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This zip file includes the knitr file (combined LaTeX + R code) that downloads the Pew Research Center datasets employed and generates the article, including all results and figures. Other data and bibliography dependencies are also included. These reproducibility materials along with their intermediate products and the complete revision history of the article are available at https://github.com/fsolt/class_consciousness
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The purpose of this work is to collect, organize and develop geodatabase of spatial and non spatial data which are relevant to monitor land degradation and assess the major drivers to land degradation in Ethiopia. Accordingly, important time series biophysical (climate, vegetation, hydrology, soil...etc) and socioeconomic data (human population/demography, livestock population, major crops production and productivity....etc) are collected. Geodatabase is developed to facilitate integration and standardization of the collected data and making it suitable to use for further study. The next phase of this work is to find out the cause of land degradation in Ethiopia as human induced or (e.g. poor land management), climate driven (e.g. El Niño induced drought), or a combination of both factors at different spatial and temporal scales. Thus it is possible to devise suitable solutions to sites specific and time dependent problems
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  • Document
  • File Set
Data Dictionary, Codebook, Time Periods and Chronologies
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  • Text
  • File Set
V6 All Layers in GBK Encoding
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  • Text
  • File Set
V6 All Layers in UTF8 Encoding: Counties, Prefectures, Provinces, Towns.
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  • Text
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Replication data for the article Eady, Gregory (2016) "The Statistical Analysis of Misreporting on Sensitive Survey Questions"
Data Types:
  • Software/Code
  • Text
  • File Set
Updated Prefecture Polygons now have mostly complete spatial coverage for the Dynastic administrative units from 1350 - 1911 CE. Prefectures from earlier periods, 221 BCE to 1350 CE, still have gaps in spatial coverage.
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  • Image
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Contains Archive readme file (text file), country code ID key (excel file), and country code ID shapefile. Also contains production code for base grids and for additional spatial datasets.
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  • File Set
Nightlights v4 1992-2013 (DMSP-OLS Nighttime Lights Time Series Average Visible, Stable Lights, & Cloud Free Coverages. US NOAA's National Geophysical Data Center and the US Air Force Weather Agency, 2014 - http://ngdc.noaa.gov/eog/dmsp/downloadV4composites.html). Upsampled from original spatial resolution of 1 km to 100m and provided as 1201x1201 pixel tiles. Data available between latitudes 75 degrees North and 65 degrees South.
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  • File Set
OpenStreetMap (OSM) highway, inland water, railway network, railway stations, aeroway heliports, aeroway runways, January 2016 (OpenStreetMap contributors, 2016 - http://www.openstreetmap.org; http://www.opendatacommons.org; http://www.creativecommons.org). Resampled (from pbf source data of varying resolution, typically comparable with SRTM1 at @ ~30 m) to 100 m and provided as 1201x1201 pixel tiles. Attribute values of 1 usually indicate the presence of the respective feature. All 'waterway' tagged features (streams, rivers, drains, etc., and tagging variants/ misspellings) in the osm data are denoted by this single attribute value. 'Waterway' and 'Natural' tagged features of quantifiable size at grid resolution (lakes, wetlands, riverbanks, and variants) are similarly denoted. Rail network features denote ('railway' tagged) lines/tracks only (i.e. commuter, light_rail, mainline, monorail, narrow_gauge, rail, station, subway, unknown, y, yes, branch, goods, railway, single_rail, track, wide_gauge, abandoned, disused, and variants). For railway stations, the osm tag for underground stations is inconsistently used in the source data. Some underground stations use the regular (overground) 'station' tag (denoted by 1). Where underground stations are tagged using the 'subway' tag this is denoted by an attribute value of 2. Similarly, aviation ('aeroway' tag) heliports are sometimes differentiated from helipads in tagging, the latter denoted by an attribute value of 2. Highway attribute values are denoted hierarchically as below: 1 WHERE highway tag = 'proposed' OR 'construction' 2 WHERE highway tag = 'path' OR 'footway' 3 WHERE highway tag = 'track' OR 'bridleway' OR 'disused' OR 'unsurfaced' OR 'abandoned' OR 'trail' OR 'byway' OR 'unknown' OR 'unmarked_route' 4 WHERE highway tag = 'service' OR 'services' 5 WHERE highway tag = 'living_street' OR 'pedestrian' 6 WHERE highway tag = 'unclassified' OR 'road' OR 'yes' 7 WHERE highway tag = 'residential' 8 WHERE highway tag = 'tertiary_link' 9 WHERE highway tag = 'tertiary' 10 WHERE highway tag = 'secondary_link' 11 WHERE highway tag = 'secondary' 12 WHERE highway tag = 'primary_link' 13 WHERE highway tag = 'primary' 14 WHERE highway tag = 'trunk_link' 15 WHERE highway tag = 'trunk' 16 WHERE highway tag = 'motorway_link' 17 WHERE highway tag = 'motorway' 30 WHERE highway tag = 'bridge' or 'tunnel' (used only where highways span coastal water bodies).
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  • File Set
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