Full text: Remote sensing for resources development and environmental management (Volume 2)

Figure 5 A. The high-water situation in a part of 
the Porttipahta reservoir in northern Finland. The 
symbol I displays surrounding dry areas while other 
symbols indicate aquatic areas. B. Lower littoral 
areas 2.3 m below the water level of Fig. 5A are 
displayed with white pixels. C. Upper littoral 
areas up to 5 m above the water level are indicated 
with various dark pixels (Jantunen and Raitala 1984). 
5. DISCUSSION 
The continuity of the Landsat program from 1972 
until now has been very promising with respect to 
long-term studies. During the last 14 years the 
main focus of research has been to develop methods 
and approaches for practical applications of 
monitoring remote sensing. The latest satellite in 
this series, Landsat 5, is expected to stop trans 
mitting data before replacement. This in itself in 
creases expectations for the French SPOT satellite 
remote sensing, but there will still be abundant 
need of information especially on environmental 
changes over the last decade, and this need can be 
met only by using the old Landsat MSS data. 
The use of previous Landsat data should not be 
diminished merely because of the availability of new 
satellite data with better spectral and ground re 
solution. Although remote sensing science itself 
will gain advantages with the increased accuracy of 
the radiation recordings many more practical demands 
of other natural and environmental sciences will 
derive advantage from the time perspective offered 
by the Landsat data. This is especially evident 
within the spheres of aquatic research and inves 
tigation because these repeated registrations may 
often constitute the only possibility of tracing the 
more original situation before the changes, appear 
ing almost daily, have taken place. 
There is no denying the charm of novelty with 
respect to new and ever-better satellite data. But 
we should also maximize the continued use of all 
satellite information and share the evident benefits 
of multitemporal satellite data with all possible 
diversified users, including scientists, decision 
makers and ordinary people interested in the state 
of the environment. 
REFERENCES 
Arkimaa, H. and J. Raitala 1981. Landsat example of 
small lake classification. Aqua Fennica 11: 55- 
60. 
Arkimaa, H. and J. Raitala 1984. Landsat classifi 
cation of the coastal water areas of the Bothnian 
Bay off Oulu. Finnish Marine Research 250: 45-51. 
Beardsley, T. 1986. Remote sensing. Nature 319: 4. 
Hammack, J.C. 1977. Landsat goes to sea. Photo- 
gramm. Eng. Remote Sensing 43: 683-691. 
Jantunen, H. and J. Raitala 1984. Locating shore 
line changes in the Porttipahta (Finland) water 
reservoir by using multitemporal Landsat data. 
Photogrammetria 39: 1-12. 
Lindell, T. 1980. Calibration of Landsat data for 
mapping of water quality in Malaren, Sweden. 
Statens naturvardsverk PM 1266, Uppsala, Sweden. 
Raitala, J. and H. Jantunen and S. Hellsten 1984a. 
A Landsat-assisted study of the aquatic areas of 
the Lake Kemijarvi region, Northern Finland. 
Earth, Moon, and Planets 31: 183-216. 
Raitala, J. and H. Jantunen and V. Myllymaa 1984b. 
Developments in the evaluation of small lake water 
quality from digital Landsat MSS data, Kuusamo, 
Northeast Finland. Earth, Moon, and Planets 31: 
249-264. 
Raitala, J. and J. Siira and H. Arkimaa 1984c. 
Landsat classification of the hydrolittoral areas 
of the Bay of Liminka (Gulf of Bothnia, Finland). 
Aquilo Ser. Bot. 20: 14-23. 
Raitala, J. and J. Lampinen 1985. A Landsat study 
of the aquatic vegetation of the Lake Luodonjarvi 
reservoir, Western Finland. Aquatic Botany 21: 
325-346. 
Acknowledgement: The writing of this paper was per 
formed while the author held a NRC - NASA Resident 
Research Associateship at the Jet Propulsion Labora 
tory, Calif. Institute of Technology. 
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