What is urban remote sensing? - Urban Remote Sensing: Monitoring, Synthesis and Modeling in the Urban Environment - page 7

not only urban spatial characteristics but also socioeconomic
conditions such as population density and transportation. The
chapter reviews the literature and debates on the definition of
urban sprawl, emphasizing common themes in definitions and
those measurable spatial characteristics that would be of specific
interest to the remote sensing community. It shows that sprawl
can be described by multiple quantitative measures but different
sprawl measures can yield contradictory outcomes. The chapter
suggests that sprawl should be best defined for a given case study
and quantified using different indicators that can accommodate
the researcher's definition of sprawl, spatial scale of analysis, and
specific characteristics of the study site.
The remaining four chapters in Part IV focus on population
estimation (Ch. 13), dasymetric mapping (Ch. 14), electrification
rate estimation (Ch. 15), and environmental justice research
(Ch. 16). Chapter 13 discusses a method for small area population
estimation by combined use of high-resolution imagery with lidar
data. This type of information is critical for decision-making by
both public and private sectors but is only available for one date
per decade. The work has provided an alternative that can be
used to derive reliable population estimation in a timely and cost-
effective fashion. Chapter 14 reviews various areal interpolation
techniques emphasizing dasymetric mapping, followed by an
example in which population estimates and sociodemographic
data are derived for different spatial units by using dasymetric
mapping methods that rely upon ancillary data from a variety
of sources including satellite imagery. Chapter 15 discusses a
method that has been developed to estimate the global percent
population having electric power access based on the presence
of satellite detected night-time lighting. The satellite-derived
results are pretty close to the reported electrification rates by
the International Energy Agency. The last chapter (Ch. 16)
included in Part IV discusses the role of remote sensing for
urban environmental justice research. The chapter comprises
a review on the principles and issues in environmental justice
research, a case study investigating the relationship between
a satellite-derived vegetation index and indicators of race and
socioeconomic status in Philadelphia, and a discussion on some
issues that need further research.

sensing approach to high-resolution urban impervious surface
mapping. This topic is included as part of urban environmental
analyses because landscape imperviousness has recently emerged
as a key indicator being used to address a variety of urban
environmental issues such as water quality, biodiversity of
aquatic systems, habitat structure, and watershed health (Yang
and Liu, 2005). The chapter reviews some major pixel-based and
object-based techniques for impervious surface estimation, and
compares the performance of the two groups of methods with
case studies.
The other chapters included in Part V deal with urban
hydrological processes (Ch. 18), vegetation carbon sequestration
(Ch. 19), biodiversity (Ch. 20), and air quality and climate
(Ch. 21). Chapter 18 discusses the impact of different remote
sensing methods for characterizing the distribution of impervious
surfaces on runoff estimation, and how this can affect the assess-
ment of peak discharges in an urbanized watershed. The study
shows that detailed information on the spatial distribution of
impervious surfaces strongly affects local runoff estimation and
has a clear impact on the modeling of peak discharges. Chapter 19
reviews the light-use efficiency (LUE) models and applied them
to estimate gross primary production (GPP) in the eastern
United States in two different years. The estimated GPP was
associated with various settlement densities. The LUE-based
vegetation productivity estimates may be integrated with car-
bon emissions data, thus providing a comprehensive view of net
carbon exchange between land and the atmosphere due to urban
development. Chapter 20 discusses the utilities of remote sensing
for characterizing biodiversity in urban areas, how urbanization
affects biodiversity, and how remote sensing-based biodiversity
research can be integrated with urban planning and manage-
ment for biodiversity conservation. The last chapter (Ch. 21) in
Part V reviews the existing literature concerning the influence
of urban land use/cover changes on urban meteorology, climate
and air quality. This is followed by a case study focusing on the
Phoenix metropolitan area to demonstrate how remote sensing
can be used to study the effect of historic land use changes on
near-surface air temperature during recent extreme heat events.

1.7 Urban growth and
landscape changemodeling

1.6 Urban environmental
analyses

A group of important activities in urban studies is to understand
urban dynamics and to assess future urban growth impacts on
the environment. There are two major types of models that can
be used to support such activities: analytical models that are
useful to explain urban expansion and evolving patterns as well
as dynamic models that can be used to predict future urban
growth and landscape changes. Here we direct our attention to
the second type of models because of their predictive power that
can be used to imagine, test and assess the spatial consequences of
urban growth under specific socioeconomic and environmental
conditions. The role of remote sensing is indispensible in the
entire model development process from model conceptualization
to implementation that includes input data preparation, model
calibration, and model validation (Lo and Yang, 2002; Yang and
Lo, 2003).

Although urban areas are quite small relative to the global
land cover, they significantly alter hydrology, biodiversity, bio-
geochemistry, and climate at local, regional, and global scales
(Grimm et al ., 2008). Understanding environmental conse-
quences of urbanization is a critical concern to both the planning
(Alberti, Weeks and Coe, 2004) and global change science
communities (Turner, Lambin and Reenberg, 2007). Urban envi-
ronmental analyses can help understand the status, trends, and
threats in urban areas so that appropriate management actions
can be planed and implemented. This is a research area in which
remote sensing can play a critical role.
Part V (Chs 17 - 21) reviews the latest developments in the syn-
ergistic use of remote sensing and relevant geospatial techniques
for urban environmental analyses. Chapter 17 discusses a remote