Remote Sensing to Analyze Wealth, Poverty, and Crime

J. Irvine, Richard J. Wood, Payden Mcbee
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引用次数: 1

Abstract

understanding of economic, social, and cultural characteristics of a society is critical to effective government policy and successful commercial undertakings. Obtaining this information, however, often requires direct interactions with the local populace through surveys or other costly methods. We address this challenge by combining automated processing of satellite imagery with advanced modeling techniques. We have developed methods for inferring measures of wellbeing and perceptions of crime from commercial satellite imagery. Through analysis of commercial satellite imagery and coincident survey data, previous research has demonstrated models for rural afghanistan and selected countries in sub-saharan africa. The findings show the potential for predicting peoples' attitudes about the a variety of social, economic, and political issues, based only on the imagery-derived information. This paper extends the previous research, focusing on wealth, poverty, and crime. We present models to predict indicators and quantify model performance through cross-validation. The paper concludes with recommendations for future exploration.
遥感分析财富、贫困和犯罪
了解一个社会的经济、社会和文化特征对有效的政府政策和成功的商业事业至关重要。然而,获得这些信息往往需要通过调查或其他昂贵的方法与当地民众直接互动。我们通过将卫星图像的自动处理与先进的建模技术相结合来解决这一挑战。我们已经开发了从商业卫星图像中推断幸福和对犯罪的看法的方法。通过分析商业卫星图像和一致的调查数据,以前的研究已经展示了阿富汗农村和撒哈拉以南非洲某些国家的模型。研究结果表明,仅基于图像衍生的信息,就有可能预测人们对各种社会、经济和政治问题的态度。本文扩展了以前的研究,重点关注财富、贫困和犯罪。我们提出模型来预测指标,并通过交叉验证量化模型的性能。最后,对今后的探索提出了建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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