International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B2. Istanbul 2004
Especially when comparing the results of the first and the last
time step of the time series (Figure 4) regarding the class
*Bushland / shrubs* (3), very high portions of the land cover
classes 1 (“Near natural + old secondary forest") and 2 (*Sec-
ondary forest^) for the earlier time slice are revealed, pointing at
major forest loss. When looking at the diagramms comparing
the neighbouring time steps (not shown here), the unchanged
portion of class 3 is always relatively low. This allows to sus-
pect that bushland does not stay bushland for long, but either
regenerates to secondary forest or is further cleared and thus
changes to grassland or agricultural land. Similar fluctuating
dynamics can be noticed for the class "Secondary forest^ (2),
but here the largest portion of the changed classes is always
“Near natural + old secondary forest“ (1). This could be due to
misclassifications because of spectral similarities. between
pixels making up the classes | and 2. But portions of land cover
class 1 (for 1972/73) in class 2 (2001) can also be related to
forest loss if these have been compensated for by such forest
plantations that could not be distinguished from the natural”
forest formations as in the case of e.g. Maesopsis eminii. As can
be seen from Figure 4 forest loss has mainly occurred in favour
of bushland (3), grassland (6) and agricultural land (10).
Whereas the also high portions of class | (“Near natural + old
secondary forest“) in class 2 (Secondary forest") and 7 (Plan-
tation forest — Pinus patula^) have to be interpreted with care,
as discussed above.
5. CONCLUSION AND OUTLOOK
The classification of Landsat imagery for 7 time steps between
1972 and 2001 aimed at a homogeneous (unlike Brooks et al.,
1999) as well as dense (unlike ICRAF, 1996 with only 2 time
steps) time series for documenting land cover change in the
wider Kakamega Forest area in order to contribute to biodiver-
sity research and management (compare Schaab et al., 2002).
For the first time such a consistent land cover time series for
Kakamega Forest and its associated forest areas is now avail-
able which is differentiating between forest formations and
covers the past 30 years.
The results reveal distinct pattern in land cover change and thus
regarding disturbance and fragmentation for the different forest
areas considered. In total a decrease in forest area is observed
due to clear fellings of larger areas as well as due to selective
logging opening the forest cover by numerous small gaps. At
the same time for some areas, especially for those under strict
conservation managment, regeneration via successional stages
can be observed in the time series. So far the classification
quality has been only assessed by a visual interpretation. Colour
aerial photography from 2000 will be hopefully available soon
for the demanded accuracy assessment via error matrices
(Congalton & Green, 1998) for the most actual classification
result. Further, it is planed to elongerate the time series by
means of historical aerial photography (1948, 1952, 1965, 1967)
as well as by old topographic maps (ca. 1910).
REFERENCES
Blackett, H.L., 1994. Forest Inventory Report No. 3. Kakame-
ga. Forest Dept./KIFCON, Nairobi, Kenya.
Brooks, T.M., S.L. Pimm & J.O. Oyugi, 1999, Time Lag be-
tween Deforestation and Bird Extinction in Tropical Forest
Fragments. Conservation Biology, 13(5), pp. 1140 - 1150.
470
Congalton, G.R. & K. Green, 1998. Assessing the Accuracy of
Remotely Sensed Data: Principles and Practices. Lewis Pub-
lishers, Boca Raton. London.
Gaston, K.J., 2000.
405, pp. 220-227.
Global patterns in biodiversity. Nature,
Geist, H.J. & E.F. Lambin, 2001. What Drives Tropical Defor-
estation? A Meta-analysis of Proximate and Underlying Causes
of Deforestation Based on Subnational Case Study Evidence.
LUCC Report Series No. 4, LUCC International Project Office,
Louvain-la-Neuve, Belgium.
Hildebrandt, G., 1996. Fernerkundung und Luftbildmessung fiir
Forstwirtschaft, Vegetationskartierung und Landschafisokolo-
gie. Wichmann Verlag, Heidelberg.
ICRAF, 1996. Tree Cover Changes in Kenya's West Rift. In:
ICRAF-Report Visions of Landscapes and Vegetation Changes,
June 1996, pp. 106-115.
Jätzold, R. & H. Schmidt, 1982. Farm Management Handbook
of Kenya - Natural Conditions and Farm Management Informa-
tion. Vol. IVA: West Kenya, Nyanza and Western Provinces,
Ministry of Agriculture, Nairobi, Kenya and Trier, Germany.
KIFCON, 1994. Kakamega Forest. The Official Guide. KIF-
CON (Kenya Indigenous Forest Conservation Programme),
Nairobi, Kenya.
Kôhler, J., 2004. Was hat Biodiversitätsforschung mit 'nachhal-
tiger Nutzung' zu tun? Tier und Museum, 8(3), pp. 82-91.
Kokwaro, J.O., 1988. Conservation Status of the Kakamega
Forest in Kenya. The Easternmost Relic of the Equatorial Rain
Forests of Africa. Monographs in Systematic Botany (Missouri
Botanical Garden), 25, pp. 471-489.
Lillesand, T. M. & R.W. Kiefer, 2000. Remote Sensing and
Image Interpretation. John Willy & Sons, New York, Chi-
chester.
Lung, T., 2004. Landbedeckungsánderungen im Gebiet ,,Ka-
kamega Forest und assoziierte Waldgebiete“ (Westkenia) -
Multispektrale Klassifizierung von LANDSAT-Satellitenbild-
daten und Auswertung mittels Methoden im Raster-GIS. Di-
ploma thesis, Karlsruhe University of Applied Sciences, De-
partment of Geoinformation, Karlsruhe. Germany.
Mitchell, N., in print. The Exploitation and Disturbance History
of Kakamega Forest, Western Kenya. In: Bielefelder Okologi-
sche Beiträge, 20, BIOTA Report No. 1, edited by B. Bleher &
H. Dalitz.
Schaab, G., B. Hórsch & G. Strunz, 2002. GIS und Fernerkun-
dung für die Biodiversitátsforschung im Rahmen des BIOTA-
Projektes. In: CD-ROM with proceedings of the 19^ DFD-
Nutzerseminar, 15-16 October 2002, Oberpfaffenhofen.
Wade, T.G., K.H. Riitters, J.D. Wickham & K.B. Jones, 2003.
Distribution and Causes of Global Forest Fragmentation. Con-
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art7 (accessed 10 Apr. 2004)
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