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Trujillano, Fedra, Jimenez Garay, Gabriel, Alatrista-Salas, Hugo, Byrne, Isabel, Nunez-del-Prado, Miguel, Chan, Kallista, Manrique, Edgar, Johnson, Emilia, Apollinaire, Nombre, Kouame Kouakou, Pierre, Oumbouke, Welbeck, Tiono, Alfred B., Guelbeogo, Moussa W., Lines, Jo, Carrasco-Escobar, Gabriel and Fornace, Kimberly (2023) 'Mapping Malaria Vector Habitats in West Africa: Drone Imagery and Deep Learning Analysis for Targeted Vector Surveillance'. Remote Sensing, Vol 15, Issue 11, e2775.
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Abstract
Disease control programs are needed to identify the breeding sites of mosquitoes, which transmit malaria and other diseases, in order to target interventions and identify environmental risk factors. The increasing availability of very-high-resolution drone data provides new opportunities to find and characterize these vector breeding sites. Within this study, drone images from two malaria-endemic regions in Burkina Faso and Côte d’Ivoire were assembled and labeled using open-source tools. We developed and applied a workflow using region-of-interest-based and deep learning methods to identify land cover types associated with vector breeding sites from very-high-resolution natural color imagery. Analysis methods were assessed using cross-validation and achieved maximum Dice coefficients of 0.68 and 0.75 for vegetated and non-vegetated water bodies, respectively. This classifier consistently identified the presence of other land cover types associated with the breeding sites, obtaining Dice coefficients of 0.88 for tillage and crops, 0.87 for buildings and 0.71 for roads. This study establishes a framework for developing deep learning approaches to identify vector breeding sites and highlights the need to evaluate how results will be used by control programs.
| Item Type: | Article |
|---|---|
| Subjects: | QX Parasitology > Insects. Other Parasites > QX 650 Insect vectors WC Communicable Diseases > Tropical and Parasitic Diseases > WC 750 Malaria |
| Faculty: Department: | Biological Sciences > Vector Biology Department IVCC |
| Digital Object Identifer (DOI): | https://doi.org/10.3390/rs15112775 |
| SWORD Depositor: | JISC Pubrouter |
| Depositing User: | JISC Pubrouter |
| Date Deposited: | 05 Jun 2023 08:16 |
| Last Modified: | 06 Jun 2023 09:09 |
| URI: | https://archive.lstmed.ac.uk/id/eprint/22593 |
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