412
have Tsfe/NDVI values that do not correspond to any one
land cover class.
The OLS-pct values associated with the seven DFW
climatic stations is also displayed as a function of NDVI
(Figure 2). Generally those stations with large OLS-pct
values displayed lower NDVI values. A clear distinction
exists between the OLS-pct values of stations 279, 281
and 285, and the other stations. A similar distinction,
although not as great, was observed in the OLS-cal data.
The OLS-pct values suggest that stations 279, 281 and
285 might be considered "urban." These three stations
were indeed identified as "urban" through a manual
procedure described in Gallo er al. (1993a).
The OLS data, combined with the NDVI and Tsfc data
that describe the surface energetic response to urban land
cover, provide a meteorologically sensitive
characterization of stations as urban and rural (e.g.,
Figures 2 and 3). Comparing the urban assessment based
on land cover, the relatively large OLS-pct values for
station 279 and 281 in Figure 3 suggest that the OLS data
may be particularly useful in discerning urban and rural
land covers along the transition zones between classes.
The use of OLS values to characterize stations as urban or
rural in the transitional area between urban and rural
locations could be especially beneficial for future
assessments of urbanization-induced temporal
discontinuities in temperature observations. Landsberg
(1981) pointed out that the largest gradient in urban-rural
ambient temperatures occurred along the urban-rural
fringe at the periphery of metropolitan areas. Many
long-term climate observing stations that are included in
historical networks, due in part to their rural settings, will
be vulnerable to discontinuous temperature changes due
to encroaching urbanization. Planned analysis include the
use of AVHRR and DMSP-OLS data to assess the
urbanization at stations included in several U.S. and
global climatological data sets.
SUMMARY
The process of urbanization is dynamic. As urban areas
expand into regions of varied vegetation, due to culturally
diverse land use, assessment of the urban expansion relative
to the location of climate observation stations will continue to
be critical. This paper demonstrates the value of using
multiple sensors in the identification of urban heat islands.
The repartitioning of surface energy fluxes due to urban
land use change can be implicitly linked to lower values
of NDVI and higher values of radiant surface temperature
with the AVHRR data. Higher resolution land cover data
from classified Landsat MSS data can be used to relate
land cover classes to observed changes in NDVI and °
radiant surface temperature. The DMSP-OLS data
exploits anthropogenic nighttime light sources as a further
tool for the distinction between urban and rural locales.
Additionally, the DMSP data may be most applicable in
cvaluation of urban heat islands in regions that are sparsely
vegetated. The information provided by a single sensor,
while valuable, can clearly be enhanced by the use of
multiple sensors.
ACKNOWLEDGMENTS
The data included in this analysis were provided by
NOAA's National Climatic Data Center and National
Geophysical Data Center, and the USGS/EROS Data
Center. This research was partially funded by NOAA's
Office of Global Programs’ Climate and Global Change
Program and NASA.
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