Landsat TM and NSOOl TMS Spectral Bands 
Both the Landsat Thematic Mapper and NSOOl Thematic Mapper Simulator sensor 
systems measure reflected radiation in the visible to shortwave infrared wavelength region 
(400 - 2500 rim) that conveys information on the state of health and vitality of a plant canopy. 
The airborne NSOOl TMS is the precursor instrument to the spaceborne Landsat TM, and 
differs from the Thematic Mapper only slightly in channel bandwidths and in the presence of 
an additional channel in the near-infrared spectral region. Tables 1, 2, 3, and 4 briefly describe 
the Landsat and NSOOl sensor systems (Slater, 1980, NASA, 1986) and the plant properties 
measured by their respective spectral bands (Tucker, 1978). The most significant difference 
between the two instruments is the nominal 30 m ground spatial resolution or instantaneous 
field of view (IFO V) of the Landsat TM sensor versus the flying height dependent, but generally 
5 - 15 m GIFOV of the NSOOl TMS sensor. It is this factor that can give rise to marked 
variations in the spectral response characteristics of vegetation canopies recorded by the two 
sensor systems. 
Data Collection, Integration, and Analysis 
During the summer of 1986, NASA acquired NSOOl Thematic Mapper Simulator data 
from several test areas in Austria, including the stressed Norway spruce forest used as a test 
site for this study. Stress symptoms in the spruce stand are manifested primarily as a reduction 
in canopy biomass, as determined by DBH-based measurements of leaf area indices (LAI’s) 
obtained from 10-m diametre sample plots spaced at 50-m intervals over the test site and 
reformatted to a LAI isopleth map. 
Landsat TM data from June 1984 (Banninger, 1985) and NSOOl TMS data from July 
1986 (Banninger, 1990) were co-registered to the LAI isopleth map and the weighted average 
of canopy LAI values calculated for each TM and TMS pixel corresponding to the Norway 
spruce forest, using an appropriately scaled 36-point dot grid for the TM and a 12-point dot 
grid for the TMS data sets. A pairwise linear regression analysis between TM and TMS 
pixel values and twenty-nine TM and TMS single and transformed bands (Table 5) selected 
for their ability to measure specific plant biochemical and biophysical properties statistically 
defined those bands and transformations which best discriminated stress in the Norway spruce 
canopy. TMS bands 4 and 5 measure similar plant properties and therefore only band 4 was 
used in the analysis. Before their inclusion in any computations, the TM and TMS bands 
were processed to remove the atmospheric haze component incorporated in their radiance 
values (Crane, 1971). Both data sets represent mid-morning acquisition times and nadir or 
near-nadir situated pixels relative to the field of view of the repective instruments. 
Results and Conclusions 
Although Landsat TM and NSOOl TMS spectral bands have almost identical band cen 
tres and bandwidths, TM data gave overall better results in the descrimination of stressed 
versus non-stressed areas in the Norway spruce forest, whereas TMS data performed better at 
delineating stressed parts of the canopy, but at the expense of including a significant number 
of non-stressed areas within the stressed group. Normalised difference, band difference, and 
the simple band ratio incorporating bands 1 and 4 proved overall best in detecting canopy 
stress for both the TM and TMS data sets employed in the analysis, as did the TM band 
difference utilising bands 3 and 4 and the TMS first principal component. The TM vegetation 
indices, however, ranked higher statistically than those of comparable TMS indices. 
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