS Techniques for mapping urban ventilation, using frontal area index and least cost path analysis. Landscape and Urban Planning, 102(4), 245–253.

Weber, S., Kordowski, K., & Kuttler, W. (2013). Variability of particle number concentration and particle size dynamics in an urban street canyon under different meteorological conditions. Science of the Total Environment, 449, 102–114.CrossRef

Zhang, J. J. Y., Sun, L., Barrett, O., Bertazzon, S., Underwood, F. E., & Johnson, M. (2015). Development of land-use regression models for metals associated with airborne particulate matter in a North American city. Atmospheric Environment, 106, 165–177.CrossRef

Titel: Comparison of 2D & 3D Parameter-Based Models in Urban Fine Dust Distribution Modelling
verfasst von: Yahya Ghassoun
M. -O. Löwner
Verlag: Springer International Publishing
Buch: Advances in 3D Geoinformation
Print ISBN: 978-3-319-25689-4

Electronic ISBN: 978-3-319-25691-7

Copyright-Jahr: 2017
DOI: https://doi.org/10.1007/978-3-319-25691-7_13

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"