Geospatial techniques for environmental modeling of mosquito breeding habitats at Suez Canal Zone, Egypt

Egypt is currently witnessing a number of mega projects, along the axis of Suez Canal, which consequently have a great effect on environment and its biological components including mosquito vectors of diseases. This study is an attempt to explore the use and efficiency of integrated remote sensing-G...

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Main Authors: Ahmed El-Zeiny, Asmaa El-Hefni, Mohamed Sowilem
Format: Article
Language:English
Published: Elsevier 2017-12-01
Series:Egyptian Journal of Remote Sensing and Space Sciences
Subjects:
GIS
Online Access:http://www.sciencedirect.com/science/article/pii/S1110982316301284
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spelling doaj-88aa7a468b4e41f598cabb9f2d1a148a2020-11-24T20:58:00ZengElsevierEgyptian Journal of Remote Sensing and Space Sciences1110-98232017-12-0120228329310.1016/j.ejrs.2016.11.009Geospatial techniques for environmental modeling of mosquito breeding habitats at Suez Canal Zone, EgyptAhmed El-ZeinyAsmaa El-HefniMohamed SowilemEgypt is currently witnessing a number of mega projects, along the axis of Suez Canal, which consequently have a great effect on environment and its biological components including mosquito vectors of diseases. This study is an attempt to explore the use and efficiency of integrated remote sensing-GIS techniques and field surveys for detection of mosquito breeding habitats at Suez Canal Zone. Remote sensing and field surveys provided the necessary verified ground truth information to the present study. A corrected Landsat8 image, acquired in Jan. 2015, was utilized to produce NDVI, NDMI and LST to identify environmental variables associated with mosquitoes breeding habitats. Concurrently, a GIS model was developed to predict probable mosquito habitats and areas under environmental risk of diseases transmission. Results revealed that Culex pipiens and Ochlerotatus detritus are the most abundant species in Suez Canal Zone recording total number of 362 larvae (51.86%) and 244 larvae (34.96%), respectively. The model predicted that Ismailia is the most subjected Suez Canal Governorate to mosquito borne diseases. It recorded the maximum levels of high risk, risk and vulnerable areas to mosquito proliferation; 6.06 km2 (64.26%), 954.65 km2 (54.58%) and 152.87 km2 (80.09%), respectively. The developed prediction model achieved an accuracy of 80.95% and increased to 100% at sites where predicted larval habitats were ascertained by in-situ checks.http://www.sciencedirect.com/science/article/pii/S1110982316301284Remote sensingGISEnvironmental modelingSuez Canal areaMosquito breeding habitat
collection DOAJ
language English
format Article
sources DOAJ
author Ahmed El-Zeiny
Asmaa El-Hefni
Mohamed Sowilem
spellingShingle Ahmed El-Zeiny
Asmaa El-Hefni
Mohamed Sowilem
Geospatial techniques for environmental modeling of mosquito breeding habitats at Suez Canal Zone, Egypt
Egyptian Journal of Remote Sensing and Space Sciences
Remote sensing
GIS
Environmental modeling
Suez Canal area
Mosquito breeding habitat
author_facet Ahmed El-Zeiny
Asmaa El-Hefni
Mohamed Sowilem
author_sort Ahmed El-Zeiny
title Geospatial techniques for environmental modeling of mosquito breeding habitats at Suez Canal Zone, Egypt
title_short Geospatial techniques for environmental modeling of mosquito breeding habitats at Suez Canal Zone, Egypt
title_full Geospatial techniques for environmental modeling of mosquito breeding habitats at Suez Canal Zone, Egypt
title_fullStr Geospatial techniques for environmental modeling of mosquito breeding habitats at Suez Canal Zone, Egypt
title_full_unstemmed Geospatial techniques for environmental modeling of mosquito breeding habitats at Suez Canal Zone, Egypt
title_sort geospatial techniques for environmental modeling of mosquito breeding habitats at suez canal zone, egypt
publisher Elsevier
series Egyptian Journal of Remote Sensing and Space Sciences
issn 1110-9823
publishDate 2017-12-01
description Egypt is currently witnessing a number of mega projects, along the axis of Suez Canal, which consequently have a great effect on environment and its biological components including mosquito vectors of diseases. This study is an attempt to explore the use and efficiency of integrated remote sensing-GIS techniques and field surveys for detection of mosquito breeding habitats at Suez Canal Zone. Remote sensing and field surveys provided the necessary verified ground truth information to the present study. A corrected Landsat8 image, acquired in Jan. 2015, was utilized to produce NDVI, NDMI and LST to identify environmental variables associated with mosquitoes breeding habitats. Concurrently, a GIS model was developed to predict probable mosquito habitats and areas under environmental risk of diseases transmission. Results revealed that Culex pipiens and Ochlerotatus detritus are the most abundant species in Suez Canal Zone recording total number of 362 larvae (51.86%) and 244 larvae (34.96%), respectively. The model predicted that Ismailia is the most subjected Suez Canal Governorate to mosquito borne diseases. It recorded the maximum levels of high risk, risk and vulnerable areas to mosquito proliferation; 6.06 km2 (64.26%), 954.65 km2 (54.58%) and 152.87 km2 (80.09%), respectively. The developed prediction model achieved an accuracy of 80.95% and increased to 100% at sites where predicted larval habitats were ascertained by in-situ checks.
topic Remote sensing
GIS
Environmental modeling
Suez Canal area
Mosquito breeding habitat
url http://www.sciencedirect.com/science/article/pii/S1110982316301284
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AT asmaaelhefni geospatialtechniquesforenvironmentalmodelingofmosquitobreedinghabitatsatsuezcanalzoneegypt
AT mohamedsowilem geospatialtechniquesforenvironmentalmodelingofmosquitobreedinghabitatsatsuezcanalzoneegypt
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