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

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 o...

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Published in:Malaria Journal
Main Authors: Kakoma Ibulaimu I, Githure John I, Shililu Josephat I, Funes Jose E, Muturi Ephantus J, Jacob Benjamin G, Novak Robert J
Format: Article in Journal/Newspaper
Language:English
Published: BMC 2006
Subjects:
Online Access:https://doi.org/10.1186/1475-2875-5-91
https://doaj.org/article/e4d97e234fa24a398f04d1e296895722
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spelling ftdoajarticles:oai:doaj.org/article:e4d97e234fa24a398f04d1e296895722 2023-05-15T15:15:46+02:00 A grid-based infrastructure for ecological forecasting of rice land Anopheles arabiensis aquatic larval habitats Kakoma Ibulaimu I Githure John I Shililu Josephat I Funes Jose E Muturi Ephantus J Jacob Benjamin G Novak Robert J 2006-10-01T00:00:00Z https://doi.org/10.1186/1475-2875-5-91 https://doaj.org/article/e4d97e234fa24a398f04d1e296895722 EN eng BMC http://www.malariajournal.com/content/5/1/91 https://doaj.org/toc/1475-2875 doi:10.1186/1475-2875-5-91 1475-2875 https://doaj.org/article/e4d97e234fa24a398f04d1e296895722 Malaria Journal, Vol 5, Iss 1, p 91 (2006) Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 article 2006 ftdoajarticles https://doi.org/10.1186/1475-2875-5-91 2022-12-31T09:33:48Z 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. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Malaria Journal 5 1
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Arctic medicine. Tropical medicine
RC955-962
Infectious and parasitic diseases
RC109-216
spellingShingle Arctic medicine. Tropical medicine
RC955-962
Infectious and parasitic diseases
RC109-216
Kakoma Ibulaimu I
Githure John I
Shililu Josephat I
Funes Jose E
Muturi Ephantus J
Jacob Benjamin G
Novak Robert J
A grid-based infrastructure for ecological forecasting of rice land Anopheles arabiensis aquatic larval habitats
topic_facet Arctic medicine. Tropical medicine
RC955-962
Infectious and parasitic diseases
RC109-216
description 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.
format Article in Journal/Newspaper
author Kakoma Ibulaimu I
Githure John I
Shililu Josephat I
Funes Jose E
Muturi Ephantus J
Jacob Benjamin G
Novak Robert J
author_facet Kakoma Ibulaimu I
Githure John I
Shililu Josephat I
Funes Jose E
Muturi Ephantus J
Jacob Benjamin G
Novak Robert J
author_sort Kakoma Ibulaimu I
title A grid-based infrastructure for ecological forecasting of rice land Anopheles arabiensis aquatic larval habitats
title_short A grid-based infrastructure for ecological forecasting of rice land Anopheles arabiensis aquatic larval habitats
title_full A grid-based infrastructure for ecological forecasting of rice land Anopheles arabiensis aquatic larval habitats
title_fullStr A grid-based infrastructure for ecological forecasting of rice land Anopheles arabiensis aquatic larval habitats
title_full_unstemmed A grid-based infrastructure for ecological forecasting of rice land Anopheles arabiensis aquatic larval habitats
title_sort grid-based infrastructure for ecological forecasting of rice land anopheles arabiensis aquatic larval habitats
publisher BMC
publishDate 2006
url https://doi.org/10.1186/1475-2875-5-91
https://doaj.org/article/e4d97e234fa24a398f04d1e296895722
geographic Arctic
geographic_facet Arctic
genre Arctic
genre_facet Arctic
op_source Malaria Journal, Vol 5, Iss 1, p 91 (2006)
op_relation http://www.malariajournal.com/content/5/1/91
https://doaj.org/toc/1475-2875
doi:10.1186/1475-2875-5-91
1475-2875
https://doaj.org/article/e4d97e234fa24a398f04d1e296895722
op_doi https://doi.org/10.1186/1475-2875-5-91
container_title Malaria Journal
container_volume 5
container_issue 1
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