Leaf _ Cell 
pigments; structure ; Water content 
h Dominant factor 
v controlling leaf 
J reflectance 
Table 1. Spectral bandwidths (in microns) of some 
satellite systems commonly used for vegetation 
surveyance. 
" c -o ; Near infrared I Middle infrared 
5 £ * 
O 
'i Primary 
v absorption 
J bands 
I Spectral 
[ region 
Figure 1. Typical reflectance curve of green vegeta 
tion (from Hoffer 1978). 
1 The thermal sensors have usually much coarser 
resolution than the ones in visible and NIR. So far 
the best spaceborne resolution is offered by the 
Landsat TM channel 6, wich is 120 m, compared to 30 
m in the other bands. According to Lynn (1986) 
there are no plans, so far, for launching 
satellites equipped with thermal IR sensors with a 
resolution better than_2 km. 
2 The measured radiating temperature is a mixture of 
vegetation and soil temperature. Due to the dynamic 
nature of temperature it is practically impossible 
to get data on soil temperature other than for 
limited experiments. It is therefore difficult to 
separate the influence from vegetation on the 
emitted thermal radiation. 
3 The emissivity of a vegetation canopy and soil 
surface varies with the water content, which in 
turn is very variable in time and space. 
Landsat 
MSS 
Band 4 
0.5 
- 
0.6 
Band 5 
0.6 
- 
0.7 
Band 6 
0.7 
- 
0.8 
Band 7 
0.8 
- 
1.1 
Landsat 
TM 
Band 1 
0.45 
- 
0.52 
Band 2 
0.52 
- 
0.60 
Band 3 
0.63 
- 
0.69 
Band 4 
0.76 
- 
0.90 
Band 5 
1.55 
- 
1.75 
Band 6 
10.4 
- 
12.5 
Band 7 
2.08 
- 
2.35 
SPOT 
Band 1 
0.50 
- 
0.59 
Band 2 
0.61 
- 
0.69 
Band 3 
0.79 
- 
0.89 
Panchromatic 
0.51 
- 
0.73 
TIROS-N 
AVHRR 
Band 1 
0.55 
- 
0.90 
Band 2 
0.725 
- 
1.10 
Band 3 
3.55 
- 
3.93 
Band 4 
10.5 
- 
11.50 
NOAA 6- 
7 AVHRR 
Band 1 
0.58 
- 
0.68 
Band 2 
0.725 
- 
1.10 
Band 3 
3.55 
- 
3.93 
Band 4 
10.5 
- 
11.5 
Band 5 
11.5 
- 
12.5 
* = NOAA 7 only. 
2.3 Microwave radiation 
The microwave radiation of interest to remote sensing 
is usually restricted to 5-500 mm and the most common 
sensing systems working in this band are radar 
instruments. A radar system is not necessarily rest 
ricted to work in the microwave region, though most 
of them do. 
Radar is an example of an active technique, where 
the radiation is transmitted, towards the surface of 
the earth, by the instrument. The returning radiation 
is then measured concerning the time lapse since 
transmittance and properties of the returning signal. 
Two characteristics of the surface being sensed are 
important, surface roughness and conductivity. This 
means that radar imagery can provide information on 
vegetation type (e.g. Bush & Ulaby 1978, Shanmugam 
et.al. 1983) as well as on vegetation conditions 
(e.g. Ulaby et.al 1984, Paloscia & Pampaloni 1984). 
So far, most of the experiences from spaceborne 
radar imagery come from Seasat in 1978. Although 
primarily intended for surveying the oceans many 
investigations over land surfaces were carried out. 
In Canada, the very high cloud frequency contri 
buted to the development of radar instrumentation for 
remote sensing purposes. Cihlar et.al. (1986) 
summarizes the Canadian experiences concerning micro- 
wave remote sensing of agricultural crops, during the 
last 10 years. A general conclusion is that, although 
it is difficult to establish consistent mathematical 
relationships based on the present knowledge, crop 
classification as well as canopy and soil parameters 
can be studied successfully under certain conditions, 
Table 2. The relationship between multispectral 
reflectance and vegetation amount for five wavelength 
bands for a grass canopy. Source: Curran 1980, Tucker 
& Maxwell 1976. 
Waveband 
Waveband 
width (nm) 
Characteristics 
Relationship to 
vegetation amount 
1 Ultraviolet/blue 
350-500 
Strong chlorophyll 
and carotenoid 
absorption 
Strong negative 
2 Green 
500-600 
Reduced level of 
pigment absorption 
Weak positive 
3 Orange/red 
600-700 
Strong chlorophyll 
absorption 
Strong negative 
4 Far red 
700-740 
Transition between 
strong absorbance 
(3) and strong 
reflectance (5) 
Weak negative 
5 Near infrared 
740-800 
High vegetation 
reflectance 
Strong positive 
the data obtained by visible and near infrared 
sensors. 
3. SATELLITE REMOTE SENSING, DATA CONSIDERATIONS 
Remote sensing from space-borne platforms has been an 
area of intensive research the last two decades, and 
computerized analysis of remotely sensed data has 
been common for more than ten years. Both techniques 
and equipment for analysis of the data as well as for 
capture of tl 
rapid developr 
the launch of 
remote sensinc 
resource invenl 
more importanl 
the introducl 
resolution has 
bands has ino 
volumes have 
consequent of 
the demands on 
the gap betw< 
widened. 
Table 3. Spat: 
as Landsat MSS 
most commonly • 
Sensing system 
Landsat MSS 
Landsat TM 
Spot (multispe 
Spot (panchrom 
NOAA 6 and 7 A 
* Local area c 
In spite of th 
and feasibili 
tional applica 
major constra 
tively long i 
chances of obt 
region at a c 
small. Justic 
or two scenes 
launch of the 
parts of West 
worse over t 
this problem 1 
weather sate11 
recordings (He 
et. al. 198S 
parisons betwe 
carried out, 
information c 
Townshend & 
represented e 
bands 5 and 7 
The ability 
satellite wi] 
solve some c 
repeat cycle 
using the ofi 
average repee 
maximum 5 days 
The use of 
views, e.g. N( 
however sevet 
mainly from tl 
1 Varying ati 
length 
2 Vegetation 
properties, 
3 The topogr; 
pronounced 
4 Distorted p: 
A comprehe: 
on SPOT and 
Cracknell (l 1 
authors have 
(NOAA AVHRR).