Environmental Engineering Reference
In-Depth Information
TABLE 21.1
Input parameters for urban physical representations of different degrees of complexity in regional atmospheric models (from
Ching
et al
., 2009). For an explanation of parameters see Burian and Ching (2009).
Parameters
Roughness
Single-layer
Multi-layer
approach
model
model
Albedo
x
Emissivity
x
Roughness length for momentum and heat above the urban canopy layer
x
x
Zero-plane displacement height above the urban canopy layer
x
x
Heat capacity and heat conductivity of urban surface
x
Anthropogenic heat
x
x
x
Surface fractions of vegetation, water, soil, road, roof
x
x
Building height
x
Albedo of roof, road and wall surfaces
x
x
Emissivity of roof, road and wall surfaces
x
x
Heat capacity of roof, wall and road surfaces
x
x
Heat conductivity of roofs, roads and walls
x
x
Roughness length of heat and momentum of roof, road and wall
x
x
Mean and standard deviation of building height
x
x
Plan area weighted mean building and vegetation height
x
Building height histograms
x
Plan area fraction and frontal area index
x
Plan area density
x
Rooftop area density
x
Frontal area density
x
Complete aspect ratio
x
x
Building area ratio
x
x
Building height-to-width ratio
x
x
Distribution of street orientation and width
x
Drag coefficient of buildings
x
of complex interactions between the land cover and land use
(Jansen, 2009). Land cover is the observed surface material,
whereas land use is a description of the human activity taking
place at the surface; the former is detectable by remote sensing
systems, but the latter typically requires additional information
fromother sources tomake a correct determination. Throughout
the text, we use ''LULC'' in cases where combined land use and
land cover classifications are discussed; cases where land use
or land cover alone are used are explicitly noted. Appropriate
urban LULC classifications (i.e., using land cover, land use,
or a combination of both) and building characteristics derived
from remotely sensed data for atmospheric modeling depend
on the model formulation and parameterization; spatial grid
resolution; any simplifying assumptions, and the urban physical
approach provided with the regional model; and application in
terms of processes of interest. We focus our discussion on optical
satellite-based sensor systems, as these provide the most extensive
historical and spatial coverage of urban areas.
albedo, emissivity - are appropriate inputs for atmospheric
models (see Stefanov and Brazel, 2007 for a recent overview
of relevant orbital and airborne sensors and their data specifi-
cations; also see chapters in Part II of this volume). However,
because of the relatively recent emphasis on detailed urban
atmospheric modeling, there are efforts going on to update the
spatial extent and consider heterogeneity of urbanizing regions
in the LULC data sets provided with the standard release versions
of atmospheric models.
For example, in order to adjust to the increasing resolution
of atmospheric models Masson
et al
. (2003) derived a new global
database for land surface parameters including LULC at the 1 km
scale and associated parameters of 215 ecosystems derived by
combining existing LULC, climate maps and Advanced Very
High Resolution Radiometer (AVHRR) satellite data. For the
European continent the cover types of the Coordination of
Information of the Environment (CORINE) land use classifica-
tion are used (Heymann
et al
., 1994), including 11 urban types
(continuous urban fabric, discontinuous urban fabric, industrial
or commercial units, road and rail networks and associated land,
port areas, airports, mineral extraction sites, dump sites, con-
struction sites, green urban areas, sport and leisure facilities).
The CORINE data were derived from medium-resolution satel-
lite images such as Landsat Thematic Mapper (TM) and Systeme
Probatoire d'Observation de la Terre multispectral (Spot XS)
scanner images and complementary information from ancillary
21.3.1
Urban land use and land
cover data
For many applications LULC and biophysical measurements
derived from remotely sensed data - such as vegetation cover,
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