Monitoring vegetation phenological stages using remote sensing data for pasture management in selected asals of Kenya
Abstract
The objective of this study was to monitor phenological stages of grassland in selected
ASALs of Kenya, so as to provide information for sustainable pasture management. NDVI
data obtained by the VEGETATION instrument onboard SPOT satellite was extracted over
three selected ASAL districts of Kenya namely, Kajiado, Garissa and Baringo. Extraction
points were based on a land cover map that showed the location of grassland in the three
districts.
Piecewise logistic functions were applied on the extracted NDVI data in order to identify
phenological stages. Rainfall estimate data was then used to relate the identified phenological
stages to rainfall using lagged correlation. Curves of the correlated lagged rainfall and NDVI
from the determined phenological stages were plotted to compare their temporal patte-ns.
Spatial patterns oflength of the growth period were also determined.
Interannual phenological stages appeared to follow a clear growth - senescence temporal
pattern. Two growth periods were identified in all the districts studied, consistent with known
cycles of different grass and browse species in the districts. Peak growth was seen to occur
during the short rains in Kajiado district and during the long rains in Baringo district. Growth
in the two seasons was almost the same in Garissa district. Phenological stages were
significantly correlated to different lags of rainfall, with response to a longer lag observed
during the March to June growth period. Patterns of lagged rainfall were also found to be
similar to those of NDVI at the different phenological stages. The length of both growth
periods showed spatially coherent patterns that signified the distribution of different pasture
species.
Given these results, logistic functions were able to model grassland phenological stages in the
ASALs. However, further investigations are needed using a longer time series of NDVI data
and more spatial points, as well as validation using in situ data. The results can give useful
information for sustainable pasture management in the ASALs of Kenya.
Citation
Master of science in meteorologySponsorhip
University of NairobiPublisher
Department of meteorology School of physical sciences University of Nairobi