利用卫星图像追踪印度农村20年来的社会经济发展

Anant Gulgulia, Aman Gupta, Akshay P. Sarashetti, Aaditya Sinha, Aaditeshwar Seth
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引用次数: 1

摘要

对次国家层面的社会经济发展进行纵向分析,可以揭示出哪些地区往往比其他地区发展得更快,以及原因何在。然而,这种分析很难用传统的数据来源进行,例如不经常重复的人口普查和调查,并且可能需要在未调查地点进行价值估算的假设。基于卫星数据的社会经济发展指标已经成为在精细的空间和时间尺度上跟踪发展的代理。我们利用白天和夜间的卫星数据建立了一个模型,以估计印度村庄一级的社会经济发展指数。我们评估了我们的模型的时间稳健性,并使用它来产生20年期间的三个时间点的估计。然后,我们使用这些估计来了解诸如村庄到经济活动中心的地理距离以及该地区发展的不平等等因素对村级发展的影响。我们的研究结果为这一时期的政策变化对村庄发展可能产生的影响提供了证据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tracking Socio-economic Development in Rural India Over Two Decades Using Satellite Imagery
Longitudinal analysis of socio-economic development at sub-national scales can reveal valuable insights about which areas tend to develop faster than others and why. Such analysis is however difficult to conduct with traditional data sources such as censuses and surveys which are not repeated frequently and may require assumptions for imputation of values at non-surveyed locations. Indicators of socio-economic development based on satellite data have emerged as a proxy to track development at fine spatial and temporal scales. We build a model using daytime and nightlights satellite data to estimate an index of socio-economic development at the village level in India. We evaluate our model for temporal robustness and use it to produce estimates at three-time points over a two-decade period. We then use these estimates to understand the effect on village-level development of factors such as the geographic distance of a village to hubs of economic activity and the inequality of development in the district. Our findings provide evidence of the possible impact that policy changes during this period have had on village development.
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