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CONSTRUCTION OF GROUND REFLECTANCE MAP FROM REMOTE SENSING 
DATA AND ITS APPLICATION TO TEMPORAL DATA ANALYSIS 
T.Kusaka, Y.Kawata, H. Okazaki and S.Ueno 
Kanazawa Institute of Technology, P.O. Kanazawa-South, 
Nonoichimachi, Ishikawa 921 , JAPAN 
ABSTRACT 
In the present study we describe a method to estimate the 
optical thickness of the atmospheric haze from a Landsat 
data set itself. Then we give a conversion method from the 
original CCT level data to the true ground albedo data with 
an aid of the Atmospheric Effect Correction System developed 
at Kanazawa Institute of Technology. We also show that the 
signature extension becomes possible by correcting the 
original Landsat data for the atmospheric effects and this 
approach will be a powerful tool in temporal data analysis. 
Finally, a processing system implementing the signature 
extension system is described. We introduce a new and 
powerful table look-up method in classification and a data 
base containing the statistical information on albedos for 
various ground classes with time. 
INTRODUCTION 
It has been known that the contrast of the surface images 
obtained by the Landsat's MSS is frequently degraded by 
atmospheric haze. This atmospheric haze causes a significant 
decrease in classification accuracy. In the temporal 
analysis of one particular geographyical location it is very 
unfortunate that we can not compare a Landsat data set 
quantitatively with another Landsat data set taken at 
different time ( because of different haze conditions). If 
the optical thickness of haze is known, the true spectral 
response by ground, namely the ground albedo, can be 
computed from the observed data set. This problem has been 
studied by Odell and Weinman (Odell 1975 ) and more 
intensively by us (Kawata 1978;Haba 1979). It is not always 
possible to get the optical thickness of the haze by direct 
measurement . In addition to the foregoing discussion, 
it is imperative to increase performance in data processing 
as the remote sensing of the Eath surface becomes 
operational and the volume of data increases. These are 
major motivations by which we began to work on the present 
study. 
Here we first describe a method to estimate the value 
of the optical thickness of the haze from the remotely 
sensed data itself. Then we convert a relative CCT level 
data set into a absolute ground albedo data set using the 
Atmospheric Effect Correction System. Finally , we give a 
signature extension system consisting of the data base phase 
and table look-up phase.