- 882 - 
Regression lines of the form y - axP were fitted to the various data 
sets and correlation coefficients computed. The r values for all of the 
data sets were approximately *0.9 or better and the graph which shows kwh 
as a function of IUA dome volume is of particular interest since it 
demonstrates that even very small-scale, relatively crude satellite image 
data provides potential for monitoring urban energy consumption patterns 
(Figure 8). As the analyses of additional images of other areas of the 
United States have produced comparable results, it appears feasible to 
develop regression equations which reflect differences in regional urban 
energy demands. A detailed report of these investigations is being 
prepared. 
Lo, 
Norc 
Ogrc 
Conclusion Tobl 
Satellite image data may be used to establish regression equations of 
the form y = axP which relate population to urban built-up area measured U.S 
from Landsat images, and urban energy consumption in kwh to the volume of - 
three-dimensional figures constructed from microdensitometer profiles of 
IUA's recorded on nighttime DMSP images. Correlation coefficients of 
+0.8 or better indicate the validity of the relationships and demonstrate U.S 
the potential for monitoring urban population and energy utilization Spin 
patterns on a regional or national basis from satellite data. A full 
evaluation of this potential, however, will only be realized when, in 
addition to being timely and repetitive, the satellite data are of 
sufficient scale, resolution and radiometric fidelity to justify their 
use in models designed to provide for the efficient allocation of resources. 
Acknowledgements 
The contributions of Dr. C. P. Lo and Dr. C. W. Pannell to earlier 
studies of China's urban population patterns are gratefully acknowledged. 
Stephen Zupko performed the microdensitometer traces on the DMSP images 
and assisted with the computations; and Miss Ann Yi-rong Hsu established 
the data structures used to create the Calcomp perspectives. The 
cooperation of numerous utilities is greatly appreciated. Diagrams were 
prepared by The University of Georgia Cartographic Services Laboratory. 
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