Cargando…

Landscape determinants and remote sensing of anopheline mosquito larval habitats in the western Kenya highlands

BACKGROUND: In the past two decades the east African highlands have experienced several major malaria epidemics. Currently there is a renewed interest in exploring the possibility of anopheline larval control through environmental management or larvicide as an additional means of reducing malaria tr...

Descripción completa

Detalles Bibliográficos
Autores principales: Mushinzimana, Emmanuel, Munga, Stephen, Minakawa, Noboru, Li, Li, Feng, Chen-chieh, Bian, Ling, Kitron, Uriel, Schmidt, Cindy, Beck, Louisa, Zhou, Guofa, Githeko, Andrew K, Yan, Guiyun
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1420309/
https://www.ncbi.nlm.nih.gov/pubmed/16480523
http://dx.doi.org/10.1186/1475-2875-5-13
_version_ 1782127143900151808
author Mushinzimana, Emmanuel
Munga, Stephen
Minakawa, Noboru
Li, Li
Feng, Chen-chieh
Bian, Ling
Kitron, Uriel
Schmidt, Cindy
Beck, Louisa
Zhou, Guofa
Githeko, Andrew K
Yan, Guiyun
author_facet Mushinzimana, Emmanuel
Munga, Stephen
Minakawa, Noboru
Li, Li
Feng, Chen-chieh
Bian, Ling
Kitron, Uriel
Schmidt, Cindy
Beck, Louisa
Zhou, Guofa
Githeko, Andrew K
Yan, Guiyun
author_sort Mushinzimana, Emmanuel
collection PubMed
description BACKGROUND: In the past two decades the east African highlands have experienced several major malaria epidemics. Currently there is a renewed interest in exploring the possibility of anopheline larval control through environmental management or larvicide as an additional means of reducing malaria transmission in Africa. This study examined the landscape determinants of anopheline mosquito larval habitats and usefulness of remote sensing in identifying these habitats in western Kenya highlands. METHODS: Panchromatic aerial photos, Ikonos and Landsat Thematic Mapper 7 satellite images were acquired for a study area in Kakamega, western Kenya. Supervised classification of land-use and land-cover and visual identification of aquatic habitats were conducted. Ground survey of all aquatic habitats was conducted in the dry and rainy seasons in 2003. All habitats positive for anopheline larvae were identified. The retrieved data from the remote sensors were compared to the ground results on aquatic habitats and land-use. The probability of finding aquatic habitats and habitats with Anopheles larvae were modelled based on the digital elevation model and land-use types. RESULTS: The misclassification rate of land-cover types was 10.8% based on Ikonos imagery, 22.6% for panchromatic aerial photos and 39.2% for Landsat TM 7 imagery. The Ikonos image identified 40.6% of aquatic habitats, aerial photos identified 10.6%, and Landsate TM 7 image identified 0%. Computer models based on topographic features and land-cover information obtained from the Ikonos image yielded a misclassification rate of 20.3–22.7% for aquatic habitats, and 18.1–25.1% for anopheline-positive larval habitats. CONCLUSION: One-metre spatial resolution Ikonos images combined with computer modelling based on topographic land-cover features are useful tools for identification of anopheline larval habitats, and they can be used to assist to malaria vector control in western Kenya highlands.
format Text
id pubmed-1420309
institution National Center for Biotechnology Information
language English
publishDate 2006
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-14203092006-03-30 Landscape determinants and remote sensing of anopheline mosquito larval habitats in the western Kenya highlands Mushinzimana, Emmanuel Munga, Stephen Minakawa, Noboru Li, Li Feng, Chen-chieh Bian, Ling Kitron, Uriel Schmidt, Cindy Beck, Louisa Zhou, Guofa Githeko, Andrew K Yan, Guiyun Malar J Research BACKGROUND: In the past two decades the east African highlands have experienced several major malaria epidemics. Currently there is a renewed interest in exploring the possibility of anopheline larval control through environmental management or larvicide as an additional means of reducing malaria transmission in Africa. This study examined the landscape determinants of anopheline mosquito larval habitats and usefulness of remote sensing in identifying these habitats in western Kenya highlands. METHODS: Panchromatic aerial photos, Ikonos and Landsat Thematic Mapper 7 satellite images were acquired for a study area in Kakamega, western Kenya. Supervised classification of land-use and land-cover and visual identification of aquatic habitats were conducted. Ground survey of all aquatic habitats was conducted in the dry and rainy seasons in 2003. All habitats positive for anopheline larvae were identified. The retrieved data from the remote sensors were compared to the ground results on aquatic habitats and land-use. The probability of finding aquatic habitats and habitats with Anopheles larvae were modelled based on the digital elevation model and land-use types. RESULTS: The misclassification rate of land-cover types was 10.8% based on Ikonos imagery, 22.6% for panchromatic aerial photos and 39.2% for Landsat TM 7 imagery. The Ikonos image identified 40.6% of aquatic habitats, aerial photos identified 10.6%, and Landsate TM 7 image identified 0%. Computer models based on topographic features and land-cover information obtained from the Ikonos image yielded a misclassification rate of 20.3–22.7% for aquatic habitats, and 18.1–25.1% for anopheline-positive larval habitats. CONCLUSION: One-metre spatial resolution Ikonos images combined with computer modelling based on topographic land-cover features are useful tools for identification of anopheline larval habitats, and they can be used to assist to malaria vector control in western Kenya highlands. BioMed Central 2006-02-16 /pmc/articles/PMC1420309/ /pubmed/16480523 http://dx.doi.org/10.1186/1475-2875-5-13 Text en Copyright © 2006 Mushinzimana et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Mushinzimana, Emmanuel
Munga, Stephen
Minakawa, Noboru
Li, Li
Feng, Chen-chieh
Bian, Ling
Kitron, Uriel
Schmidt, Cindy
Beck, Louisa
Zhou, Guofa
Githeko, Andrew K
Yan, Guiyun
Landscape determinants and remote sensing of anopheline mosquito larval habitats in the western Kenya highlands
title Landscape determinants and remote sensing of anopheline mosquito larval habitats in the western Kenya highlands
title_full Landscape determinants and remote sensing of anopheline mosquito larval habitats in the western Kenya highlands
title_fullStr Landscape determinants and remote sensing of anopheline mosquito larval habitats in the western Kenya highlands
title_full_unstemmed Landscape determinants and remote sensing of anopheline mosquito larval habitats in the western Kenya highlands
title_short Landscape determinants and remote sensing of anopheline mosquito larval habitats in the western Kenya highlands
title_sort landscape determinants and remote sensing of anopheline mosquito larval habitats in the western kenya highlands
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1420309/
https://www.ncbi.nlm.nih.gov/pubmed/16480523
http://dx.doi.org/10.1186/1475-2875-5-13
work_keys_str_mv AT mushinzimanaemmanuel landscapedeterminantsandremotesensingofanophelinemosquitolarvalhabitatsinthewesternkenyahighlands
AT mungastephen landscapedeterminantsandremotesensingofanophelinemosquitolarvalhabitatsinthewesternkenyahighlands
AT minakawanoboru landscapedeterminantsandremotesensingofanophelinemosquitolarvalhabitatsinthewesternkenyahighlands
AT lili landscapedeterminantsandremotesensingofanophelinemosquitolarvalhabitatsinthewesternkenyahighlands
AT fengchenchieh landscapedeterminantsandremotesensingofanophelinemosquitolarvalhabitatsinthewesternkenyahighlands
AT bianling landscapedeterminantsandremotesensingofanophelinemosquitolarvalhabitatsinthewesternkenyahighlands
AT kitronuriel landscapedeterminantsandremotesensingofanophelinemosquitolarvalhabitatsinthewesternkenyahighlands
AT schmidtcindy landscapedeterminantsandremotesensingofanophelinemosquitolarvalhabitatsinthewesternkenyahighlands
AT becklouisa landscapedeterminantsandremotesensingofanophelinemosquitolarvalhabitatsinthewesternkenyahighlands
AT zhouguofa landscapedeterminantsandremotesensingofanophelinemosquitolarvalhabitatsinthewesternkenyahighlands
AT githekoandrewk landscapedeterminantsandremotesensingofanophelinemosquitolarvalhabitatsinthewesternkenyahighlands
AT yanguiyun landscapedeterminantsandremotesensingofanophelinemosquitolarvalhabitatsinthewesternkenyahighlands