Image Processing Reference
In-Depth Information
adequately capturing changes over time in the characteristics of a place. The urbane-
ness of a place as a continuum is determined based on a range of elements encom-
passing population size and density, social and economic organization, and the
transformation of the natural and agricultural environments into a built environment.
This chapter introduces you to one of such indices, i.e. an urban index that combines
census and survey data (to capture aspects of the social environment) with data from
remotely sensed imagery (to capture aspects of the built environment).
Martin Herold and Dar A. Roberts describe in Chapter 4 the spectral properties
of urban areas , how different urban land-cover types are spectrally discriminated,
and which sensor configurations are most useful to map urban areas. They also
demonstrate potentials of new remote sensing technologies improving capabilities to
map urban areas in high spatial and thematic detail. The authors stress the fact that
urban areas with roofing materials, pavement types, soil and water surfaces, and
vegetated areas represent a large variety of surface compositions. It is emphasized
that most suitable wavelengths are characterized by specific spectral features to
separate urban land cover.
The purpose of Chapter 5 authored by Richard Sliuzas, Monika Kuffer and Ian
Masser is to examine the utility of remote sensing data on urban and suburban areas
for Urban Planning and Management (UPM) from an application perspective . This
chapter especially discusses the use of remote sensing at two different spatial
scales, city-wide and neighborhood or site specific, the information needed with
respect to monitoring planned and unplanned development, and the optimal spatial
and temporal requirements for images used in this regard.
Rene M. Gluch and Meryll K. Ridd emphasize in Chapter 6 the ecological
nature of urban places and introduce the V-I-S (Vegetation-Impervious surface-
Soil) model to be used for remotely sensed data to characterize, map, and quantify
the ecological composition of urban/peri-urban environments. The model serves
not only as a basis for biophysical and human system analysis, it also serves as a
basis to detect and measure morphological/environmental changes of urban places
over time.
In Chapter 7 Debbie Fugate, Elena Tarnavsky, Douglas Stow review the devel-
opment of remote sensing systems and their contribution to the emergence of urban
remote sensing , especially how they promoted the pursuit of novel approaches to
the study of urban environments. The chapter also covers data availability and
requirements for a number of the most common earlier remote sensing applications
such as land use and land cover classification, building and cadastral infrastructure
mapping and planning, and utility and transportation system analysis. Additionally,
the chapter highlights first attempts that have already been made to link the physi-
cal and social attributes of urban environments.
In Chapter 8, Victor Mesev explores the role of ancillary data (information from
beyond remote sensing) for improving the contextual interpretation of satellite sensor
imagery during spectral-based and spatial-based classification. Supplementary,
explanations are given to the distinctions between urban land cover and urban land use,
and how the inherent heterogeneous structure of urban morphologies is statistically
represented between hard and soft classifications.
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