Full text: Proceedings of the Symposium on Global and Environmental Monitoring (Part 1)

Table 5: Landsat TM Bands and Transformations Employed in Analysis. 
Band 1 
Band 2 
Band 3 
Band 4 
Band 5 
Band 6 
Band 7 
Single Band 
(TM only) 
(TMS only) 
Band 4 - Band 1 
Band 4 - Band 2 
Band 4 - Band 3 
Band 4 - Band 5 
Band 4 - Band 6 
Band 4 - Band 7 
Band 4/Band 1 
Band 4/Band 2 
Band 4/Band 3 
Band 4/Band 5 
Band 4/Band 6 
Band 4/Band 7 
Band 2/Band 3 
Band 3/Band 1 
Band 5/Band 7 
Band 6/Band 7 
Band Difference 
(TM only) 
(TMS only) 
Simple Band Ratio 
(TM only) 
(TMS only) 
(TM only) 
(TMS only) 
(Band 4 - Band l)/(Band 4 -f Band 1) 
(Band 4 - Band 2)/(Band 4 + Band 2) 
(Band 4 - Band 3)/(Band 4 -f Band 3) 
(Band 4 - Band 5)/(Band 4 -f Band 5) 
(Band 4 - Band 6)/(Band 4 + Band 6) 
(Band 4 - Band 7)/(Band 4 -f Band 7) 
Normalised Difference 
(TM only) 
(TMS only) 
The presence of small structural and compositional irregularities in the spruce tree canopy 
exerted a much greater influence on the radiance values of the smaller resolution cells of TMS 
than the much larger ones of TM and were primarily responsible for the lower ranking of 
TMS versus TM vegetation indices. However, the vegetation indices employed in the analysis 
are still not sufficiently developed to be able to separate stress-related anomalies from non 
stress-related anomalies in a plant canopy. 
Unless only pixels situated at or near the nadir of the field of view of a sensor are used in 
an analysis, appropriate geometric corrections and re-sampling will be necessary for aircraft- 
acquired spectral data, to reduce the variability in radiance values incurred by the panoramic 
perspective of off-nadir viewing. These effects are even more apparent in hilly and mountainous 
terrain, which would severely hamper the interpretation of TMS-type data. 
Spatial resolution is just one of several factors that need to be considered when assessing 
the capabilities of a sensor system for stress detection in forest canopies, as flexibility in time of 
data acquisition can also be an important determining factor, not only with respect to weather 
conditions, but also for acquiring data at the optimal time(s) of the year and even day for 
maximum discrimination of stress in a canopy. 
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