Using the Normalized Difference Water Index (NDWI) within a Geographic Information System to Detect Swimming Pools for Mosquito Abatement: A Practical Approach

Abstract

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.

Automated Extraction of Inundated Areas from Multi-Temporal Dual-Polarization RADARSAT-2 Images of the 2011 Central Thailand Flood

“…To extract the flooded areas from the optical images, using the Normalize Different Water Index (NDWI) calculated from the Green (G) and near-infrared (NIR) band values is the most popular and effective method [36]. McFeeters proposed the NDWI in 1996 to detect surface waters in wetland environments and to allow for the measurement of surface water extent, and asserted that values of NDWI greater than zero are assumed to represent water surfaces, while values less than, or equal to, zero are assumed to be non-water surfaces [37].…”

The estimation of Lake Naivasha Area Changes using of Hydro-Geospatial Technologies

“…Surface water is one of the irreplaceable strategic resources for human survival and social development, and it is essential for humans, food crops, and ecosystems (Lu et al 2011). Remote sensing satellites at different spatial, spectral, and temporal resolutions provide an enormous amount of data that have become primary sources, being extensively used for detecting and extracting surface water and its changes in recent decades (McFeeters, 2013).…”

Delimitação de áreas inundáveis a partir de Modified Normalized Difference Water Index (MNDWI) no Município de Esteio (RS, Brasil)

“…O NDWI (Índice de Diferença Normalizada de Água), proposto por McFeeters (1996McFeeters ( , 2013, utiliza as bandas do verde e do infravermelho próximo, com objetivo de maximizar a reflectância de água, por meio da utilização da banda verde, minimizar a baixa reflexão dos corpos de água pelo infravermelho próximo e tirar proveito da alta reflexão da vegetação e do solo no infravermelho médio.…”