Landsat satellite derived environmental metric for mapping mosquitoes breeding habitats in the Nkomazi municipality, Mpumalanga Province, South Africa
Adeola, A.M. (Abiodun Morakinyo); Olwoch, Jane Mukarugwiza; Botai, J.O. (Joel Ongego); Rautenbach, C.J. de W. (Cornelis Johannes de Wet); Kalumba, Ahmed M.; Tsela, Philemon Lehlohonolo; Adisa, O.M. (Omolola); Nsubuga, F.W.N. (Francis Wasswa Nkugwa)
The advancement, availability and high level of accuracy of satellite
data provide a unique opportunity to conduct environmental and
epidemiological studies using remotely sensed measurements. In
this study, information derived from remote sensing data is used to
determine breeding habitats for Anopheles arabiensis which is the
prevalent mosquito species over Nkomazi municipality. In particular,
we have utilized the normalized difference vegetation index (NDVI)
and normalized difference water index (NDWI) coupled with land
surface temperature (LST) derived from Landsat 5 TM satellite data.
NDVI, NDWI and LST are considered as key environmental factors that
influence the mosquito habitation. The breeding habitat was derived
using multi-criteria evaluation (MCE) within ArcGIS using the derived
environmental metric with appropriate weight assigned to them.
Additionally, notified malaria cases were analysed and spatial data
layers of water bodies, including rivers and dams, were buffered to
further illustrate areas at risk of malaria. The output map from the MCE
was then classified into three classes which are low, medium and high
areas. The resulting malaria risk map depicts that areas of Komatieport,
Malelane, Madadeni and Tonga of the district are subjected to high
malaria incidence. The time series analysis of environmental metrics
and malaria cases can help to provide an adequate mechanism for
monitoring, control and early warning for malaria incidence.