{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T18:36:27Z","timestamp":1775586987904,"version":"3.50.1"},"reference-count":38,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2022,1,11]],"date-time":"2022-01-11T00:00:00Z","timestamp":1641859200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000865","name":"Bill &amp; Melinda Gates Foundation","doi-asserted-by":"publisher","award":["INV-010583"],"award-info":[{"award-number":["INV-010583"]}],"id":[{"id":"10.13039\/100000865","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Drones have the potential to revolutionize malaria vector control initiatives through rapid and accurate mapping of potential malarial mosquito larval habitats to help direct field Larval Source Management (LSM) efforts. However, there are no clear recommendations on how these habitats can be extracted from drone imagery in an operational context. This paper compares the results of two mapping approaches: supervised image classification using machine learning and Technology-Assisted Digitising (TAD) mapping that employs a new region growing tool suitable for non-experts. These approaches were applied concurrently to drone imagery acquired at seven sites in Zanzibar, United Republic of Tanzania. Whilst the two approaches were similar in processing time, the TAD approach significantly outperformed the supervised classification approach at all sites (t = 5.1, p &lt; 0.01). Overall accuracy scores (mean overall accuracy 62%) suggest that a supervised classification approach is unsuitable for mapping potential malarial mosquito larval habitats in Zanzibar, whereas the TAD approach offers a simple and accurate (mean overall accuracy 96%) means of mapping these complex features. We recommend that this approach be used alongside targeted ground-based surveying (i.e., in areas inappropriate for drone surveying) for generating precise and accurate spatial intelligence to support operational LSM programmes.<\/jats:p>","DOI":"10.3390\/rs14020317","type":"journal-article","created":{"date-parts":[[2022,1,11]],"date-time":"2022-01-11T20:33:04Z","timestamp":1641933184000},"page":"317","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Improved Use of Drone Imagery for Malaria Vector Control through Technology-Assisted Digitizing (TAD)"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7928-8873","authenticated-orcid":false,"given":"Andy","family":"Hardy","sequence":"first","affiliation":[{"name":"Department of Geography and Earth Sciences, Aberystwyth University, Aberystwyth SY23 3DB, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5054-1548","authenticated-orcid":false,"given":"Gregory","family":"Oakes","sequence":"additional","affiliation":[{"name":"Department of Geography and Earth Sciences, Aberystwyth University, Aberystwyth SY23 3DB, UK"}]},{"given":"Juma","family":"Hassan","sequence":"additional","affiliation":[{"name":"Zanzibar Malaria Elimination Programme, Ministry of Health, Stone Town, Zanzibar P.O. Box 408, Tanzania"}]},{"given":"Yussuf","family":"Yussuf","sequence":"additional","affiliation":[{"name":"Tanzania Flying Labs, Dar es Salaam P.O. Box 33335, Tanzania"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Ferguson, H.M., Dornhaus, A., Beeche, A., Borgemeister, C., Gottlieb, M., Mulla, M.S., Gimnig, J.E., Fish, D., and Killeen, G.F. (2010). Ecology: A prerequisite for malaria elimination and eradication. PLoS Med., 7.","DOI":"10.1371\/journal.pmed.1000303"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"338","DOI":"10.1186\/1475-2875-10-338","article-title":"Large-scale use of mosquito larval source management for malaria control in Africa: A cost analysis","volume":"10","author":"Worrall","year":"2011","journal-title":"Malar. 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