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Fig. 11.6 Modeling results for the southern test site. ( a ) Original CASI data (color-infrared). ( b )
Modeling input (legend: see Fig. 11.4 ). ( c ) Nighttime simulation (w/o buildings). ( d ) Nighttime
simulation (w/buildings)
the potential of the described mapping and modeling workflow for urban planning
applications. Second, ENVI-met was primarily designed and reportedly works well
for making relative, not absolute, comparisons among climate variables and their
spatial patterns (Emmanuel and Fernando 2007 ;Bruse 2009 ; Heldens 2010 ). Since
the two case studies presented do not compare absolute values of modeled air
temperature, the necessity of validating the simulation outputs is debatable. Third, it
was practically impossible to objectively assess model performance due to the lack
of suitable reference data. Of the information needed to quantify simulation quality,
neither multiday air temperature records from a high-density network of climate
stations nor thermal imagery acquired by an airborne remote sensing system (e.g.,
AVIRIS (NASA Jet Propulsion Laboratory 2014 ) or G-LiHT (Cook et al. 2013 ))
were available for the modeling test sites.
As an alternative to model validation, one can refer to different aspects of
this work suggesting that the obtained simulation results can be considered as
reliable. One indication is that the surface material map - one of the most
important modeling inputs - has proven to be sufficiently accurate to parameterize
ENVI-met (cf. Sect. 11.5.1 ). Nevertheless, to exclude smaller misclassifications
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