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非洲家庭电力接入情况(2000-2013 年):利用基于模型的地质统计学方法填补信息空白。

Household electricity access in Africa (2000-2013): Closing information gaps with model-based geostatistics.

机构信息

Malaria Elimination Initiative, Institute for Global Health Sciences, UCSF, San Francisco, CA, United States of America.

Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.

出版信息

PLoS One. 2019 May 1;14(5):e0214635. doi: 10.1371/journal.pone.0214635. eCollection 2019.

Abstract

Household electricity access data in Africa are scarce, particularly at the subnational level. We followed a model-based Geostatistics approach to produce maps of electricity access between 2000 and 2013 at a 5 km resolution. We collated data from 69 nationally representative household surveys conducted in Africa and incorporated nighttime lights imagery as well as land use and land cover data to produce maps of electricity access between 2000 and 2013. The information produced here can be an aid for understanding of how electricity access has changed in the region during this 14 year period. The resolution and the continental scale makes it possible to combine these data with other sources in applications in the socio-economic field, both at a local or regional level.

摘要

非洲家庭电力接入数据稀缺,特别是在国家以下各级。我们采用基于模型的地统计学方法,以 5 公里的分辨率制作了 2000 年至 2013 年期间的电力接入地图。我们整理了非洲 69 次全国代表性家庭调查的数据,并纳入了夜间灯光图像以及土地利用和土地覆盖数据,以制作 2000 年至 2013 年期间的电力接入地图。这里提供的信息可以帮助了解在这 14 年期间该地区的电力接入情况发生了怎样的变化。该分辨率和大陆尺度使得可以在地方或区域一级的社会经济领域的应用中,将这些数据与其他来源结合起来。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2f8/6493706/4e5db7ceb353/pone.0214635.g001.jpg

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