See the complete article: Publicly available global environmental layers
- Edited by: T. Hengl
Administrative data can be used to calculate proximity-based parameters and to orient the users geographically. One publicly accessible global administrative data database is the GADM database of Global Administrative Areas GADM. It comprises borders of countries and lower level subdivisions such as provinces and counties (more than 100,000 areas). Lower level administrative boundaries can be obtained via the FAO's GeoNetwork server. Another important global dataset is the World Vector Shoreline data set at scale 1:250,000 (Soluri and Woodson, 1990). This can be, for example, used to derive the global distance from the sea coast line map (see below).
Various small scale topographic (vector and raster) maps at scales 1:5M to 1:110M can be obtained from Natural Earth Data website compiled by Nathaniel Vaughn (KELSO) and volunteers. These raster and vector maps are ideal as background or base maps for visualization of global vector layers at small scales (e.g. at A4 or A3 page formats). Natural Earth Data's layer "Admin - 0 Countries" has been used consistently do visualize WorldGrids.org products and for validation of the spatial accuracy.
Paul Wessel, from the University of Hawai'i, maintains a similar vector database called "A Global Self-consistent, Hierarchical, High-resolution Shoreline Database", which is described in detail in Wessel and Smith (1997). These vectors can be imported to R by using the maptools package (see
Note that some basic (and slightly out-dated) vector maps are available in the R's package maps. This contains data map of political borders, world cities, CIA's World Data Bank II data, administrative units from the NUTS III (Tertiary Administrative Units of the European Community) and similar. To obtain these vector maps for your GIS, you can run:
> library(maps) > worldmap <- map2SpatialLines(map("world", fill=TRUE, col="transparent", plot=FALSE), + proj4string=CRS("+proj=longlat +datum=WGS84")) > worldmap <- SpatialLinesDataFrame(worldmap, data.frame(name=(map("world"))$names), match.ID=F) > writeOGR(worldmap, "worldmap.shp", "worldmap", "ESRI Shapefile")
The original shape files of World political borders can be obtained from thematicmapping.org. Wikipedia has a repository of blank maps of the World (in SVG and PNG formats), that you can use either as background maps for plotting, or as mask maps. Eight general purpose thematic layers: boundaries, transportation, drainage, population centres, elevation, vegetation, land use and land cover (al at scale 1:1,000,000) can be obtained via the Global Map Data project.
A common projection system used to plot the world data with a balanced representation of areas and distances is the Robinson projection. Here you can download the land mask map of the world at 5 km resolution: landm5km.tif.gz.
Population density maps
The most important global socio-economic data layers are the population density maps and attached socio-economic variables. The Socioeconomic Data and Applications Center (SEDAC) distributes the global population density maps at resolution of 1 km for periods from 1990 up to 2015 (projected density). The two maps (principal components) shown down-below were derived from a set of 6 maps (1990-2015 period; the maps for 2010 and 2015 are projected population densities). The second component shows high values in China and India, some parts of Europe and USA, but then low values over large areas of African continent and Middle East. This map can be literary interpreted as the anticipated population change (positive or negative) and could be of interest to various environmental impact studies.
Another 0.5-degree gridded dataset with population density (and estimated GDP) is the SRES gridded global population dataset (Bengtsson et al., 2006). It is based on the SRES scenarios developed for the IPCC climate modeling framework, and covers the period 1990-2100.
- Bengtsson, M., Shen, Y., Oki, T., 2006. A SRES-based Gridded Global Population Dataset for 1990–2100. Population and Environment, 28(2): 113-131.
- Soluri, E.A., and Woodson, V.A., 1990. World Vector Shoreline. International Hydrographic Review, LXVII(1).
- Wessel, P., and W. H. F. Smith, 1996. A Global Self-consistent, Hierarchical, High-resolution Shoreline Database. Journal of Geophysical Research, 101, 8741-8743.