%0 Journal Article
%T A grid-based infrastructure for ecological forecasting of rice land Anopheles arabiensis aquatic larval habitats
%A Benjamin G Jacob
%A Ephantus J Muturi
%A Jose E Funes
%A Josephat I Shililu
%A John I Githure
%A Ibulaimu I Kakoma
%A Robert J Novak
%J Malaria Journal
%D 2006
%I BioMed Central
%R 10.1186/1475-2875-5-91
%X A land cover map was generated in Erdas Imagine V8.7£¿ using QuickBird data acquired July 2005, for three villages within the Mwea Rice Scheme, Kenya. An orthogonal grid was overlaid on the images. In the digitized dataset, each habitat was traced in Arc Info 9.1£¿. All habitats in each study site were stratified based on levels of rice stageThe orthogonal grid did not identify any habitat while the digitized grid identified every habitat by strata and study site. An analysis of variance test indicated the relative abundance of An. arabiensis at the three study sites to be significantly higher during the post-transplanting stage of the rice cycle.Regions of higher Anopheles abundance, based on digitized grid cell information probably reflect underlying differences in abundance of mosquito habitats in a rice land environment, which is where limited control resources could be concentrated to reduce vector abundance.Rice land Anopheles arabiensis have adapted to take advantage of relatively ephemeral and irregular shaped aquatic habitats [1-5], where the remote measurement of larval abundance can be difficult due to their size and there temporal brevity. Overlaying a GIS grid on remotely sensed high resolution data can help organize and characterize mosquito larval habitats [6-11]. A grid is constructed by applying a mathematical algorithm in order to fit a continuous and bounded surface consisting of equidistant estimates of a quantity from a field sampled attribute [12]. GIS grid-based data files consist of columns and rows of uniform cells coded according to data values. Each grid cell within a matrix contains an attribute value as well as location coordinates. The spatial location of each cell is implicitly contained within the ordering of the matrix. As such aquatic habitats containing the same spatial attribute value are easily recognized.However, due to asymmetrically shaped aquatic habitats in rice lands, an orthogonal grid may straddle habitat boundaries making
%U http://www.malariajournal.com/content/5/1/91