16.4% of the homes visited were not occupied at the time of the visit due to work away from the home or market days. Only 3.6% of the occupants of mapped homes visited declined to be interviewed. Over 96% of the homes mapped using Google Earth imagery were correctly identified as occupied dwellings. Results: A total of 537 homes initially were mapped and a randomized subset of 96 was identified as potential survey locations. The development and use of a remote sensing method was essential to the selection and location of random households. Homes were identified and mapped in Google Earth, exported to ArcMap 10.0, and a random list of homes was generated using Microsoft Excel which was then loaded onto handheld GPS units for field location. Methods: The random selection of households and the location of these households during field surveys were accomplished using GIS, Google Earth, Microsoft Excel, and handheld Garmin GPSmap 76CSx GPS units. The technique does not require access to governmental records or ground based surveys to collect household location data and can be performed in a rapid, cost-effective manner. The method was used to select homes for ethnographic and water quality research in a region of rural Haiti located within 9 km of a local hospital and source of health education in Deschapelles, Haiti. AbstractBackground: A remote sensing technique was developed which combines a Geographic Information System (GIS) Google Earth, and Microsoft Excel to identify home locations for a random sample of households in rural Haiti. This article is from International Journal of Health Geographics, volume 12.
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