Image Processing Reference
In-Depth Information
size results in a low local variance, and an image
resolution that is similar to the dominant object
size results in a maximized local variance. The
maximum of the local variance is thus an indica-
tion of the object size and can consequently aid in
determining a good spatial resolution.
spatial resolution
required for a given study
is determined by the size
of the smallest objects
that need to be identified
The Life Cycle of Planning Processes and Urban Objects
Strategic plans often have a life span of about 10 years and a requirement to be
reviewed and updated every 5 years. The review process monitors the implementa-
tion of the plans (Masser 1986 ) and provides an opportunity to use remote sensing
data. Site development plans, on the other hand, have very different temporal data
requirements, depending on the nature and speed of development. Planned develop-
ments are normally facilitated through very detailed planning activities in an initial
phase and potentially in intermediate phases depending on the scale of the project.
Remotely sensed data can assist in the initial phase of site development processes,
and in updating information on the city level after completion. Unplanned develop-
ments have higher temporal requirements (varying from days to years) for monitor-
ing. For example, if a planning agency is intervening in an unplanned area (e.g.,
through an upgrading project), the time span between monitoring will ideally
decrease, reflecting an increased level of control of development during such inter-
vention. However, the availability of resources for data acquisition and processing
may override considerations.
The temporal resolution of currently operating sensor systems normally used for
urban applications ranges from 3 to 24 days. While this resolution is generally suf-
ficient, the availability of usable, cloud-free data may actually be significantly
lower. For example, the number of usable images per year may be as low as one for
cities in humid climatic zones. In such cases, the use of radar data, which have the
ability to penetrate could cover, is an option, either as
a single data source (Stabel and Fischer 2001 ; Grey
et al. 2003 ) or in combination with optical data (Chen
et al. 2003 ). The recent availability of very high reso-
lution radar data from the DLR's TerraSARX system
may improve opportunities to reduce the impact of the
cloud cover problem.
With respect to the temporal domain of data, and depending on the remote sensing
application, it is also crucial to select imagery acquired during an appropriate season.
For example, while winter images with a minimum of vegetation cover are well-
suited for topographic mapping in temperate zones, such images may hinder or pre-
vent the classification of land use or the performance of environmental studies.
As another example, while the number of useable rainy-season images in tropical
areas may be scarce, dry-season images are likely to create problems related to the
spectral distinction between highly reflective surfaces (e.g., buildings and bare soil).
life-cycles of planning
processes determine
the temporal resolu-
tion requirements of
remotely sensed data
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