Environmental Engineering Reference
In-Depth Information
2009. Even with a two-year difference, there is evidence (in the
top middle section of the figure) of a temporal lag. This is where
the pixels from the IKONOS image clearly show spectral colors
associated with new built land cover yet the POINTER dataset
has yet to be updated. This is obviously a situation of temporal
discrepancy and the real question is whether such new structural
developments in urban areas can be linked by functional demand
by the population and if they can be linked whether they are
predictive of future urban development. These are issues that
need further research.
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Conclusions
This chapter is a review of urban remote sensing research and
the challenges for developing more complete representations of
urban areas from remotely sensed data and socioeconomic data
sources. It is an exploration into the feasibility of addressing a
temporal lag between the structural configuration of a city (as
measured by satellite imagery) and the city's functional char-
acteristics (as measured by social surveys, such as population
censuses). Such research can be developed to predict urban
growth based on previous demands and policies for new residen-
tial and commercial developments. The chapter is also a call for
scientists engaged in urban remote sensing research to advocate
models and methodologies that are more pragmatic and pre-
scriptive; with the distinct objective of informing policy makers
of possible demands for residential development and commercial
expansion. And finally, this chapter is an attempt to stimulate
conceptual thinking and develop research agendas on how tem-
poral lags help define prescriptive methodologies that help target
possible changes in urban structure with careful reference to
population censuses that were taken well before these structural
changes materialized. Possible items on a research agenda may
include a more precise measurement of a temporal lag between
function and form; should it be decennial to coincide with pop-
ulation censuses or linked to specific urban building regimes; do
temporal lags vary with city size and urbanization rates; and are
temporal lags uniform across an entire city or variable within
neighborhoods.
Urban remote sensing is gaining in prominence on the world
stage yet has far to go before being able to foster rigorous and
reliable models of the urban hierarchy - the most spatially diffuse
and functionally dynamic landscapes on the earth's surface. The
distinction between micro and macro remote sensing equates
to a distinction between precision urban structural (syntactic)
configuration and city-wide functional representation using inte-
grative models that link spectral information from high spatial
resolution sensor data with spatial and temporal indicators from
auxiliary sources. In each the focus is on integrative models that
explore metrics and maximization procedures in an attempt to
summarize the cartographic and geocomputation potential of
the burgeoning urban remote sensing technology. The author is
currently testing sensitivity analyses to determine optimum lags
and it is hoped that the resulting models of multi-temporality
will become vital components in the monitoring of city-wide
variations of social poverty, housing density, traffic congestion,
heat island effects, non-point source pollution and others issues
of urban sustainability.
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