Full text: Resource and environmental monitoring

  
eli 
  
  
410 
minimum air temperatures observed for urban and rural 
locations. The satellite-derived vegetation index data of a 
monthly composite were lincarly related to the difference in 
observed urban and rural minimum temperatures, explaining 
37% of its variation (versus 15% using radiant surface 
temperature). Thus, during the growing season and in 
well-vegetated regions, a vegetation index is a useful 
parameter for assessing the UHI effect. 
In addition to land cover parameters derived from the 
AVHRR, Gallo er al. (1995) found that “city lights” data 
(Elvidge er al., 1997) derived from the 0.6-0.9 um band 
of the Operational Linescan System (OLS) of the U.S. Air 
Force Defense Meteorological Satellite Program (DMSP) 
appeared useful in distinguishing between urban and rural 
locations. The “city lights” data set offers the prospect of 
periodic and objective assessments of urban expansion at 
a continental-scale. 
The general objective of the paper is to provide an 
overview of the application of data and products available 
from the AVHRR, Landsat MSS and DMSP-OLS sensors 
to studies of urban climate. A more specific objective is 
to demonstrate how the data from these sensors can be 
used to assess whether a given meteorological station can 
be characterized as "urban" or "rural." An objective 
method for determining whether‘à station is urban or rural 
would bc beneficial for the assessment of global climate 
change, as the influence of urban stations could be 
extracted from future analyses of temperature trends. 
DATA AND METHODOLOGY 
Data Analysis 
The Dallas-Fort Worth (DFW), Texas, USA, metropolitan 
arca was selected for this analysis. The population 
associated with this metropolitan region has increased 
from 2.3 million in 1970 to an estimated 4.4 million in 
1995 (U.S. Bureau of the Census, 1997) . AVHRR and 
DMSP-OLS data were sampled for 7 climatological 
stations (Table 1) included in the DFW region. These 
stations are part of a larger network of stations throughout 
the USA being utilized to examine the heat-island effect 
(Gallo et al., 19933). The reported AVHRR and DMSP- 
OLS values are the mean values for 3X3 km? “windows” 
centered on the location of the climatological stations, 
unless otherwise noted. 
AVHRR-Derived Vegetation Index 
Normalized Difference Vegetation Index (NDVI) values, 
computed (equation 1) from the visible (C1; 0.58- 0.68 
pm) and near-infrared (C2; 0.72 - 1.1 um) data acquired 
by the AVHRR as 
NDVi = (C2-C1)/ (C2 + C1), [1] 
were obtained from two products for use in this analysis. 
The NDVI, like most other vegetation indices, exploits the 
difference in the reflectance of vegetation in the near- 
infrared wavelengths compared to visible wavelengths. 
Multiple scenes for a given time period (typically 10-day, 
14-day or monthly) are composited by retaining, on a 
pixel-by-pixel basis, the maximum observed value of 
NDVI during the interval. Composited NDVI images 
minimize the probability that pixels with cloud or haze 
contamination (which result in lower NDVI values) will 
remain in the image. 
Fourteen-day composited NDVI and individual channel 
AVHRR data are readily available for the Conterminous 
USA at the 1-km resolution in a Lambert Azimuthal 
Equal Area (LAEA) projection. NDVI values were 
extracted from a CD-ROM product (USGS, 1991) for two 
14-day composite intervals of 1991. The data of the two 
14-day composites were then further composited over a 
28-day interval (5 July through 1 August 1991). 
AVHRR-Derived Radiant Surface Temperature 
Radiant surface temperature (Tsfc) can be approximated 
from calibrated thermal IR data of channels 4 (T4; 10.3 - 
11.3 um) and 5 (T5; 11.5 - 12.5 um) of the AVHRR 
sensor for a surface emissivity of 1.0 as suggested by 
Price (1990) as 
Tsfc = T4 + 3.3(T4-T5) . (2) 
The T4 and TS data associated with the NDVI values 
composited over the 5 July through August 1991 interval 
were used to compute Tsfc. The Tsfc of this interval was 
selected for analysis to permit direct examination of the 
relationship between Tsfc and NDVI at the climate 
stations. 
DMSP-OLS-Derived “City Lights" Data 
The DMSP-OLS data have historically been used to 
monitor the global distribution of clouds and cloud top 
temperatures. However, the data acquired in the 
visible/near-infrared band (0.6-0.9 um) at night under 
cloud-free conditions can be used to identify light emitted 
at the surface of the earth. Gallo e: al. (1995) 
demonstrated that this data might be useful for 
identification of urban and rural locations as it primarily 
identifies the light associated with urban locales (e.g., 
“city lights”). However, caution must be used when these 
data are used for identification of urban areas as, on any 
single night, the burning of forests (e.g., burning biomass) 
and fossil fuels could be misinterpreted to represent the 
location of an urban areas. 
Two DMSP-OLS data sets were used in this analysis. The 
first DMSP-OLS data product was based on a composite 
of 231 orbits that were used to identify stable (e.g., urban 
areas) from non-stable (e.g., burning biomass) light 
sources. The orbital data were mapped to a |-km 
projection (Goodes Homolosine) to match the globally 
available 1-km AVHRR data. The DMSP-OLS data were 
provided by the National Geophysical Data Center and 
Intemational Archives of Photogrammetry and Remote Sensing. Vol. XXXII, Part 7, Budapest, 1998 
  
 
	        
Waiting...

Note to user

Dear user,

In response to current developments in the web technology used by the Goobi viewer, the software no longer supports your browser.

Please use one of the following browsers to display this page correctly.

Thank you.