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Title
Remote sensing for resources development and environmental management
Author
Damen, M. C. J.

456
Table 2. Key to the land-use units
facilitated by the extensive network and
access roads in the Nairobi area.
Symbol
Land-use units
CT
coffee, tea
or pineapple
F
forest
G
grassland
B
buildup
S
sisal
Table
3. Phototones of the land-use
units.
Phototone
Land-use
Land-use zone
black :
water bodies
S3,S4,P4
green :
bare red soil or quarries
E.S2.P1,P3
red :
bright red :
soft wood plantations
M1 ,E
coffee
S2,S3,S4
pineapple
S3
foodcrops
E,S1,S2,S5
riverbottom vegetation and
wetlands
S3,P3
dark red :
indigenous forest
M1,M2,S3,S5
low density residential
S5
pinkish red :
tea
S1 f S4
yellow:
yellow :
grasslands
M2,E,P1,P2,P3
pinkish yel :
dairy grasslands
S4
brown :
brown :
sisal
P4
orange brown:
sisal overgrown with grass
P3
blue :
bright light:
roads
P1 ,P2
blue : industrial
high density residential
grasslands with bare grey
soil
: commerce and administration
middle density residential
E,P1
S5,P2
S5,P2
agricultural activity, building construction
costs), topography (altitude, drainage, set
tlement, infrastructure) and the vegetation
(a function of geomorphology, climate and
soil) (Morgan 1969).
For effective planning these elements must
be considered and assessed and the LANDSAT
imagery creates the appropriate basis for
asking pertinent questions.
Specific conclusions are:
If properly used LANDSAT data could replace
the intermediate scale inventory presently
compiled from aerial photography at scales
in the 1:100.000 to 1:250.000 range. This
might be both cost and time effective. In
particular the amount of information and
its geographical location presented in the
LANDSAT scene is an integration of the many
influences at the earth's surface, and can
guide the landscape planner's work
effectively.
The level of detail available provides an
appropriate insight into land-use processes
for the landscape planner at a regional
level. This is particularly important for
integrated planning and should contribute
to better designs and plans for future
development.
REFERENCES
Anderson, J.R. et al. 1976. A Land-use and
Land-cover Classification System for Use
with Remote Sensor Data. Geological Survey
Professional Paper 964. Washington DC:
US Government Printing Office.
Duchhart, I. 1986. Inleiding landschapsplan-
ning in ontwikkelingslanden. Wageningen:
Landbouw Hogeschool. *
Government of Kenya 1983. Development Plan
1984-1988. Nairobi: Government Printer.
Grootenhuis, F., H.Weeda & K.Kalambo 1986.
An integrated study of the Nairobi area.
Rotterdam: Balkema.
Heetman, H. & I.Duchhart 1979. A short study
of the landscape planning aspects of the
Bura irrigation and settlement project,
Kenya. Wageningen: University of Agriculture
McHarg, I.L. 1969. Design with Nature.
Philadelphia: Natural History Press.
Morgan, W.T.W. 1969 . Nairobi: City and region
London: Oxford University Press.
Timberlake, L. 1985. Africa in crisis. London
and Washington DC: International Institute
for Environmental Development.
Tjia, J.G.J. & Y.H.Tjiook 1985. A landscape
plan for Cilanang Watershed. Wageningen:
Agricultural University.
Tolba, M. 1982. Opening address to^jthe Session
of a Special Character at the 10 r Governing
Council of the United Natons Environmental
Program. Nairobi: UNEP.
LANDSAT data in a photographic print at
1:100.000 scale proved to be interpretable
at a surprisingly detailed level. Expanding
the 1:1M scale land-cover map to a map of
land-use at 1:100.000 scale required little
fieldwork. The combination of fieldwork and
pertinent information from other sources
led to a rapid understanding of the spa
tial patterns of interaction between man
and the bio-physical environment in the
Nairobi area.
Interpretation of the colour, tone and tex
ture of the LANDSAT FCC was relatively easy
at the 1:100.000 scale. Many components
could be interpreted and when related to
existing map information, provided a valua
ble level of information for mapping land-
use zones. Checking of interpretation was