Tunisia Population Map Metadata Report

Prediction Weighting Layer Used in Population Redistribution

The data presented below represent the predicted number of people per ~100 m pixel as estimated using the random forest (RF) model as described in Stevens, et al. (In Press). The following pages contain a description of the RF model and its covariates, their sources and any metadata collected for each covariate. The prediction weighting layer is used to dasymetrically redistribute the census counts and project counts to match estimated populations based on UN estimates for the final population maps provided by AfriPop, AsiaPop and AmeriPop.

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Tunisia Census Data and Observed Population Density

These data are the population density values used to estimate the RF model used to create the prediction weighting layer you see above. Values represent population density as measured by people per hectare and calculated from population counts within each census unit. These values are used as the dependent variable during model estimation.

Tunisia Census, 2014

Folder: Census
File Name: TUN_adm2_2014.shp
Source: Statistiques Tunisie, http://www.ins.tn/en/results-en#horizontalTab3, accessed 2017
Description: These high spatial resolution census block data were attained through in-country partners for 2014.
Class: polygon
Derived Covariates:
area, buff, zones,

class       : SpatialPolygonsDataFrame 
nfeatures   : 260 
extent      : 363610, 744051, 3345568, 4155217  (xmin, xmax, ymin, ymax)
coord. ref. : NA 
nvariables  : 17

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Random Forest Model and Diagnostics

These output and figures outline the estimated RF model that is used to predict the population density weighting layer. The model is fitted to the population density values for the preceding census data using covariates aggregatedfrom the ancillary data sources summarized following the model diagnostics.


Call:
 randomForest(x = x_data, y = y_data, ntree = popfit$ntree, mtry = popfit$mtry,      nodesize = length(y_data)/1000, importance = TRUE, proximity = TRUE) 
               Type of random forest: regression
                     Number of trees: 500
No. of variables tried at each split: 10

          Mean of squared residuals: 0.26
                    % Var explained: 93

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Covariate Metadata

Remotely-sensed, Classified Landcover, v1.6.1, 2015

Folder: Landcover
File Name: ESA_Reclassified_2015_100m_2017_09_20.tif
Source: European Space Agency-Climate Change Initiative, Climate Research Data Package (CRDP), http://www.esa-landcover-cci.org/, accessed 2017
Description: Land cover data from ESA-CCI, representative of 2015; aggregated to 10 broad classes.
Class: raster
Derived Covariates:
cls011, dst011, cls040, dst040, cls130, dst130, cls140, dst140, cls150, dst150, cls160, dst160, cls190, dst190, cls200, dst200, cls210, dst210, cls230, dst230, cls240, dst240, cls250, dst250, clsBLT, dstBLT,

class       : RasterBrick 
dimensions  : 8132, 3925, 31918100, 1  (nrow, ncol, ncell, nlayers)
resolution  : 100, 100  (x, y)
extent      : 357807, 750307, 3345250, 4158450  (xmin, xmax, ymin, ymax)
coord. ref. : +proj=utm +zone=32 +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0 
data source : C:\RF_working\RFmap\data\TUN\Landcover\Derived\landcover.tif 
names       : landcover 
min values  :        10 
max values  :       210 

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Suomi NPP VIIRS-Derived 2012 Lights at Night, 15 arc-second

Folder: Lights
File Name: DEFAULT: VIIRS 2012
Source: http://ngdc.noaa.gov/eog/viirs/download_viirs_ntl.html
Description: These 'Lights at Night' data were derived from imagery collected by the Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) sensor. Data were collected in 2012 on moonless nights and though background noise associated with fires, gas-flares, volcanoes or aurora have not been removed it represents the best-available data for night-time light production.
Class: raster
Derived Covariates:
,

class       : RasterBrick 
dimensions  : 8132, 3925, 31918100, 1  (nrow, ncol, ncell, nlayers)
resolution  : 100, 100  (x, y)
extent      : 357807, 750307, 3345250, 4158450  (xmin, xmax, ymin, ymax)
coord. ref. : +proj=utm +zone=32 +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0 
data source : C:\RF_working\RFmap\data\TUN\Lights\Derived\lights.tif 
names       : lights 
min values  :  -0.03 
max values  :   6460 

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WorldClim/BioClim Mean Annual Temperature 1950-2000, 30 arc-second

Folder: Temp
File Name: DEFAULT: BIO1
Source: http://www.worldclim.org/current
Description: WorldClim/BioClim 1950-2000 mean annual precipitation (BIO12) and mean annual temperature (BIO1) estimates (Hijmans et al., 2005) were downloaded, mosaicked and subset to match the extent of our land cover data for the mapping of this region.
Class: raster
Derived Covariates:
,

class       : RasterBrick 
dimensions  : 8207, 4285, 35166995, 1  (nrow, ncol, ncell, nlayers)
resolution  : 100, 100  (x, y)
extent      : 344307, 772807, 3341750, 4162450  (xmin, xmax, ymin, ymax)
coord. ref. : +proj=utm +zone=32 +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0 
data source : C:\RF_working\RFmap\data\TUN\Temp\Derived\temp.tif 
names       : temp 
min values  :  107 
max values  :  230 

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WorldClim/BioClim Mean Annual Precipitation 1950-2000, 30 arc-second

Folder: Precip
File Name: DEFAULT: BIO12
Source: http://www.worldclim.org/current
Description: WorldClim/BioClim 1950-2000 mean annual precipitation (BIO12) and mean annual temperature (BIO1) estimates (Hijmans et al., 2005) were downloaded, mosaicked and subset to match the extent of our land cover data for the mapping of this region.
Class: raster
Derived Covariates:
,

class       : RasterBrick 
dimensions  : 8207, 4285, 35166995, 1  (nrow, ncol, ncell, nlayers)
resolution  : 100, 100  (x, y)
extent      : 344307, 772807, 3341750, 4162450  (xmin, xmax, ymin, ymax)
coord. ref. : +proj=utm +zone=32 +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0 
data source : C:\RF_working\RFmap\data\TUN\Precip\Derived\precip.tif 
names       : precip 
min values  :     26 
max values  :   1422 

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Roads (OSM), 2017

Folder: Roads
File Name: OSM_roads_qgis.shp
Source: Open Street Map, Downloaded 2017-09-21, http://extract.bbbike.org/
Description: These data were downloaded as part of a per-country package of data layers made availalble as shapefiles through the http://extract.bbbike.org website, extracted from the Open Street Map (OSM) database.
Class: linear
Derived Covariates:
cls, dst,

class       : SpatialLinesDataFrame 
nfeatures   : 156641 
extent      : 363363, 743791, 3345562, 4154710  (xmin, xmax, ymin, ymax)
coord. ref. : NA 
nvariables  : 9

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Rivers (OSM), 2017

Folder: Rivers
File Name: OSM_waterways_qgis.shp
Source: Open Street Map, Downloaded 2017-09-21, http://extract.bbbike.org/
Description: These data were downloaded as part of a per-country package of data layers made availalble as shapefiles through the http://extract.bbbike.org website, extracted from the Open Street Map (OSM) database.
Class: linear
Derived Covariates:
cls, dst,

class       : SpatialLinesDataFrame 
nfeatures   : 6214 
extent      : 394627, 739397, 3491360, 4131780  (xmin, xmax, ymin, ymax)
coord. ref. : NA 
nvariables  : 9

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Populated Places

Folder: Populated
File Name: DEFAULT: Merged pop/builtupp, pop/builtupa, pop/mispopp
Source: National Geospatial-Intelligence Agency (NGA), http://geoengine.nga.mil/geospatial/SW_TOOLS/NIMAMUSE/webinter/rast_roam.html
Description: The VMAP0 data area downloaded as separate files, grouped roughly by continent, and merged into individual shapefiles for subsetting and further processing for population mapping efforts. These data were obtained directly from the original VMAP0 data sources provided by the NGA and pre-processed using Military Analyst in ArcGIS 10.0. Point data sources are buffered to 100 m and then all polygon data sources are merged to a single shapefile prior to processing.
Class: polygon
Derived Covariates:
cls, dst,

class       : SpatialPolygonsDataFrame 
nfeatures   : 263 
extent      : 391854, 729927, 3350481, 4129943  (xmin, xmax, ymin, ymax)
coord. ref. : NA 
nvariables  : 13

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Inland Waterbodies (ESA-CCI), v4.0 2000

Folder: Waterbodies
File Name: inlandWater_ESA_WBv4.shp
Source: European Space Agency-Climate Change Initiative, Climate Research Data Package (CRDP), http://maps.elie.ucl.ac.be/CCI/viewer/download.php, accessed 2015
Description: Static map of open water bodies at 150m spatial resolution resulting from a compilation and editions of land/water classifications: the Envisat ASAR water bodies indicator, a sub-dataset from the Global Forest Change 2000 - 2012 and the Global Inland Water product (http://maps.elie.ucl.ac.be/CCI/viewer/download.php)
Class: polygon
Derived Covariates:
cls, dst,

class       : SpatialPolygonsDataFrame 
nfeatures   : 1594 
extent      : 363621, 743959, 3345551, 4155274  (xmin, xmax, ymin, ymax)
coord. ref. : NA 
nvariables  : 2

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Protected Areas

Folder: Protected
File Name: DEFAULT: WDPAfgdb_Sept2012.gdb
Source: World Database on Protected Areas, Downloaded September, 2012, UNEP, http://www.wdpa.org, http://protectedplanet.net
Description: These data are compiled by UNEP and distributed via the Protected Planet website. All protected areas were downloaded regardless of International Union for Conservation of Nature (IUCN) or any other designation, so they include sanctuaries, national parks, game reserves, World Heritage Sites, etc.
Class: polygon
Derived Covariates:
cls, dst,

class       : SpatialPolygonsDataFrame 
nfeatures   : 14 
extent      : 439476, 668834, 3806968, 4118103  (xmin, xmax, ymin, ymax)
coord. ref. : NA 
nvariables  : 26

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Urban extents (GHSL, ESA_CCI, GUF), 2014

Folder: Urban
File Name: ghsl_esa_backfiltered_guf_2014.tif
Source: Derived data, processed from GHSL, European Space Agency Climate Change Initiative (http://maps.elie.ucl.ac.be/CCI/viewer/download.php) and Global Urban Footprint (http://www.dlr.de/eoc/en/desktopdefault.aspx/tabid-9628/16557_read-40454/), accessed 2017.
Description: These derived data represent a merger of features from GHSL and ESA-CCI built class, back-filtered using GUF (Global Urban Footprint) features.
Class: raster
Derived Covariates:
cls, dst,

class       : RasterBrick 
dimensions  : 8132, 3922, 31893704, 1  (nrow, ncol, ncell, nlayers)
resolution  : 100, 100  (x, y)
extent      : 358007, 750207, 3345350, 4158550  (xmin, xmax, ymin, ymax)
coord. ref. : +proj=utm +zone=32 +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0 
data source : C:\RF_working\RFmap\data\TUN\Urban\Derived\urban_cls.tif 
names       : urban_cls 
min values  :         0 
max values  :         1 

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Elevation and Derived Slope, 3 second

Folder: Elevation
File Name: DEFAULT: Void-Filled DEM.gdb
Source: HydroSHEDS Void-Filled DEM (Lehnert, et al., 2006), http://hydrosheds.cr.usgs.gov/dataavail.php
Description: The HydroSHEDS data are the result of an effort to provide a globally consistent dataset consisting of NASA's Shuttle Radar Topography Mission (SRTM) data and have been processed, void-filled and corrected for use at large scales.
Class: raster
Derived Covariates:
, slope,

class       : RasterBrick 
dimensions  : 8201, 4278, 35083878, 1  (nrow, ncol, ncell, nlayers)
resolution  : 100, 100  (x, y)
extent      : 345007, 772807, 3342250, 4162350  (xmin, xmax, ymin, ymax)
coord. ref. : +proj=utm +zone=32 +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0 
data source : C:\RF_working\RFmap\data\TUN\Elevation\Derived\elevation.tif 
names       : elevation 
min values  :       -46 
max values  :      1708 

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Digitized Building Locations (OSM), 2017

Folder: Buildings
File Name: buildings_OSM.shp
Source: Open Street Map, Downloaded 2017-09-21, http://extract.bbbike.org/
Description: These data were downloaded as part of a per-country package of data layers made availalble as shapefiles through the http://extract.bbbike.org website, extracted from the Open Street Map (OSM) database.
Class: polygon
Derived Covariates:
cls, dst,

class       : SpatialPolygonsDataFrame 
nfeatures   : 69422 
extent      : 368972, 742697, 3346052, 4153379  (xmin, xmax, ymin, ymax)
coord. ref. : NA 
nvariables  : 3

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Educational institution locations (OSM), 2017

Folder: Education
File Name: education_OSM.shp
Source: Open Street Map, Downloaded 2017-09-21, http://extract.bbbike.org/
Description: These data were downloaded as part of a per-country package of data layers made availalble as shapefiles through the http://extract.bbbike.org website, extracted from the Open Street Map (OSM) database.
Class: point
Derived Covariates:
cls, dst,

class       : SpatialPointsDataFrame 
nfeatures   : 350 
extent      : 415744, 696046, 3496617, 4126102  (xmin, xmax, ymin, ymax)
coord. ref. : NA 
nvariables  : 4

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Global Human Settlement Layer, 2014 (distance to settlement feature edge)

Folder: GHSL
File Name: GHSL_2014_TUN.tif
Source: Derived data, processsed from GHSL data (http://data.europa.eu/89h/jrc-ghsl-ghs_built_ldsmt_globe_r2015b); accessed 2015.
Description: This raster dataset-'distance to' GHSL 'feature edge'- is derived from the GHSL, a spatial raster dataset mapping human settlements globally based on the Landsat satellite data collection. Each pixel in the derived raster presents a euclidean distance value (metres) to the nearest feature boundary/edge.
Class: raster
Derived Covariates:
,

class       : RasterBrick 
dimensions  : 8197, 4129, 33845413, 1  (nrow, ncol, ncell, nlayers)
resolution  : 100, 100  (x, y)
extent      : 347507, 760407, 3342250, 4161950  (xmin, xmax, ymin, ymax)
coord. ref. : +proj=utm +zone=32 +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0 
data source : C:\RF_working\RFmap\data\TUN\GHSL\Derived\ghsl.tif 
names       :   ghsl 
min values  :  -1502 
max values  : 127459 

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Health service locations (OSM), 2017

Folder: Health
File Name: health2_OSM_HUM.shp
Source: Open Street Map, Downloaded 2017-09-21, http://extract.bbbike.org/
Description: These data were downloaded as part of a per-country package of data layers made availalble as shapefiles through the http://extract.bbbike.org website, extracted from the Open Street Map (OSM) database.
Class: point
Derived Covariates:
cls, dst,

class       : SpatialPointsDataFrame 
nfeatures   : 741 
extent      : 362597, 706949, 3542441, 4125534  (xmin, xmax, ymin, ymax)
coord. ref. : NA 
nvariables  : 16

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Geographic place locations (OSM), 2017

Folder: Places
File Name: places_OSM.shp
Source: Open Street Map, Downloaded 2017-09-21, http://extract.bbbike.org/
Description: These data were downloaded as part of a per-country package of data layers made availalble as shapefiles through the http://extract.bbbike.org website, extracted from the Open Street Map (OSM) database.
Class: point
Derived Covariates:
cls, dst,

class       : SpatialPointsDataFrame 
nfeatures   : 889 
extent      : 369794, 738194, 3357096, 4133621  (xmin, xmax, ymin, ymax)
coord. ref. : NA 
nvariables  : 4

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Points of Interest Locations (OSM), 2017

Folder: Points
File Name: points_OSM.shp
Source: Open Street Map, Downloaded 2017-09-21, http://extract.bbbike.org/
Description: These data were downloaded as part of a per-country package of data layers made availalble as shapefiles through the http://extract.bbbike.org website, extracted from the Open Street Map (OSM) database.
Class: point
Derived Covariates:
cls, dst,

class       : SpatialPointsDataFrame 
nfeatures   : 8868 
extent      : 369325, 738472, 3419114, 4133356  (xmin, xmax, ymin, ymax)
coord. ref. : NA 
nvariables  : 4

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Railways (OSM), 2017

Folder: Rail
File Name: OSM_railway_qgis.shp
Source: Open Street Map, Downloaded 2017-09-21, http://extract.bbbike.org/
Description: These data were downloaded as part of a per-country package of data layers made availalble as shapefiles through the http://extract.bbbike.org website, extracted from the Open Street Map (OSM) database.
Class: linear
Derived Covariates:
cls, dst,

class       : SpatialLinesDataFrame 
nfeatures   : 2691 
extent      : 419840, 742144, 3668714, 4125052  (xmin, xmax, ymin, ymax)
coord. ref. : NA 
nvariables  : 9