Sir Alan Muir Wood

Wood, David Muir; Mair, RJ

doi:10.1680/geot.ob.8.0008

Cited by 1 publication

(1 citation statement)

References 14 publications

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“…Pounds of AI were recalculated using the number of treated acres (Rull & Ritz, 2003). Organophosphates were identified using agricultural references (AgroPages, 2014; Alavanja et al, 2004; Dich, Zahm, Hanberg, & Adami, 1997; Greene & Pohanish, 2005; Gunier et al, 2001; Rull et al, 2009; Rull et al, 2006a; Wood, 2010). A crosswalk between PUR crop codes and CDWR LUS crop codes was created to facilitate data linkage.…”

Section: Methodsmentioning

confidence: 99%

Linking pesticides and human health: A geographic information system (GIS) and Landsat remote sensing method to estimate agricultural pesticide exposure

et al. 2015

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Accurate pesticide exposure estimation is integral to epidemiologic studies elucidating the role of pesticides in human health. Humans can be exposed to pesticides via residential proximity to agricultural pesticide applications (drift). We present an improved geographic information system (GIS) and remote sensing method, the Landsat method, to estimate agricultural pesticide exposure through matching pesticide applications to crops classified from temporally concurrent Landsat satellite remote sensing images in California. The image classification method utilizes Normalized Difference Vegetation Index (NDVI) values in a combined maximum likelihood classification and per-field (using segments) approach. Pesticide exposure is estimated according to pesticide-treated crop fields intersecting 500 m buffers around geocoded locations (e.g., residences) in a GIS. Study results demonstrate that the Landsat method can improve GIS-based pesticide exposure estimation by matching more pesticide applications to crops (especially temporary crops) classified using temporally concurrent Landsat images compared to the standard method that relies on infrequently updated land use survey (LUS) crop data. The Landsat method can be used in epidemiologic studies to reconstruct past individual-level exposure to specific pesticides according to where individuals are located.

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