Climatologists have long been interested in the differences in observed ambient air temperature between cities and their surrounding rural regions, which have been well documented (Landsberg, 1981). Urban climate studies have traditionally focused on the magnitude of such differences, which collectively describe the Urban Heat Island (UHI) effect. This effect is not restricted to large metropolitan areas, in fact, it has been detected in cities with populations of less than 10,000 people (Karl et al., 1988).
Whether the city is a metropolis or simply a county seat, the UHI effect
is linked to the composition of the underlying surface. Urban development
usually results in a dramatic alteration of the Earth's surface, as natural
vegetation is removed and replaced by non-evaporating, non-transpiring
surfaces (e.g., stone, metal, concrete, etc.) Under such alteration, the
partitioning of incoming solar radiation into fluxes of sensible and latent
heat is skewed in favor of increased sensible heat flux as evapotranspirative
surfaces are reduced. From thermal infrared measurements (10.5-11.5
micrometers)
acquired by the Advanced Very High Resolution Radiometer (AVHRR)
(http://sun1
.cr.usgs.gov/glis/hyper/guide/avhrr) aboard the NOAA series of polar
orbiting satellites, Roth et al. (1989) derived surface temperature data
and assessed its spatial distribution across several cities along the west
coast of North America. Elevated daytime surface temperatures were highly
correlated to the patterns of land cover related to urban land use (i.e.,
higher surface temperatures corresponded to industrial areas while considerably
cooler surface temperatures corresponded to vegetated areas).
In the absence of solar illumination of the surface at night, the
distinction
between surface temperature and urban land use was ill-defined, yet this
is the time when the UHI effect is greatest. In fact, urbanization within
the United States has been found to have the greatest influence on minimum
(compared to maximum or mean) temperature (Karl et al., 1988). This apparent
contradiction is explained by the contention that the sides of buildings
(rather than roofs) may be emitting thermal infrared radiation at night
(Roth et al., 1989).
Although thermal infrared satellite measurements cannot directly measure
the UHI effect, they can be coupled with satellite-derived measurements
of vegetation density to substantially describe the contributing factors
to the UHI effect. The role of vegetation in reducing amount of heat stored
in the soil and surface structures due to transpiration, in contrast to
relatively unvegetated urban areas, has been cited as a significant contributor
to the UHI effect (Carlson et al., 1981; Goward, 1981). Vegetation indices
computed from remotely sensed data have been demonstrated as useful estimators
of the amount of leaf area and related variables associated with agricultural
crops (Gallo and Daughtry , 1987), as well as forests (Nemani and Running,
1989).
Gallo et al. (1993a, 1993b) compared vegetation indices and radiant
surface temperature acquired by the AVHRR with minimum air temperatures
observed for urban and rural locations. The satellite-derived vegetation
index data were linearly related to the difference in observed urban and
rural temperatures. Data derived from the Operational Linescan System (OLS)
(http://www.ngdc.noaa.gov/dmsp/ols.html)
of the U.S. Air Force Defense Meteorological Satellite Program (DMSP) also
appeared useful for the analysis of urban and rural locations as the data
acquired at night identifies the light associated with urban locales (Gallo
et al., 1995). Given the relationship between the UHI effect, urban surface
temperatures and the texture of land cover influenced by urban land use,
this exercise employs a multi-sensor approach to assess the climatic implications
of urbanization at the regional-scale (i.e., tens of kilometers). The AVHRR
(http://sun1
.cr.usgs.gov/glis/hyper/guide/avhrr)
instrument provides data that can be used to derive both surface temperature
and a measure of vegetation at the resolution of 1 km at the surface. Identification
of urban land cover is attainable through Landsat MSS
(http://su
n1.cr.usgs.gov/glis/hyper/guide/landsat) at a resolution of 30 meters.
In addition, the DMSP-OLS (http://www.ngdc.no
aa.gov/dmsp/ols.html) provides information on the nighttime anthropogenic
sources of light at a resolution of 2.7 km that can be used as an additional
tool in verifying the distinction between urban and rural locations.
This module focuses on seven meteorological stations in the Dallas-Ft.
Worth, TX, USA (DFW) metropolitan area. The general objective of the module
includes familiarization with the data and products available from the
AVHRR, Landsat MSS and DMSP-OLS sensors, and their applications related
to urbanization. A more specific objective is to determine if the seven
meteorological stations can be characterized as "urban" or "rural"
based upon their climatologically significant surface characteristics.
An objective method for determining whether a station is urban or rural
would be beneficial for assessment of global climate change, as the influence
of urban stations could be extracted from future analyses of temperature
trends.
In the first section, values of a vegetation index and radiant surface
temperature are obtained from the AVHRR for the stations. In the second
section, the relationship between these values and landcover types is introduced,
and data is provided to make comparisons for two of the stations. Finally,
in the third section, the utility of DMSP-OLS as a tool for designating
a station as urban or rural is explored.
All data in the exercise are derived from three remote sensors-- AVHRR,
(http://sun1
.cr.usgs.gov/glis/hyper/guide/avhrr) for values of a vegetation index
and radiant surface temperature, Landsat MSS
(http://su
n1.cr.usgs.gov/glis/hyper/guide/landsat) for land cover data and
DMSP-OLS
(http://www.ngdc.no
aa.gov/dmsp/ols.html) for light intensity data. The data sets are geared
to allow the student to extract necessary information in the vicinity of
seven meteorological stations in the DFW region.