Mapping the Urban Environments of Aedes aegypti Using Drone Technology Article Swipe
Kenia Mayela Valdez-Delgado
,
Octavio Garcia‐Salazar
,
David A. Moo‐Llanes
,
Cecilia Izcapa-Treviño
,
Miguel A. Cruz-Pliego
,
Gustavo Y. Domínguez-Posadas
,
Moisés O. Armendáriz-Valdez
,
Fabián Correa‐Morales
,
Luis Alberto Cisneros-Vázquez
,
José Genaro Ordóñez-González
,
Ildefonso Fernández‐Salas
,
Rogelio Danis‐Lozano
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/drones7090581
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/drones7090581
Aedes aegypti is widely distributed worldwide and is the main vector mosquito for dengue, one of the most important infectious diseases in middle- and low-income countries. The landscape composition and vegetation cover determine appropriate environments for this mosquito to breed, and it is fundamental to define the most affordable methodology to understand these landscape variables in urban environments. The proposed methodology integrated drone technologies and traditional entomological surveillance to strengthen our knowledge about areas suitable for Ae. aegypti infestation. We included an analysis using the vegetation indexes, NDVI and NDVIRe, and their association with Ae. aegypti larvae and adults in houses from the El Vergel neighborhood Tapachula, Chiapas, Mexico. We used drone technology to obtain high-resolution photos and performed multispectral orthomosaic constructions for the data of vegetation indexes with a kernel density analysis. A negative binomial regression was performed to determine the association between the numbers of Ae. aegypti larvae and adults with the kernel density based on NDVI and NDVIRe. Medium and high values of kernel density of NDVIRe (both p-value < 0.05) and NDVI (both p-value < 0.05) were associated with a higher amount of mosquito adults per houses. The density of Ae. aegypti larvae per house did not show an association with medium and high values of NDVIRe (both p-value > 0.05) and NDVI (both p-value > 0.05). The vegetation indexes, NDVI and NDVIRe, have potential as precise predictors of Ae. aegypti adult mosquito circulation in urban environments. Drone technology can be used to map and obtain landscape characteristics associated with mosquito abundance in urban environments.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/drones7090581
- https://www.mdpi.com/2504-446X/7/9/581/pdf?version=1695028130
- OA Status
- gold
- Cited By
- 10
- References
- 52
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4386830983
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4386830983Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/drones7090581Digital Object Identifier
- Title
-
Mapping the Urban Environments of Aedes aegypti Using Drone TechnologyWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-09-15Full publication date if available
- Authors
-
Kenia Mayela Valdez-Delgado, Octavio Garcia‐Salazar, David A. Moo‐Llanes, Cecilia Izcapa-Treviño, Miguel A. Cruz-Pliego, Gustavo Y. Domínguez-Posadas, Moisés O. Armendáriz-Valdez, Fabián Correa‐Morales, Luis Alberto Cisneros-Vázquez, José Genaro Ordóñez-González, Ildefonso Fernández‐Salas, Rogelio Danis‐LozanoList of authors in order
- Landing page
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https://doi.org/10.3390/drones7090581Publisher landing page
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https://www.mdpi.com/2504-446X/7/9/581/pdf?version=1695028130Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
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https://www.mdpi.com/2504-446X/7/9/581/pdf?version=1695028130Direct OA link when available
- Concepts
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Aedes aegypti, Normalized Difference Vegetation Index, Dengue fever, Geography, Drone, Vegetation (pathology), Multispectral image, Cartography, Biology, Larva, Forestry, Ecology, Remote sensing, Climate change, Medicine, Virology, Pathology, GeneticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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10Total citation count in OpenAlex
- Citations by year (recent)
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2025: 7, 2024: 3Per-year citation counts (last 5 years)
- References (count)
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52Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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