GIS without GPS: new opportunities in technology and survey research to link people and place

• Published in: Population and environment Vol. 37; no. 4; pp. 391 - 410
• Main Authors: Vale, Petterson Molina, Stabile, Marcelo C. C.
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Science+Business Media 01.06.2016; Springer Netherlands; Springer Nature B.V
• Subjects: Agricultural population; Boundaries; Cattle; Community research; Cost analysis; Data acquisition; Data collection; Data processing; Deforestation; Demography; Environment; Farmers; Farms; Geographic information systems; Global positioning systems; Government agencies; GPS; Households; Information retrieval; Legislation; Legitimacy; Mapping; PERSPECTIVES; Population distributions; Population Economics; Property boundaries; Public Health; Random sampling; Research design; Rural areas; Rural communities; Sampling; Sampling distributions; Satellite imagery; Satellite navigation systems; Satellites; Social Sciences; Sociology; Spatial analysis; Spatial data; Spatial discrimination; Subsistence farming; Surveying; Sustainable agriculture; Technology; Brazil; GIS; Satellite imagery; Survey; Probabilistic sampling; Brazil; Research design; GPS; Amazon
• ISSN: 0199-0039; 1573-7810
• DOI: 10.1007/s11111-015-0249-0

This paper presents innovative ways to relate survey data to GIS maps, thereby making the connection of people and place more accessible for the research community. Based on data from rural areas in the Brazilian Amazon, we describe a successful effort to sample households while linking farm-level data to property boundaries, these boundaries generated from subjects' interpretations of satellite images on a computer screen. The sampling framework is based on legislation requiring farmers to report to a government agency in a four-week period, and the farmers' input allows for a more efficient means of identifying property boundaries as compared to GPS. We show that the resulting sampling is statistically representative. We discuss the potential of this association of institutional design and low-cost methods of data collection to allow for more cost-effective generation of spatial data and of geospatial analysis.