Occurrence and Distribution of <I>Anopheles</I> (Diptera: Culicidae) Larval Habitats on Land Cover Change Sites in Urban Kisumu and Urban Malindi, Kenya

Abstract

A multitemporal, land use land cover (LULC) classification dataset incorporating distributions of mosquito larval habitats was produced in ERDAS Imagine using the combined images from the Multispectral Thermal Imager (MTI) at 5 m spatial resolution from 2001 with Thematic Mapper-classification data at 28.5 m spatial resolution from 1987 and 1989 for Kisumu and Malindi, Kenya. Total LULC change for Kisumu over 14 yr was 30.2%. Total LULC change for Malindi over 12 yr was 30.6%. Of those areas in which change was detected, the LULC change for Kisumu was 72.5% for nonurban to urban, 21.7% urban to nonurban, 0.4% urban to water, 4.5% water to urban, and 0.9% water to nonurban. The proportion of LULC change for Malindi was 93.5% for nonurban to urban, 5.9% urban to nonurban, 0.2% urban to water, 0.3% nonurban to water, and 0.1% water to urban. A grid (270 m x 270 m cells) was overlaid over the maps stratifying grid cells based on drainage and planning. Of 84 aquatic habitats in Kisumu, 32.1% were located in LULC change sites and 67.9% were located in LULC nonchange sites. Of 170 aquatic habitats in Malindi, 26.5% were located in LULC change sites and 73.5% were located in LULC nonchange sites. The most abundant LULC change per strata with anopheline habitats was unplanned and poorly drained. Ditches and puddles in Kisumu and car tracks in Malindi displayed the highest number of anopheline larval habitats for all LULC change sites. The proportion of site positive aquatic habitats for anopheline larvae was higher in LULC change sites than for LULC nonchange sites for Kisumu. This evidence suggests LULC change can influence anopheline larval habitat distribution.

Geospatial variability in the egg raft distribution and abundance of Culex pipiens and Culex restuans in Urbana‐Champaign, Illinois

“…GIS overlay operations involve adding and ratioing map values, which requires application of the operation to each pixel; in turn, however, the problem of error propagation such as location errors through the use of these operations may be relevant to GIS. The presence of location error interacting with the spatial structure in the source maps, the presence of spatial correlation in the errors of the attribute measurement process, or indeed their simultaneous presence is capable of generating spatially complex maps of propagated error (Arbia et al 1998, Jacob et al 2003. For the Urbana-Champaign study site, the geographic registration may have resulted in misclassification.…”

“…Previous research on urban anopheline vectors of malaria that incorporated highresolution optical data from multitemporal datasets found that land use land cover (LULC) change sites provide a basis for the spatial prediction of vector larval habitat abundance and distribution, as well as human risk (Eisle et al 2003, Jacob et al 2003, Keating et al 2004. The initial objective of our study was to determine whether spatial variation in abundance of Culex pipiens (Linnaeus) and Culex restuans (Theobald), as measured by oviposition traps in an urban area of EastCentral Illinois, was related to several remotely measured LULC landscape parameters.…”

Quantifying stochastic error propagation in Bayesian parametric estimates using non-linear parameters of Anopheles gambiae s.l. habitats

“…gambiae s.l. aquatic habitat larval count, in the study sites, to follow a Poisson distribution, as was the case in previous research in Kenyan urban areas (Jacob et al 2003, 2005, 2008b, Keating et al 2004). Therefore, we used the mean Spatial covariates of urban Anopheles 6589 count and standard deviations on the log number of mosquito larval counts collected in the study sites to determine sample size requirements.…”

“…gambiae s.l. aquatic habitats and their larval productivity (Khambea et al 1994, Chinery 1995, Jacob et al 2003, 2008c, Diuk-Wasser et al 2007). If spatial autocorrelation patterns remain present in an An.…”

The use of remotely sensed environmental data in the study of malaria

“…In urban settings, land cover changes have also been associated with breeding sites. In two Kenyan cities, multi-spectral thermal imager (MTI; http://www.globalsecurity.org/space/systems/mti.htm) images recorded at 14-years interval showed that presence, abundance and spatial distribution of larval habitats were related to urbanization (Jacob et al, 2003). An.…”