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RS-1 data 
asentative 
jes due to 
the inherent differences in resolution and 
imaging geometry between the two sensors. 
Further analysis of the SAR data will include: 
1) the merging of two flight lines with 
opposite look directions to eliminate radar 
shadowing in mountainous terrain; 2) 
radiometric rectification to correct for local 
incidence angle effects; 3) texture analysis 
to emphasize variations between land cover 
classes. 
5. DISCUSSION AND RESULTS 
The preliminary focus was on the SPOT 
segment of the project since at the time of 
printing, the SAR segment was at a 
preliminary stage. Results of the SAR 
investigation will be presented in the 
symposium session and will be reported in a 
later publication. 
The SPOT ortho-rectification results are 
described in some detail as the availability of 
the ortho-rectification software and digital 
elevation information were unique in the 
authors' experience. 
The ortho-correction procedure recently 
developed at the Canada Centre for Remote 
Sensing (CCRS) (Toutin and Carbonneau, 
1992) and transferred to PCI software (PCI, 
1993) for commercialization was employed. 
Simply described, the technique uses a four 
step process: 1) reading the digital & 
ephemeral data (satellite orbital and path 
information) from tape; 2) collecting ground 
control points (including elevation 
information); 3) calculating the algorithm; 4) 
and correcting the data. 
The ortho-rectification package is compatible 
with a number of the processing levels 
provided by the satellite data vendors 
(RADARSAT International Inc. in Canada). In 
the first attempt at correcting the SPOT PLA 
and MLA data, georeferenced data was used. 
Once ortho-corrected, these data yielded 
Root Mean Squared errors (RMS errors) of 22 
m in the Eastings direction and 6 m in 
Northings. 
451 
The MLA data set were included in the 
research effort to allow MacMillan Bloedel 
staff to familiarize themselves with digital 
classification and land cover discrimination 
techniques. The RMS errors achieved with 
the MLA data were 17 m in Eastings and 11 
m in Northings. 
An effort to improve the correction was 
sought. Discussions with the author of the 
correction algorithms suggested 
improvements to the accuracies could be 
expected the input data was restricted to the 
raw or bulk processed levels. 
The authors are confident that a second 
attempt at ortho-correction with the more 
appropriate input data will increase the 
accuracies. 
6. SUMMARY - PLANNED FUTURE WORK 
The use of SPOT PLA for detecting and 
accurately mapping forest harvesting features 
has been demonstrated. Ortho-correction of 
the SPOT data, using the raw and bulk 
products as input, will be attempted. Current 
results are encouraging and are expected to 
fulfil MacMillan Bloedel’s stringent 
requirements. 
Work will continue to further improve the 
correction and information extraction 
techniques. SPOT and SAR mapping results 
will be compared with traditional 
photogrammetric techniques. 
SAR data analysis will include the 
development of radiometric and geometric 
correction methodologies in addition to the 
investigation of texture analysis algorithms to 
accentuate variations between land cover 
classes. 
The radiometric and geometric correction of 
the simulated RADARSAT and the ERS-1 data 
will serve as a demonstration for the possible 
capabilities of RADARSAT data. Although the 
results of the mapping accuracies with SAR 
data are not directly applicable to the 
RADARSAT case, the exercise should 
demonstrate the general capabilities of radar