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A grid-based infrastructure for ecological forecasting of rice land Anopheles arabiensis aquatic larval habitats.

Jacob BG, Muturi EJ, Funes JE, Shililu JI, Githure JI, Kakoma II, Novak RJ - Malar. J. (2006)

Bottom Line: All habitats in each study site were stratified based on levels of rice stage The 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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Illinois Natural History Survey, Center for Ecological Entomology, 1816 South Oak St, Champaign, IL 61820 Champaign, IL 61820, USA. bjacob@uiuc.edu

ABSTRACT

Background: For remote identification of mosquito habitats the first step is often to construct a discrete tessellation of the region. In applications where complex geometries do not need to be represented such as urban habitats, regular orthogonal grids are constructed in GIS and overlaid on satellite images. However, rice land vector mosquito aquatic habitats are rarely uniform in space or character. An orthogonal grid overlaid on satellite data of rice-land areas may fail to capture physical or man-made structures, i.e paddies, canals, berms at these habitats. Unlike an orthogonal grid, digitizing each habitat converts a polygon into a grid cell, which may conform to rice-land habitat boundaries. This research illustrates the application of a random sampling methodology, comparing an orthogonal and a digitized grid for assessment of rice land habitats.

Methods: 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 stage

Results: The 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.

Conclusion: 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.

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A digitized GIS grid overlaid on QuickBird 0.61 m image within 1 km buffer in Kangichiri agro-village, Mwea Rice Scheme, Kenya.
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Figure 2: A digitized GIS grid overlaid on QuickBird 0.61 m image within 1 km buffer in Kangichiri agro-village, Mwea Rice Scheme, Kenya.

Mentions: The digitized grid captured each rice land An. arabiensis aquatic habitat in the study sites (Figure 2) while the orthogonal grid was unable to identify any aquatic habitats in any of the three study sites (Figure 3).


A grid-based infrastructure for ecological forecasting of rice land Anopheles arabiensis aquatic larval habitats.

Jacob BG, Muturi EJ, Funes JE, Shililu JI, Githure JI, Kakoma II, Novak RJ - Malar. J. (2006)

A digitized GIS grid overlaid on QuickBird 0.61 m image within 1 km buffer in Kangichiri agro-village, Mwea Rice Scheme, Kenya.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC1636646&req=5

Figure 2: A digitized GIS grid overlaid on QuickBird 0.61 m image within 1 km buffer in Kangichiri agro-village, Mwea Rice Scheme, Kenya.
Mentions: The digitized grid captured each rice land An. arabiensis aquatic habitat in the study sites (Figure 2) while the orthogonal grid was unable to identify any aquatic habitats in any of the three study sites (Figure 3).

Bottom Line: All habitats in each study site were stratified based on levels of rice stage The 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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Illinois Natural History Survey, Center for Ecological Entomology, 1816 South Oak St, Champaign, IL 61820 Champaign, IL 61820, USA. bjacob@uiuc.edu

ABSTRACT

Background: For remote identification of mosquito habitats the first step is often to construct a discrete tessellation of the region. In applications where complex geometries do not need to be represented such as urban habitats, regular orthogonal grids are constructed in GIS and overlaid on satellite images. However, rice land vector mosquito aquatic habitats are rarely uniform in space or character. An orthogonal grid overlaid on satellite data of rice-land areas may fail to capture physical or man-made structures, i.e paddies, canals, berms at these habitats. Unlike an orthogonal grid, digitizing each habitat converts a polygon into a grid cell, which may conform to rice-land habitat boundaries. This research illustrates the application of a random sampling methodology, comparing an orthogonal and a digitized grid for assessment of rice land habitats.

Methods: 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 stage

Results: The 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.

Conclusion: 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.

Show MeSH