Environmental Engineering Reference
In-Depth Information
Conclusions
Blaschke, T. and Hay, G. (2001) Object-oriented image analysis
and scale-space: Theory and methods for modeling and evalu-
ating multi-scale landscape structure. International Archives of
Photogrammetry and Remote Sensing , 34 (4/ W5), 22-29.
Blaschke, T., Burnett, C. and Pekkarinen, A. (2006) Image seg-
mentationmethods for object-based analysis and classification,
in (eds de Jong, S.M. and F.D. van der Meer), Remote Sensing
Image Analysis: Including the Spatial Domain , Springer, Berlin.
Brenner, A.R. and Roessing, L. (2008) Radar imaging of urban
areas by means of very high-resolution SAR and Interferomet-
ric SAR. IEEE Transactions in Geoscience and Remote Sensing ,
46(10) , 2971-2982.
Brown, M. (2000) Urban Parameterizations for Mesoscale Mete-
orological Models, in Mesoscale Atmospheric Dispersion (ed. Z.
Boybeyi), WIT Press, Southampton, UK, pp. 193-255.
Brown,M.J.,Burian,S.J.,Linger,S.L.,Velugubantla,S.P.and
Ratti, C. (2002) An overview of building morphological
characteristics derived from 3D building databases. Preprint
Proceedings of the American Meteorological Society's Fourth
SymposiumontheUrbanEnvironment , 20-24 May 2002,
Norfolk, VA.
Burian,S.J.,Brown,M.J.,McPherson,T.N. et al . (2006) Emerging
urban databases for meteorological and dispersion modeling.
Preprints, AMS Annual Meeting , 6th Symposium on the Urban
Environment, 29 January - 2 February 2006, Atlanta, Georgia.
Burian, S.J., Augustus, N., Jeyachandran, I. and BrownM. (2008).
National Building Statistics Database, Version 2 .FinalReport.
LA-UR-08-1921, Los Alamos National Laboratory.
Burian, S. J. andChing, J. (2009) Development of gridded fields of
urban canopy parameters for advanced urban meteorological
and air quality models, Environmental Protection Agency,
Washington, EPA/600/R-10/007.
Byun, D. and Schere, K.L. (2006) Review of the governing
equations, computational algorithms, and other components
of the models-3 Community Multiscale Air Quality (CMAQ)
modeling system. Applied Mechanics Reviews , 59 , 51-77.
Buyantuyev, A. (2005) Land cover classification using Landsat
Enhanced Thematic Mapper (ETM) data - year 2005. Online.
Available http://caplter.asu.edu/home/products/showDataset.
jsp?keyword = Land-Use%20and%20Land-Cover%
20Change&id = 377_1 (accessed on 18 November 2010).
CDC (Centers for Desease Control) (2005) Heat-
related mortality - Arizona, 1993-2002, and United States,
1979 - 2002. Morbidity & Mortality Weekly Report , 54 ,
628-630.
Cadenasso, M.L., Pickett, S.T.A. and Schwarz, K. (2007) Spatial
heterogeneity in urban ecosystems: reconceptualizing land
cover and a framework for classification. Fronteirs in Ecology
and Environment , 5 (2), 80-88.
ChenF.,Kusaka,H.,Bornstein,R. et al . (2010) The integrated
WRF/urban modeling system: development, evaluation, and
applications to urban environmental problems. International
Journal of Climatology , doi: 10.1002/joc.2158.
Chen, F., Tewari, M. and Ching, J. (2007) Effects of high resolu-
tion building and urban data sets on the WRF/urban coupled
model simulations for the Houston-Galveston areas. Seventh
Here we gave an overview of the recent development of physical
approaches for the representation of urban areas in regional
atmospheric models, input data, and urban characterization
along with the methods to derive them from remotely sensed data
from various platforms. The review of meteorological, climate
and air quality modeling studies for cities, in which those recent
model developments were applied, showed an improvement of
the quality of the simulations in terms of capturing meteorolog-
ical fields and phenomena and subsequently air quality.
AnexamplewasgiveninhowLULCareusedinregionalatmo-
spheric modeling. The potential contribution of LULC changes
to daily minimum and maximum near-surface air temperatures,
during four recent summer EHEs in the Phoenix metropolitan
area, were studied using WRF with Noah Urban Canopy Model
and remotely sensed LULC classification data for 1973, 1985,
1998 and 2005. Simulations were carried out for each EHE with
the four LULC classification data sets. Results show that urban
land use characteristics that have evolved over the past 35 years
in the Phoenix metropolitan region have had a significant impact
on extreme near-surface air temperatures occurring during EHEs
in the area. Simulated maximum daytime and minimum night-
time temperatures were notably higher due to the conversion
of agricultural to urban land use (by
2-4Kand8-10K,
respectively). The conversion of desert to urban land use led to a
significant increase in night-time air temperatures (6-7 K) and
no significant changes in daytime temperatures.
Acknowledgments
This material is based upon work supported by the National
Science Foundation under Grants No. ATM-0710631, No. GEO-
0816168, No. DEB-0423704, Central Arizona - Phoenix Long-
Term Ecological Research (CAP LTER). Any opinions, findings
and conclusions or recommendation expressed in this material
are those of the authors and do not necessarily reflect the views
of the National Science Foundation.
References
Anderson, J.R., Hardy, E.E., Roach, J.T. and Witmer, R.E. (1976)
A Land Use and Land Cover Classification System for Use with
Remote Sensor Data . Geological Survey Professional Paper 964,
US Government Printing Office.
Arnfield, J.A. (2003) Two decades of urban climate research: a
review of turbulence, exchanges of energy and water, and the
urban heat island. International Journal of Climatology , 23 ,
1-26.
Banzhaf, E. and Netzband, M. (2004) Detecting urban brown-
fields by means of high resolution satellite imagery, The
International Archives of the Photogrammetry, Remote Sensing,
and Spatial Information Sciences , 25 , 6 p. (on CDROM).
Bian, L. (2003) Retrieving urban objects using awavelet transform
approach. Photogrammetric Engineering and Remote Sensing ,
69 , 133-141.
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