Applying Remote Sensing and Geographic Information System to Arab Fertility

这项研究通过调查两个阿拉伯国家：埃及和约旦的城市和农村环境中生育率差异的空间模式及其随时间变化的存在，增加了对阿拉伯生育率过渡的理解。该研究以一个概念框架为指导，该框架将生育率转变解释为地方背景下人力资本变化（供需框架）和关于家庭规模的思想和行为的空间扩散（文化扩散视角的“水平”部分）的结合。这项研究的主要目的是探索阿拉伯国家农村和城市地区生育率变化的时空组成部分，其依据是一个更普遍的假设，即生殖行为是你是谁和你在哪里的一个功能。该项目扩展了研究人员已经开始的工作，将明确的空间成分纳入阿拉伯生育率转变的分析。这个空间成分有两个重要的方面：(1)衡量你所在的地方对生殖行为的影响程度，而不是你是谁；(2)量化做出生殖决定的环境背景。这些目标将通过应用遥感技术、地理信息系统和当地空间关联指标，并将它们与埃及和约旦研究地点的人口普查数据相结合来实现。卫星图像提供了一种能力，可以产生关于正在发生生殖行为的当地生态/环境背景的其他方面无法获得的信息。将这些变量与人口普查数据结合到GIS中，提供了一种使用新兴空间统计技术对信息进行统计分析的方法。这些技术允许对低生育率和高生育率的空间聚类进行定量评估，它们还允许计算空间过滤的回归模型，这些模型能够区分因变量（生育率）的可变性，这是由于空间成分（你在哪里）造成的，这是由于非空间成分（你是谁）造成的。虽然该项目并不是单独使用这些技术的先驱，但还没有人口统计学家以这种方式把所有这些碎片放在一起。由于这些技术在人口研究中仍然是相当新的，因此这个研究项目的实施和产品将为促进空间观点和方法在人口教育和研究中的作用提供模式。该项目将证明，要了解区域生育率变化，就必须了解生育率水平及其随时间变化呈现空间聚类的方式，以及空间聚类与特定社会生态环境的关系。所采用的方法提供了一个模型，说明增加当地预测如何能够提高可能影响生殖决定的当地适用政策的效力。在更广泛的社会一级，实质性成果将有助于指导明智地利用一向稀缺的资源，以改善发展中国家的生殖健康。

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.