Applying Remote Sensing and Geographic Information System to Arab Fertility

San Diego State University Foundation, San Diego CA

Investigators

Abstract

This research adds to an understanding of the Arab fertility transition by investigating the existence of spatial patterns of fertility differentials and change over time in urban and rural settings in two Arab nations: Egypt and Jordan. The research is guided by a conceptual framework that explains the fertility transition as a combination of human capital changes in local contexts (the supply-demand framework) and the spatial diffusion of ideas and behavior regarding family size (the "horizontal" component of the cultural diffusion perspective). The major thrust of the research is oriented toward the exploration of the spatio-temporal component of fertility change in rural and urban areas in Arab countries, predicated on the more general hypothesis that reproductive behavior is a function of both who you are and where you are. The project extends the work that the researchers have already begun incorporating an explicitly spatial component to the analysis of the Arab fertility transition. This spatial component has two important aspects: (1) measuring the extent to which where you are influences reproductive behavior, net of who you are; and (2) quantifying the environmental context in which reproductive decisions are being made. These objectives will be accomplished by applying techniques of remote-sensing, geographic information system (GIS), and local indicators of spatial association and combining them with census data for study sites in Egypt and Jordan. The satellite imagery offers the ability to generate otherwise unavailable information about the ecological/environmental context of the local areas in which reproductive behavior is occurring. The incorporation of these variables into a GIS with the census data offers a way to statistically analyze the information using emerging spatial-statistical techniques. These techniques permit the quantitative assessment of spatial clustering of low and high fertility, and they also permit the calculation of spatially filtered regression models which are able to distinguish between variability in the dependent variable (fertility) that is due to the spatial component (where you are) and that which is due to the non-spatial component (who you are). Although the project is not individually pioneering the use of any of these techniques, no demographers have yet put all of these pieces together in this way. Since these techniques are still quite new in demographic research, the conduct of and products from this research project will provide models for advancing the role of spatial perspectives and methods in demographic education and research. The project will demonstrate that an understanding of regional fertility transitions requires an understanding of the way in which fertility levels and their change over time exhibit spatial clustering, and of the way in which spatial clustering is related to specific social ecological environments. The methods employed offer a model of how an increase in local prediction could increase the effectiveness of locally applied policies that may influence reproductive decisions. At the broader societal level, the substantive results will help to guide intelligent use of always-scarce resources in improving reproductive health in developing countries.