Use of land surface remotely sensed satellite and airborne data for environmental exposure assessment in cancer research

Abstract

In recent years, geographic information systems (GIS) have increasingly been used for reconstructing individual-level exposures to environmental contaminants in epidemiological research. Remotely sensed data can be useful in creating space-time models of environmental measures. The primary advantage of using remotely sensed data is that it allows for study at the local scale (e.g., residential level) without requiring expensive, time-consuming monitoring campaigns. The purpose of our study was to identify how land surface remotely sensed data are currently being used to study the relationship between cancer and environmental contaminants, focusing primarily on agricultural chemical exposure assessment applications. We present the results of a comprehensive literature review of epidemiological research where remotely sensed imagery or land cover maps derived from remotely sensed imagery were applied. We also discuss the strengths and limitations of the most commonly used imagery data (aerial photographs and Landsat satellite imagery) and land cover maps.

Fusion of Sentinel-1A and Sentinel-2A data for land cover mapping: a case study in the lower Magdalena region, Colombia

“…Information on the characteristics and use of land surface elements has proved crucial for environmental studies involving biogeochemical cycles, conservation and the management of natural resources, urban planning, food and health among others (Fritz et al, 2015;Grimm et al, 2008;Maxwell, Meliker, & Goovaerts, 2009;Olson et al, 2001;Sterling, Ducharne, & Polcher, 2013). Remote sensing is the most significant technology for effective land cover mapping at large scales, bringing numerous advantages such as cost-effectiveness and repeatability of observations (Chilar, 2000;Kuemmerle et al, 2013).…”

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

“…Pesticide exposure estimation during a year lacking a temporally concurrent LUS will be affected as the utilized LUS may not adequately capture agricultural lands during that particular time period. Methods of incorporating remote sensing such as Landsat, which provide multispectral and multitemporal imagery capable of distinguishing landscape features (Maxwell, Meliker, & Goovaerts, 2010; USGS, 2014), allow for a useful approach to improving pesticide exposure estimation. The primary strengths of this research include the implementation of the Landsat method, an improved MLC and per-field classification approach to classify Landsat imagery into crops (compared to minimum distance methods), and the demonstration of a linkage between PUR data and Landsat-classified crops to estimate agricultural pesticide exposure in California in a year without a concurrent LUS.…”

Generating land cover boundaries from remotely sensed data using object-based image analysis: Overview and epidemiological application

“…Remotely sensed data can provide important information to support epidemiological studies (Herbreteau et al, 2007; Maxwell et al, 2010). Studies, such as the agricultural chemical exposure assessment application described in this paper, require that the satellite image data first be converted to digital land cover maps before integrating with other geospatial data in an exposure model.…”