Now ubiquitous in modern life, spatial data present great
opportunities to transform many of the processes on which we base
our everyday lives. However, not only do these data depend on the
scale of measurement, but also handling these data (e.g., to make
suitable maps) requires that we account for the scale of
measurement explicitly. Scale in Spatial Information and Analysis
describes the scales of measurement and scales of spatial variation
that exist in the measured data. It provides you with a series of
tools for handling spatial data while accounting for scale.
The authors detail a systematic strategy for handling scale
issues from geographic reality, through measurements, to resultant
spatial data and their analyses. They also explore a
process-pattern paradigm in approaching scale issues. This is well
reflected, for example, in chapters dealing with terrain analysis,
in which scale in terrain derivatives is described in relation to
the processing involved in the derivation of specific terrain
variables from elevation data, and area classes, which are viewed
as driven by class-forming covariates. Lastly, this book provides
coverage of some of the issues related to scale that are relatively
under-represented in the literature, such as the effects of scale
on information content in remotely sensed images, and the
interaction between scale and uncertainty that is increasingly
important for spatial information and analysis.
By taking a rigorous, scientific approach to scale and its
various meanings in relation to the geographic world, the book
alleviates some of the frustration caused by dealing with issues of
scale. While past research has led to an increasing number of
journal articles and a few books dedicated to scale modeling and
change of scale, this book helps you to develop coherent strategies
for scale modeling, highlighting applicability for a variety of
fields, from geomatic engineering and geoinformatics to
environmental modeling.
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