{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T14:51:59Z","timestamp":1776091919663,"version":"3.50.1"},"reference-count":37,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2013,7,19]],"date-time":"2013-07-19T00:00:00Z","timestamp":1374192000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Mosquito-borne diseases affect millions of people worldwide. In the United States, since 1999, West Nile Virus (WNV) has infected 36,801 people and has caused the deaths of 1,580. In California, since 2002, nearly 3,600 people have been infected with WNV with an additional 124 fatalities. Analyses of remotely- and spatially-based data have proven to facilitate the study of mosquito-borne diseases, including WNV. This study proposes an efficient procedure to identify swimming pools that may serve as potential mosquito habitat. The procedure derives the Normalized Difference Water Index (NDWI) from high resolution, multi-spectral imagery to detect the presence of surface water, and then incorporates vector-based data layers within a GIS to identify residential land parcels with detectable water. This study compared the parcels identified as having water (535) with parcels known to have swimming pools (682) resulting in an accuracy of 78.4%. Nineteen of the 147 land parcels with swimming pools had backyards with enough vegetation to obscure the presence of a swimming pool from the satellite. The remaining 128 parcels lacked enough surface water for the NDWI to indicate them as actually having surface water. It is likely then that swimming pools, associated with such parcels, may have enough water in them to provide adequate habitat for mosquitoes, and so field inspection by mosquito abatement personnel would be justified.<\/jats:p>","DOI":"10.3390\/rs5073544","type":"journal-article","created":{"date-parts":[[2013,7,19]],"date-time":"2013-07-19T12:12:52Z","timestamp":1374235972000},"page":"3544-3561","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":303,"title":["Using the Normalized Difference Water Index (NDWI) within a Geographic Information System to Detect Swimming Pools for Mosquito Abatement: A Practical Approach"],"prefix":"10.3390","volume":"5","author":[{"given":"Stuart","family":"McFeeters","sequence":"first","affiliation":[{"name":"Department of Geography, California State University Fresno, Fresno 2555 E. San Ramon Ave,  MS SB69, Fresno, CA 93740, USA"}]}],"member":"1968","published-online":{"date-parts":[[2013,7,19]]},"reference":[{"key":"ref_1","unstructured":"World Health Organization (WHO) World Malaria Report 2012. Available online: http:\/\/www.who.int\/malaria\/publications\/world_malaria_report_2012\/report\/en\/index.html."},{"key":"ref_2","unstructured":"World Health Organization Neglected Tropical Diseases, Dengue: The Fastest Growing Mosquito-Borne Disease in the World; 29 October 2010. Available online: http:\/\/www.who.int\/neglected_diseases\/integrated_media\/integrated_media_2010_Dengue_vs_malaria\/en\/."},{"key":"ref_3","unstructured":"Centers for Disease Control and Prevention (CDC) Morbidity and Mortality Weekly Report; 3 May 2013. 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