High-accuracy detection of malaria vector larval habitats using drone-based multispectral imagery.
Interest in larval source management (LSM) as an adjunct intervention to control and eliminate malaria transmission has recently increased mainly because long-lasting insecticidal nets (LLINs) and indoor residual spray (IRS) are ineffective against exophagic and exophilic mosquitoes. In Amazonian Pe...
Published in: | PLOS Neglected Tropical Diseases |
---|---|
Main Authors: | , , , , , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Public Library of Science (PLoS)
2019
|
Subjects: | |
Online Access: | https://doi.org/10.1371/journal.pntd.0007105 https://doaj.org/article/c4586256e4e9416ea2d49899e2e15444 |
id |
ftdoajarticles:oai:doaj.org/article:c4586256e4e9416ea2d49899e2e15444 |
---|---|
record_format |
openpolar |
spelling |
ftdoajarticles:oai:doaj.org/article:c4586256e4e9416ea2d49899e2e15444 2023-05-15T15:05:16+02:00 High-accuracy detection of malaria vector larval habitats using drone-based multispectral imagery. Gabriel Carrasco-Escobar Edgar Manrique Jorge Ruiz-Cabrejos Marlon Saavedra Freddy Alava Sara Bickersmith Catharine Prussing Joseph M Vinetz Jan E Conn Marta Moreno Dionicia Gamboa 2019-01-01T00:00:00Z https://doi.org/10.1371/journal.pntd.0007105 https://doaj.org/article/c4586256e4e9416ea2d49899e2e15444 EN eng Public Library of Science (PLoS) http://europepmc.org/articles/PMC6353212?pdf=render https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0007105 https://doaj.org/article/c4586256e4e9416ea2d49899e2e15444 PLoS Neglected Tropical Diseases, Vol 13, Iss 1, p e0007105 (2019) Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2019 ftdoajarticles https://doi.org/10.1371/journal.pntd.0007105 2022-12-30T23:04:04Z Interest in larval source management (LSM) as an adjunct intervention to control and eliminate malaria transmission has recently increased mainly because long-lasting insecticidal nets (LLINs) and indoor residual spray (IRS) are ineffective against exophagic and exophilic mosquitoes. In Amazonian Peru, the identification of the most productive, positive water bodies would increase the impact of targeted mosquito control on aquatic life stages. The present study explores the use of unmanned aerial vehicles (drones) for identifying Nyssorhynchus darlingi (formerly Anopheles darlingi) breeding sites with high-resolution imagery (~0.02m/pixel) and their multispectral profile in Amazonian Peru. Our results show that high-resolution multispectral imagery can discriminate a profile of water bodies where Ny. darlingi is most likely to breed (overall accuracy 86.73%- 96.98%) with a moderate differentiation of spectral bands. This work provides proof-of-concept of the use of high-resolution images to detect malaria vector breeding sites in Amazonian Peru and such innovative methodology could be crucial for LSM malaria integrated interventions. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic PLOS Neglected Tropical Diseases 13 1 e0007105 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
spellingShingle |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 Gabriel Carrasco-Escobar Edgar Manrique Jorge Ruiz-Cabrejos Marlon Saavedra Freddy Alava Sara Bickersmith Catharine Prussing Joseph M Vinetz Jan E Conn Marta Moreno Dionicia Gamboa High-accuracy detection of malaria vector larval habitats using drone-based multispectral imagery. |
topic_facet |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
description |
Interest in larval source management (LSM) as an adjunct intervention to control and eliminate malaria transmission has recently increased mainly because long-lasting insecticidal nets (LLINs) and indoor residual spray (IRS) are ineffective against exophagic and exophilic mosquitoes. In Amazonian Peru, the identification of the most productive, positive water bodies would increase the impact of targeted mosquito control on aquatic life stages. The present study explores the use of unmanned aerial vehicles (drones) for identifying Nyssorhynchus darlingi (formerly Anopheles darlingi) breeding sites with high-resolution imagery (~0.02m/pixel) and their multispectral profile in Amazonian Peru. Our results show that high-resolution multispectral imagery can discriminate a profile of water bodies where Ny. darlingi is most likely to breed (overall accuracy 86.73%- 96.98%) with a moderate differentiation of spectral bands. This work provides proof-of-concept of the use of high-resolution images to detect malaria vector breeding sites in Amazonian Peru and such innovative methodology could be crucial for LSM malaria integrated interventions. |
format |
Article in Journal/Newspaper |
author |
Gabriel Carrasco-Escobar Edgar Manrique Jorge Ruiz-Cabrejos Marlon Saavedra Freddy Alava Sara Bickersmith Catharine Prussing Joseph M Vinetz Jan E Conn Marta Moreno Dionicia Gamboa |
author_facet |
Gabriel Carrasco-Escobar Edgar Manrique Jorge Ruiz-Cabrejos Marlon Saavedra Freddy Alava Sara Bickersmith Catharine Prussing Joseph M Vinetz Jan E Conn Marta Moreno Dionicia Gamboa |
author_sort |
Gabriel Carrasco-Escobar |
title |
High-accuracy detection of malaria vector larval habitats using drone-based multispectral imagery. |
title_short |
High-accuracy detection of malaria vector larval habitats using drone-based multispectral imagery. |
title_full |
High-accuracy detection of malaria vector larval habitats using drone-based multispectral imagery. |
title_fullStr |
High-accuracy detection of malaria vector larval habitats using drone-based multispectral imagery. |
title_full_unstemmed |
High-accuracy detection of malaria vector larval habitats using drone-based multispectral imagery. |
title_sort |
high-accuracy detection of malaria vector larval habitats using drone-based multispectral imagery. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2019 |
url |
https://doi.org/10.1371/journal.pntd.0007105 https://doaj.org/article/c4586256e4e9416ea2d49899e2e15444 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
PLoS Neglected Tropical Diseases, Vol 13, Iss 1, p e0007105 (2019) |
op_relation |
http://europepmc.org/articles/PMC6353212?pdf=render https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0007105 https://doaj.org/article/c4586256e4e9416ea2d49899e2e15444 |
op_doi |
https://doi.org/10.1371/journal.pntd.0007105 |
container_title |
PLOS Neglected Tropical Diseases |
container_volume |
13 |
container_issue |
1 |
container_start_page |
e0007105 |
_version_ |
1766336997267341312 |