Image Processing Reference
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sector and include the Système Probatoire d' Observation de la Terre, or SPOT
(Martin et al. 1988 ), IKONOS (Dial et al. 2003 ), and Quickbird (Sawaya et al.
2003 ). These high-resolution systems enable highly detailed land cover/land use and
ecological characterization of urban and suburban regions (Weber 1994 ; Greenhill
et al. 2003 ; Sawaya et al. 2003 ; Small 2003, 2007 ; Weber and Puissant 2003 ). Data
from these commercial systems are typically limited in both spatial and temporal
coverage, and spectral coverage is generally limited to the visible and near infrared
wavelengths (Jensen 2000 ). Active remote sensing of urban areas using radar and
lidar technologies is also becoming more common, and provides new tools for use
in urban ecology (Dell'Acqua and Gamba 2001 ; Gamba et al. 2006 )
The ready availability of both commercial and governmental satellite data has led
to several comparative studies of urban centers under national and multinational
auspices. For example, several such programs have focused on European cities
(Eurostat 1995 ; Churchill and Hubbard 1994 ; Weber 2001 ). The project MOLAND
was initiated in 1998 (under the name of Murbandy - Monitoring Urban Dynamics)
with the objective to monitor the development of urban areas and identify trends at
the European scale (Lavalle et al. 2001 ). The United States' Defense Meteorological
Satellite Program Operational Linescan Systems (DMSP OLS) nighttime imagery of
global light distributions has been used to estimate urban to suburban population
densities and urban extents throughout the world (Sutton 2003 ; Elvidge et al. 2003 ;
Imhoff et al. 1997 ). Astronaut photography has also been used to track urban growth
in several US cities (Robinson et al. 2000 ). The 100 Cites Project (formerly known
as the Urban Environmental Monitoring Project) based at Arizona State University
(Stefanov et al. 2001a ; Netzband and Stefanov 2003 ; Ramsey 2003 ; Netzband et al.
2007 ; Stefanov et al. 2007 ; Wentz et al. 2009 ) seeks to foster collaborative use of
remotely sensed data - primarily EOS datasets - and analysis techniques to advance
understanding of urban development trajectories around the world.
In this chapter we will focus on the complementary use of two EOS- based sensors
for urban ecological analysis to assess the question “does urban landscape structure influ-
ence biophysical parameters at the 1 km scale?” We use the Advanced Spaceborne
Thermal Emission and Reflection Radiometer (ASTER) on board the Terra satellite, and
the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on board both
the Terra and Aqua satellites to answer this question. The ASTER instrument was built
by the Japanese Ministry of International Trade and Industry, and acquires surface data
in the visible to near-infrared (three bands at 15 m/pixel), shortwave infrared (six bands
at 30 m/pixel; data from these bands acquired after April 2008 are not usable due to
anomalously high detector temperatures), and thermal-infrared (five bands at 90 m/pixel)
wavelength regions of the electromagnetic spectrum. An additional panchromatic band
is included to allow for the generation of high-resolution (30 m postings) digital elevation
models from ASTER scenes (Abrams 2000 ). Each ASTER scene captures a 60 × 60 km
area. The expanded wavelength range, spectral resolution, and increased spatial resolu-
tion of ASTER allow for increased characterization and investigation of urban/peri-urban
land cover and biophysical parameters (biomass, albedo, spatial metrics, and surface
temperature/emissivity) relative to the Landsat sensors (Ramsey et al. 1999 ; Stefanov
et al. 2001a, 2007 ; Zhu and Blumberg 2002 ; Ramsey 2003 ; Netzband and Stefanov
2003 ; Schöpfer and Moeller 2006 ; Stefanov and Netzband 2005 ; Wentz et al. 2008 ).
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