Full text: Remote sensing for resources development and environmental management (Volume 1)

312 
rate allows the laser to produce many individual 
measurements per single tree and it is thus possible 
to get a representative average height and reflection 
measurement per tree or plant species. 
Figure 1. Laser height and reflection profile of a 
forested transect. 
The separation of vegetation and terrain surfaces 
based on reflection alone is thus very restricted 
and this can be seen in Figure 2 where mean reflec 
tion values for a number of uniform vegetation sur 
faces are portrayed. It is obvious that the poten 
tial of laser remote sensing can greatly be enhanced 
if the analysis can be extended to include multi- 
spectral capabilities. 
Figure 2. Vegetation differentiation with laser 
reflection measurements at 904 nm wavelength. 
2.3 Developing a multispectral airborne laser 
Having shown the potential of single wavelength air 
borne laser observation it is a logical extension to 
suggest that the use of multispectral lasers be con 
sidered. Unfortunately no tunable airborne lasers 
have yet been developed, but the logical alternative 
is to use several lasers simultaneously, where each 
type operates at a different wavelength. This raises 
the question as to the choice of wavelength to be 
used. This is not a simple question in view of the 
different requirements needed for the separation of 
vegetation type, for differentiations amongst rock 
types, and for identifying different soil conditions. 
Each user is likely to require reflection measure 
ments at different wavelength ranges. For the separ 
ation of vegetation types, vegetation stress, and 
vegetation vigour the chlorophyll sensitive red/near 
infrared reflection bands are likely to be most 
appropriate (Tucker 1979, Curran and Milton 1983, 
Horler et al 1983, Elridge and Lyon 1984). For 
geological applications bands at 600, 1200, 1600 and 
2200 nm wavelengths appear to be most desirable 
(Siegrist and Schnetzler 1980, Buckingham and Sommer 
1983, Gladwell et al 1983, and Elvidge and Lyon 
1984). For soil assessments the most useful spectral 
bands are also in the visible and near infrared wave 
length range (Stoner and Baumgardner 1981) but these 
might differ from the geological band depending on 
soil conditions. 
At the current state of technology the testing of 
dual or triple lasers for specific applications is 
likely to be most profitable and the potential of 
such an approach is illustrated in the following 
example which deals with the quantification of soils 
to facilitate fertilizer assessment in agricultural 
fields. 
3 SPECTRAL REFLECTION MEASUREMENTS TO DIFFERENTIATE 
SOIL CONDITIONS 
Most agricultural fields have great soil variability 
not only because soils have a naturally high chemical 
variability but most fields do not follow soil type 
boundaries and it is very common at least on the 
West Coast of Canada that two or three soil types 
are present in most agricultural fields. If the 
soils are contrasting management is considerably 
more difficult. The use of fertilizers in intensive 
agriculture is becoming a major component in the 
economics of farming and there is an increasing 
need to apply fertilizers in a more efficient 
manner so as to minimize over and under fertilization 
of any part of the field and to overcome production 
deficiencies in some parts of the field. It is pro 
posed that remote sensing using a multispectral 
laser system can aid in this process. To show how 
this potential can be realized a number of soil 
reflection measurements were made using a multi 
channel spectro-radiometer to demonstrate what soil 
properties can best be predicted from spectral 
reflection measurements, what wavelengths are most 
useful in separating soil types, and how this infor 
mation will aid in the development of a multispectral 
laser. 
It is well known that organic matter and soil 
provenance has a significant influence on spectral 
reflection, and soil mapping with multispectral data 
has been attempted by numerous researchers (e.g. 
Kristoff et al 1973, Westin and Frazee 1976, Cipra 
et al 1980) . The main problem is that vegetation 
cover, crop residue, disk pattern, and soil moisture 
(Gausman et al 1975 and 1977, Huete et al 1985) 
seriously affect the soil reflection spectra. It is 
anticipated that the use of a multispectral laser 
system will facilitate such analysis since it can 
provide an assessment of surface roughness at the 
same time the reflection data is obtained. 
3.1 Method of analysis 
Three experiments were carried out at three different 
sites. The first site represented a bare field which 
had been plowed and which had a mixture of organic 
and marine clay rich soils. Thirty surface soil 
samples were collected for laboratory analysis and 
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