Difference between revisions of "Global datasets"

(Biodiversity / human impacts maps)
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{{Drop|G}}lobal maps on our environment (both remote sensing-based and thematic) are nowadays increasingly attractive for environmental modelling. A variety of publicly available maps can be obtained at no cost at resolutions up to 1 km or better. This article reviews some of the most known global datasets of interest for various environmental modeling projects (see also some similar galleries of world maps by [http://www.google.com/gadgets/directory?synd=earth&cat=education Google Earth], [http://www.fao.org/geonetwork/srv/en/main.home FAO's GeoNetwork], [http://geodata.grid.unep.ch/ UNEP/GRID GEO DataPortal], [http://maps.grida.no/region/global UNEP/GRID-Arendal], The [http://earthtrends.wri.org Environmental Information Portal] of the World Resources Institute, [http://www.sage.wisc.edu/atlas/maps.php Atlas of the Biosphere portal], and/or [http://www.geoportal.org/web/guest/geo_image_gallery GeoPortal]).
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{{#meta: REFRESH | 1;url=http://worldgrids.org/doku.php?id=source_data}}
  
Use this [http://spatial-analyst.net/scripts/worldmaps.R R script] to automatically download and browse the maps shown below (the script also includes some small exercises to import/export data, set the correct coordinate system, make displays and run spatial analysis using point-sampled variables). The total size of maps is about 300 MB (62 maps). Each gridded map consists of 7200 columns and 3600 rows; the cell size is 0.05 arcdegrees, which corresponds to about 5 km. All maps are projected in the Latitude-Longitude WGS84 system <tt>+proj=longlat +ellps=WGS84</tt>. Displays shown below were produced using the [[Software#SAGA GIS|SAGA GIS]].
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#REDIRECTS to [http://worldgrids.org/doku.php?id=source_data Publicly available global environmental layers]
 
 
{{Plainlist|align=right|background=lightyellow|heading=Obtain all maps at once.|
 
* [[Image:icon_R.png|18px]] [http://spatial-analyst.net/scripts/worldmaps.R worldmaps.R] : R script to automatically download and browse the global maps (includes an data analysis example: mapping species distribution for [http://spatial-analyst.net/book/Mdwlark Sturnella magna] over the USA).
 
* [[Image:icon_txt.gif|18px]] [http://spatial-analyst.net/worldmaps/README.txt README.txt] : A complete description of the directory and the metadata fields used.
 
* [[Image:Ge_icon.jpg|18px]] [http://spatial-analyst.net/worldmaps/worldmaps.kml worldmaps.kml] : Browse maps in Google Earth.
 
* [[Image:7z_icon.jpg|18px]] [http://globalsoilmap.org/data/GlobCover1km.7z GlobCover1km.7z] : ~1 km resolution (0.1 arc-degree) DEM of the world (16 MB).
 
* [[Image:7z_icon.jpg|18px]] [http://globalsoilmap.org/data/globedem1km.7z globedem1km.7z] : ~1 km (0.08333) resolution DEM of the world (626 MB!).
 
}}
 
 
 
A description of how were the maps produced and what was the original source is provided in the attached <tt>*.rdc</tt> image documentation file (adopted [http://www.gdal.org/frmt_Idrisi.html Idrisi's format] for metadata). The processing steps are described in the R scripts as indicated in the field <tt>lineage:</tt>. In most cases I used the [http://www.gdal.org/gdal_utilities.html GDAL utilities], which I highly recommend for processing large data and for data processing automation. By using a relatively coarse resolution (5 km), many original small features in the input maps have disappeared or their spatial accuracy has been downgraded. In almost all cases, the original data is available at 5 (or more) times better resolution / level of detail, so please consider using the original data for continental and regional studies instead of using these maps.
 
 
 
Some maps listed in the [http://spatial-analyst.net/worldmaps/ repository] are simply reformatted/reprojected version of the original grids. Most of maps listed are in fact original. For example, map <tt>PCEVI1.tif</tt> shows first Principal Component of the complete monthly time-series of MODIS EVI images. Principal component analysis has shown to be especially attractive techniques to analyze time-series of images and reduce their dimensionality (Eastman and Fulk, 1993). Such data you will not be able to find on the MODIS website.
 
 
 
The compendium of maps shown in this article are intended for non-commercial scientific, conservation, and educational purposes only. The author of this article is not responsible for any loss, damage, liability or expense that resulted from use of this data. The author does not make any warranties as to the accuracy or completeness of any of the maps presented (see also the [[spatial-analyst.net:General disclaimer|general disclaimer]]). To obtain the most up-to-date, most detailed version of each dataset, please follow the links to the original data producers/providers. If you wish to cite some of the derived maps shown here or this article, please cite as:
 
 
 
* Hengl, T. 2009. [http://www.lulu.com/content/paperback-book/a-practical-guide-to-geostatistical-mapping/8010854 A Practical Guide to Geostatistical Mapping], 2nd Edt. University of Amsterdam, www.lulu.com, 291 p. ISBN 978-90-9024981-0; chapter #4: [http://spatial-analyst.net/book/DataSources "Auxiliary data sources"]
 
 
 
 
 
 
 
= Administrative/Topographic data =
 
 
 
== Administrative data ==
 
 
 
Administrative data can be used to calculate proximity-based parameters and to orient the users geographically. One such global administrative data database is the [http://biogeo.berkeley.edu/gadm/ 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 [http://www.fao.org/geonetwork/srv/en/main.home FAO's GeoNetwork server]. Another important global dataset is the [http://www.ngdc.noaa.gov/mgg/coast/ World Vector Shoreline] dataset 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 [http://www.naturalearthdata.com/downloads/ Natural Earth Data] website (compiled by Nathaniel Vaughn (KELSO) and volunteers). These raster 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).
 
 
 
{| border=0
 
|- align=left
 
| [[Image:Dcoast.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/dcoast.zip Distance from the sea coast line].]]
 
|}
 
 
 
Paul Wessel, from the University of Hawai'i, maintains a similar vector database called [http://www.ngdc.noaa.gov/mgg/shorelines/gshhs.html "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 <tt>Rgshhs</tt> command).
 
 
 
Note that some basic (and slightly out-dated) vector maps are available in the R's package [http://cran.r-project.org/web/packages/maps/ "maps"]. This contains data map of political borders, world cities, [http://www.evl.uic.edu/pape/data/WDB/ CIA 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:
 
 
 
<geshi lang=R lines=0>
 
> worldmap <- map2SpatialLines(map("world", fill=TRUE, col="transparent", plot=FALSE),
 
+      proj4string=CRS("+proj=longlat +ellps=WGS84"))
 
> worldmap <- SpatialLinesDataFrame(worldmap, data.frame(name=(map("world"))$names), match.ID=F)
 
> writeOGR(worldmap, "worldmap.shp", "worldmap", "ESRI Shapefile")
 
</geshi>
 
 
 
The original shape files of World political borders can be obtained from [http://thematicmapping.org/downloads/world_borders.php thematicmapping.org]. Wikipedia has a repository of [http://en.wikipedia.org/wiki/Wikipedia:Blank_maps blank maps] of the World (in [[wikipedia:SVG|SVG]] and [[wikipedia:PNG|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 [http://www.iscgm.org Global Map Data project].
 
 
 
== Height/geomorphology data ==
 
 
 
Global SRTM Digital Elevation Model is probably the most well-known global environmental dataset ([http://dx.doi.org/10.1016/S0924-2716(02)00124-7 Rabus et al. 2003]). The area covered is between 60° North and 58° South. It was recorded by X-Band Radar (NASA and MIL, covering 100% of the total global area) and C-Band Radar (DLR and ASI, covering 40%). The non-public DLR-ASI data is available with a resolution of approximately 30 m (1 arcsec). A complete land surface model ETOPO1 Global Relief Model (includes bathymetry data) is available at resolution of 1 km and can be obtained from the [http://ngdc.noaa.gov NOAA's National Geophysical Data Center] ([http://www.ngdc.noaa.gov/mgg/global/relief/ETOPO1/docs/ETOPO1.pdf Amante and Eakins, 2008]). An updated 1 km resolution global topography map ([http://topex.ucsd.edu/WWW_html/srtm30_plus.html SRTM30 PLUS]; used by Google Earth) has been prepared by [http://topex.ucsd.edu/sandwell/publications/124_MG_Becker.pdf Becker et al. (2009)]. On the [http://www.worldclim.org/current worldclim website], you can download global DEMs at different resolutions from 1 km to 2.5, 5 and 10 arc-minutes. The 90 m SRTM DEMs can be obtained from the [http://srtm.csi.cgiar.org/ CGIAR] - Consortium for Spatial Information. From June 2009, ASTER-based Global Digital Elevation Model (GDEM) at resolution of 30 m has been made available to the worldwide public. The GDEM was created by stereo-correlating the 1.3 million-scene ASTER archive of optical images, covering almost 98% of Earth's land surface. The one-by-one- degree tiles can be downloaded from [https://wist.echo.nasa.gov/api/ NASA's EOS data archive] and/or [http://data.gdem.aster.ersdac.or.jp Japan's Ground Data System].
 
 
 
{| border=0
 
|- align=left
 
| [[Image:globedem.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/globedem.zip ETOPO1/SRTM30+ Global Relief Model].]]
 
|}
 
 
 
{| border=0
 
|- align=left
 
| [[Image:slope.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/slope.zip Slope map] (based on SRTM 30+ and ETOPO DEM).]]
 
|}
 
 
 
If you are interested to see how the world (continents) looked like 50, 100 and more millions ago, look at the global paleogeography maps contributed by [http://jan.ucc.nau.edu/~rcb7/globaltext2.html Ron Blakey] ([http://dx.doi.org/10.1130/2008.2441(01) 2008]).
 
 
 
== Socio-economic data ==
 
 
 
The most important global socio-economic data layers are the population density maps and attached socio-economic variables. The [http://sedac.ciesin.columbia.edu/gpw/ 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 [http://www.ciesin.columbia.edu/datasets/downscaled/ SRES gridded global population dataset] ([http://dx.doi.org/10.1007/s11111-007-0035-8 Bengtsson et al., 2006]). It is based on the SRES scenarios developed for the IPCC climate modeling framework, and covers the period 1990-2100.
 
 
 
{| border=0
 
|- align=left
 
| [[Image:pcpopd1.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/pcpopd1.zip Long-term population density map (PC1)].]]
 
|}
 
 
 
{| border=0
 
|- align=left
 
| [[Image:pcpopd2.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/pcpopd2.zip PC2 of the 6 population density maps (anticipated population change)].]]
 
|}
 
 
 
 
 
==  Water resources ==
 
 
 
The most detailed and the most accurate inventory of the global water resources is the [http://www.worldwildlife.org/science/data/item1877.html Global Lakes and Wetlands Database] (GLWD), which comprises lakes, reservoirs, rivers, and different wetland types in the form of a global raster map at 30-arcsec resolution ([http://www.geo.uni-frankfurt.de/fb/fb11/ipg/ag/dl/f_publikationen/2004/lehner_doell_JHydrol2004_GLWD.pdf Lehner and Doll, 2004]). Shape files of the World basins and similar vector data can be best obtained via the [http://iwmidsp.org RS GIS Unit of the International Water Management Institute (IWMI)]. Gabriel Bowen from Purdue University prepared global maps of H- and O-isotopes in the precipitation using data from some 340 stations ([http://wateriso.eas.purdue.edu/waterisotopes/media/PDFs/2003WR002086.pdf Bowen and Revenaugh, 2003]). The original maps can be obtained from the [http://wateriso.eas.purdue.edu/waterisotopes/ Waterisotopes.org].
 
 
 
 
 
= Geo-data via a web-service =
 
 
 
If you wish to obtain similar type of geographic information but only for specific point location, you should consider using some of the free web-services such as the [http://www.geonames.org/export/ws-overview.html GeoNames] (also available via the R package [http://geonames.r-forge.r-project.org/ GeoNames]). For example, to obtain elevation, name of the closest city and/or actual weather at some point location, we can run:
 
 
 
<geshi lang=R lines=0>
 
> install.packages("geonames")
 
> library(geonames)
 
> GNfindNearbyPlaceName(lat=47,lng=9)
 
#!
 
#! name  lat  lng    geonameId  countryCode  countryName  fcl  fcode  distance
 
#! Atzmännig    47.287633  8.988454    6559633  CH  Switzerland  P  PPL  1.6276
 
#!
 
> GNgsrtm3(lat=47,lng=9)
 
#!
 
#!  srtm3 lng lat
 
#! 1  2834  9  47
 
#!
 
> GNweather(north=47,east=8,south=46,west=9)
 
#!
 
#!      clouds weatherCondition
 
#! 1 few clouds              n/a
 
#!                                                observation
 
#! 1 LSZA 231320Z VRB02KT 9999 FEW045 BKN060 04/M02 Q0991 NOSIG
 
#!  ICAO      lng temperature dewPoint windSpeed
 
#! 1 LSZA 8.966667          4      -2        02
 
#!  humidity stationName            datetime lat
 
#! 1      64      Lugano 2009-01-23 14:20:00  46
 
#!  hectoPascAltimeter
 
#! 1                991
 
</geshi>
 
 
 
Another alternative is the Google's maps service, which allows you to obtain similar type of information (Google's service also allows you to [[Mapping_research_hot-spots#Geocoding_addresses|geocode postal addresses]]).
 
 
 
A high quantity of maps can be also obtained via some of the many commercial [[wikipedia:Web_Coverage_Service|WCS]]'s. A list of Open Geospatial Consortium (OGC) [[wikipedia:Web_Mapping_Service|WMS]]'s is available [http://www.ogcnetwork.net/servicelist here]. A popular WMS that allows download of the original vector data is the [http://openstreetmap.org/ Openstreetmap]. The original data come in the OSM format, but can be easily sorted and converted to e.g. ESRI shape files using [http://wiki.openstreetmap.org/wiki/OpenJUMP OpenJUMP GIS]. Another extensive WMS is the NASA's [http://onearth.jpl.nasa.gov/ OnEarth]. NASA also maintains the [http://gcmd.nasa.gov/ Global Change Master Directory] that can be used to locate and download a variety of global environmental maps and field data.
 
 
 
= Remote sensing imagery =
 
 
 
Remote sensing images are increasingly the main source of data for any national/continental scale mapping projects. The amount of field and remote sensing data in the world is rapidly increasing. To get an idea about how many sensors/imagery is currently available, see for example the [http://www.itc.nl/research/products/sensordb/AllSensors.aspx ITC's database]. Down-below I list only the imagery with global coverage (and available at no cost) and of interest for global modelling projects.
 
 
 
== MODIS/MERIS ==
 
 
 
The most attractive source of global high-temporal resolution imagery is the NASA's [https://lpdaac.usgs.gov/lpdaac/products/modis_products_table MODIS] system. MODIS contains a number of products ranging from raw multispectral images, to various vegetation and atmospheric indices; all at resolution of 250 m (also available at coarser resolutions of 500 m and 1 km), and at very high temporal resolution. To import the MODIS images to your GIS, you will first need to obtain the [https://lpdaac.usgs.gov/lpdaac/tools MODIS resampling tool], then [[Download and resampling of MODIS images|reproject/mosaic]] the images to your grid of interest and more compatible data format (e.g. geoTiff).
 
 
 
If you only wish to use already processed MODIS images, then look at the [http://neo.sci.gsfc.nasa.gov/ NASA's Earth Observation] (NEO) portal, which distributes global time-series of MODIS-derived parameters such as: snow cover and ice extent, leaf area index, land cover classes, net primary production, chlorophyll concentration in the sea and sea surface temperature, cloud water content, carbon monoxide in the atmosphere and many more. All the global maps on NEO are freely available for public use. You can simply download the 0.1 arcdegrees (~10 km) GeoTiff's and load them to your GIS. Please credit NASA as the source.
 
 
 
Down-below are shown Principal Components derived using 120 monthly MODIS EVI images. The first component shows the mean biomass over the period of 20 years, the second, thirds and fourth components are assumed to depict the vegetation seasonality, but also different land use practice, vegetation succession and degradation (Eastman and Fulk, 1993).
 
 
 
{| border=0
 
|- align=left
 
| [[Image:PCEVI1.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/PCEVI1.zip PC1 of 120 monthly MODIS EVI images] (mean biomass).]]
 
|}
 
 
 
{| border=0
 
|- align=left
 
| [[Image:PCEVI2.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/PCEVI2.zip PC2 of 120 monthly MODIS EVI images] (seasonality/climate).]]
 
|}
 
 
 
{| border=0
 
|- align=left
 
| [[Image:PCEVI3.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/PCEVI3.zip PC3 of 120 monthly MODIS EVI images] (seasonality/climate).]]
 
|}
 
 
 
{| border=0
 
|- align=left
 
| [[Image:CHLOm.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/CHLOm.zip Mean annual value for the MODIS Chlorophyll Concentration in the sea].]]
 
|}
 
 
 
{| border=0
 
|- align=left
 
| [[Image:CHLOs.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/CHLOs.zip Standard deviation for the MODIS Chlorophyll Concentration in the sea].]]
 
|}
 
 
 
The European version of MODIS TERRA is the ENVISAT MERIS. The [http://envisat.esa.int/ ENVISAT] satellite is a platform for several instruments adjusted for monitoring of the environmental resources: ASAR, MERIS, AATSR, MWR and similar. The MEdium Resolution Image Spectrometer ([http://envisat.esa.int/instruments/ MERIS]) is used to obtain images of the Earth’s surface at temporal resolution of 3–days. The images comprise of 15 bands, all at resolution of 300 m. To obtain MERIS images, one needs to register and receive an access to the repository (unlike the MODIS images that are available directly via an [ftp://e4ftl01u.ecs.nasa.gov/MOLT/ FTP]).
 
 
 
== Landsat/SPOT ==
 
 
 
SPOT and Landsat provide satellite imagery at about 10-30 times finer resolution than MODIS, but at commercial price. A number of their products is also available at no cost. High resolution (15 m) Landsat images for nearly all of the world (years 1990 and 2000) can be downloaded from the [http://seamless.usgs.gov/ NASA’s Seamless Server].
 
 
 
Another excellent repository of free global imagery is the [http://glcf.umiacs.umd.edu/portal/geocover/ GLCF geoportal] operated by the University of Maryland. GLCF provides not only access to raw data but also distribute a number of global products: [http://www.landcover.org/data/landcover/ land cover classification maps], [http://www.landcover.org/data/treecover/ estimated tree cover continuous fields], inventory of [http://www.landcover.org/data/vcc/ burned and deforested areas] and similar ([http://dx.doi.org/10.1016/S0034-4257(02)00081-0 Zhan et al, 2002]). All these data can be accessed also via their [ftp://ftp.glcf.umiacs.umd.edu/ ftp].
 
 
 
[http://www.spot-vegetation.com/ SPOT vegetation] offers a relatively coarse vegetation-based 10–day images of the whole Earth collected in the period from 1998 until today. Only two bands are available at the moment: NDVI and radiometry images.
 
 
 
== Google Earth imagery  ==
 
 
 
You can also consider obtaining the color composites of the high resolution imagery (QuickBird, Ikonos) that are used in Google Earth (this has some [http://www.google.com/permissions/geoguidelines.html copyright restrictions]). The fastest way to download a mosaic for an area of interest is to use the [http://www.softonpc.com/umd/ Universal maps downloader] shareware. You only need to define the zoom level and Left Longitude, Right Longitude, Top Latitude, Bottom Latitude, and then you can sellect if you wish to obtain satellite, terrain or topo-maps (from Google, Microsoft Virtual Earth or Yahoo maps). With [http://cran.r-project.org/web/packages/RgoogleMaps/ RgoogleMaps] package you can also automate retrieval and mosaicking of images. For example, to obtain a hybrid satellite image of the Netherlands, it is enough to define the position of the center and the zoom level (scale):
 
<pre>
 
&gt; library(RgoogleMaps)
 
# Get a satellite image of the Netherlands:
 
&gt; MyMap &lt;- GetMap.bbox(center=c(52.1551723,5.3872035), zoom=7, destfile="netherlands.png", maptype ="hybrid")
 
Read 1 item
 
[1] "http://maps.google.com/staticmap?center=52.1551723,5.3872035&amp;zoom=7&amp;size=640x640
 
+  &amp;maptype=hybrid&amp;format=png32&amp;key=****&amp;sensor=true"
 
trying URL 'http://maps.google.com/staticmap?center=52.1551723,5.3872035&amp;zoom=7&amp;size=640x640
 
+  &amp;maptype=hybrid&amp;format=png32&amp;key=****=true'
 
Content type 'image/png' length 703541 bytes (687 Kb)
 
opened URL
 
downloaded 687 Kb
 
 
 
netherlands.png has GDAL driver PNG
 
and has 640 rows and 640 columns
 
&gt; PlotOnStaticMap(MyMap, lat=52.1551723, lon=5.3872035)
 
</pre>
 
An alternative is to obtain the Google Earth [http://code.google.com/apis/maps/documentation/overlays.html#Google_Maps_Coordinates tiles] directly from the server (e.g. using this [http://www.maptiler.org/google-maps-coordinates-tile-bounds-projection/ maptiler.org python script]), then attach the right georeference (east, west, north, south coordinates) to each tile, and then mosaic them to create a complete GIS layer. Again, you need to be aware that these maps/images are [http://www.google.com/permissions/geoguidelines.html copyrighted], so you should really use them only for your personal purpose, non-commercial use.
 
 
 
Barry Rowlingson is developing a package called [https://r-forge.r-project.org/projects/webmaps/ webmaps] that can be used to load [http://www.openstreetmap.org OpenStreetMap] tiles into R graphics devices (this has no copyright restrictions). It can also be used to create HTML pages that show your points, lines, and polygons on world map data.
 
 
 
== AVHRR ==
 
 
 
Although outdated, AVHRR was the one of the main global environmental monitoring systems in the 80's. A set of 232 monthly NDVI images can be obtained via the [http://iwmidsp.org International Water Management Institute]. The original images are available at resolution of 300 arcseconds (cca 10 km), and cover the period July, 1981 through September, 2001. 
 
 
 
== Aviso Altimetry data ==
 
 
 
A range of satellites (Topex/Poseidon-ERS, Jason-Envisat) are used to track the sea altimetry, tides, significant wave height and wind speed, and alike oceanographic features. Most of these images are available only at course resolution of 0.125-1 arcdegree. Merged data products are available for download via the [http://www.aviso.oceanobs.com AVISO website]. One needs to register to gain the FTP access to [http://www.aviso.oceanobs.com/en/data/products/auxiliary-products/ auxiliary products] such as the long term Mean Sea Surface, Global tide (heights of tidal constituents) and similar.
 
 
 
== Meteorological images ==
 
 
 
The [http://www.eumetsat.int/ Meteosat] Second Generation (MSG) satellites (from Meteosat-8 onwards) produce SEVIRI 15–minutes images at resolution of 1 km. The most attractive data set for environmental applications is the High Rate SEVIRI, which consists of 12 spectral channels including: visible and near infrared light, water vapour band, carbon dioxide and ozone bands. MODIS produces [https://lpdaac.usgs.gov/lpdaac/products/modis_products_table/land_surface_temperature_emissivity/monthly_l3_global_0_05deg_cmg/mod11c3 monthly estimates of the global Land Surface Temperature], which are supposedly highly accurate ([http://dx.doi.org/10.1080/0143116031000116417 Wan et al. 2004]). The time series of MODIS LST images can be used to analyze seasonal variation and compare differences between the temperatures at day and night time. The Japan Aerospace Exploration Agency generated a list of [http://sharaku.eorc.jaxa.jp/GSMaP_crest/ precipitation products] based on a combination of meteorological images. These images are available in resolutions of 0.1 and 0.25 arcdegrees, and can be used to get a more global and consistent estimate of the precipitation patterns (Kubota et al. 2007).
 
 
 
{| border=0
 
|- align=left
 
| [[Image:LSTDm.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/LSTDm.zip Mean Day-time MODIS Land Surface Temperature] based on the monthly LST images.]]
 
|}
 
 
 
{| border=0
 
|- align=left
 
| [[Image:LSTDs.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/LSTDs.zip Deviation of the Day-time MODIS Land Surface Temperature] based on the monthly LST images.]]
 
|}
 
 
 
{| border=0
 
|- align=left
 
| [[Image:PRECm.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/PRECm.zip Mean annual precipitation in mm/month] based on the meteorological images ([http://sharaku.eorc.jaxa.jp/GSMaP_crest/ GSMaP]).]]
 
|}
 
 
 
== Lights at night images ==
 
 
 
Images of lights at night have shown to be highly correlated with industrial activity and Gross Domestic Product ([http://www.iussp.org/Activities/wgc-urb/Small1.pdf  Small et al., 2005]; [http://dx.doi.org/10.1016/j.ecolecon.2005.03.007 Doll et al. 2007]). A time-series of (1 km resolution) annual global night light images is available via the [http://ngdc.noaa.gov/dmsp/downloadV4composites.html NOAA's National Geophysical Data Center]. The lights at night map contains the lights from cities, towns, and other sites with persistent lighting, including gas flares. The filtered annual composites are available from 1992 until 2009 ([http://www.ngdc.noaa.gov/dmsp/pubs/ElvidgeEtAl-Global_urban_mapping_20090618.pdf Elvidge et al, 2009]). Here I show the mean value of the lights at night and the second PCA component derived from the original 1 km maps and resampled to 5 km resolution. The second component indicates the increase/decrease of lights at night over the period.
 
 
 
{| border=0
 
|- align=left
 
| [[Image:nlights.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/nlights.zip Mean night light image for year 2009].]]
 
|}
 
 
 
{| border=0
 
|- align=left
 
| [[Image:pcnligh2.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/pcnligh2.zip Change of night light intensity in period 1992-2009] (PC2).]]
 
|}
 
 
 
= Thematic (derived) maps =
 
 
 
Numerous organizations generate and distribute thematic maps that come as a result of complex GIS modeling and/or manual interpretation. These maps differ from the raw remote sensing imagery or topographic data in a sense that they can imply interpreted information (classes, complex features etc). They are also often generalized by a surveyor/cartographer, so that they are more appropriate for display, orientation, and/or planning. Their biggest limitation is that they often come as a result of subjective interpretation, thus many features are hard to reproduce. Regardless of this limitation, thematic maps carry irreplaceable information about the environment. The following section lists some of the most known global thematic datasets maintained by various teams.
 
 
 
== Land cover / land use maps ==
 
 
 
Land cover maps are categorical-type maps, commonly derived using semi-automated methods and remote sensing images as the main input. There are at least four global land cover mapping projects in the world where such data can be found (they differ in legends, resolution, temporal coverage etc). A [http://bioval.jrc.ec.europa.eu/products/glc2000/products.php Global Land Cover map for the year 2000] (GLC2000) at 1 km resolution is distributed by the Joint Research Centre in Italy (Bartholome et al., 2002). A slightly outdated (1998) global map of land cover is provided by the [http://glcf.umiacs.umd.edu/data/landcover/data.shtml AVHRR Global Land Cover Classification], provided at resolutions of 1 and 8 km ([http://glcf.umiacs.umd.edu/pdf/ijrs21_p1331.pdf Hansen et al. 2000]). [http://www.iscgm.org International Steering Committee for Global Mapping] provides access to the [http://www.iscgm.org/browse.html Global Land Cover by National Mapping Organizations] (GLCNMO) map, produced using MODIS data observed in 2003. European Space Agency has recently released the [http://ionia1.esrin.esa.int GlobCover Land Cover version V2] dataset, produced using the ENVISAT MERIS images. So far, this is the highest resolution (300 meters) Global Land Cover product in the world. The forth important source of land cover data is the [https://lpdaac.usgs.gov/lpdaac/products/modis_products_table/land_cover/yearly_l3_global_0_05deg_cmg/mod12c1 MODIS12C1 Land Cover Type Yearly L3 Global] product (available in resolution from 500 m to 0.05 arcdegrees). The advantage of using the MODIS Land cover maps (17 land cover classes defined by the [http://www.igbp.kva.se International Geosphere Biosphere Programme] - IGBP) is that this is a temporal dataset so that one can also derive various change indices and quantify the land cover dynamics ([http://dx.doi.org/10.1016/S0034-4257(02)00078-0 Friedl et al. 2002]).
 
 
 
In addition to standard land cover maps, [http://dx.doi.org/10.1890/070062 Ellis and Ramankutty (2008)] prepared the first global map of the anthropogenic biomes (18 classes; [http://www.eoearth.org/article/Anthropogenic_biomes read more]) showing dense settlements, villages, croplands, rangelands, forested lands and wildlands. FAO distributes a number of global thematic maps (usually at 5 arcmin resolution) including: suitability for various type of land use, soil and water resources, maps of environmental conditions, and similar. This can be downloaded directly from the [http://www.fao.org/geonetwork/srv/en/main.home FAO's GeoNetwork server].
 
 
 
{| border=0
 
|- align=left
 
| [[Image:globcov.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/globcov.zip Land Cover classes based on the MERIS FR images] ([http://ionia1.esrin.esa.int GlobCover Land Cover version V2.2]).]]
 
|}
 
 
 
{| border=0
 
|- align=left
 
| [[Image:glcrop.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/glcrop.zip Cropland areas in 1992].]]
 
|}
 
 
 
{| border=0
 
|- align=left
 
| [[Image:anthroms.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/anthroms.zip Map of 18 anthropogenic biomes] ([http://dx.doi.org/10.1890/070062 Ellis and Ramankutty, 2008]).]]
 
|}
 
 
 
 
 
The International Water Management Institute also produced the [http://www.iwmigiam.org/info/gmia/ Global map of Irrigated Areas] (GMIA; 28 classes) and the [http://www.iwmigiam.org/info/gmrca/ Global map of Rainfed Cropped Areas] (GMRCA), both at 10 km resolution, and based on the twenty years of AVHRR images, augmented with higher resolution SPOT and JERS-1 imagery. A Global Map of Irrigation Areas is also available for [ftp://ftp.fao.org/agl/aglw/aquastat/ download] (ArcInfo ASCII grids and shape files) via the [http://www.fao.org/nr/water/aquastat/irrigationmap/ FAO's Information System on Water and Agriculture] website.
 
 
 
{| border=0
 
|- align=left
 
| [[Image:gmia.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/gmia.zip Global map of area equipped for irrigation] expressed as percentage of total area.]]
 
|}
 
 
 
[http://www.sage.wisc.edu/mapsdatamodels.html Center for Sustainability and the Global Environment (SAGE)], a research center of the Nelson Institute for Environmental Studies at the University of Wisconsin-Madison, distributes a number of global Land Use products: (1) Crop Calendar Dataset, (2) harvested area and yields of 175 crops, (3) historical and current cropland maps and similar. 1 arcmin resolution global yield estimates for 175 crops (year 2000) can be obtained directly from the [http://www.geog.mcgill.ca/landuse/pub/Data/175crops2000/ Department of Geography, McGill University] website. A number of human impacts, land use, water resources and ecosystem maps can be browsed more systematically via the SAGE's [http://www.sage.wisc.edu/atlas/maps.php AtlasBiosphere server].
 
 
 
== Climatic maps ==
 
 
 
[http://www.worldclim.org/ WorldClim.org] provides global maps of some 18 bioclimatic parameters derived (thin plate smoothing splines) using >15,000 weather stations ([http://www.worldclim.org/worldclim_IJC.pdf Hijmans et al., 2005]). The climatic parameters include: mean, minimum and maximum temperatures, monthly precipitation and bioclimatic variables. All at ground resolution of 1 km. Coarse 1 degree global monthly and daily precipitation data (1979-present) can be obtained via the [http://precip.gsfc.nasa.gov/ NASA/GSFC]. [http://www.cru.uea.ac.uk/ Climatic Research Unit] of the University of East Anglia prepared a [http://www.cru.uea.ac.uk/cru/data/hrg/tmc/ repository] of high resolution maps (10 arcseconds) representing mean monthly surface climate over global land areas, excluding Antarctica ([http://www.int-res.com/articles/cr2002/21/c021p001.pdf New et al. 2003]). Even more detailed climatic images can be obtained via the [http://www.gewex.org/datasets.html Global Energy and Water Cycle Experiment project] and [http://badc.nerc.ac.uk/browse/badc/ British Atmospheric Data Centre] (BADC).
 
 
 
{| border=0
 
|- align=left
 
| [[Image:biocl1.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/biocl1.zip Annual Mean Temperature].]]
 
|}
 
 
 
{| border=0
 
|- align=left
 
| [[Image:biocl2.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/biocl2.zip Mean Diurnal Range (Mean of monthly (max temp - min temp))].]]
 
|}
 
 
 
{| border=0
 
|- align=left
 
| [[Image:biocl5.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/biocl5.zip Max Temperature of Warmest Month].]]
 
|}
 
 
 
{| border=0
 
|- align=left
 
| [[Image:biocl12.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/biocl12.zip Annual Precipitation in mm].]]
 
|}
 
 
 
 
 
The National Geophysical Data Centre (NGDC) provides [http://www.ngdc.noaa.gov/stp/ftp.html free access] to numerous remote sensing based global maps - from solar parameters to cloud imagery, energetic particle measurements and similar (collectively called "Solar-terrestrical physics" products).
 
 
 
[http://nsidc.org/data/easytouse.html The National Snow and Ice Data Center] maintains a number of global datasets - frozen ground maps, monthly satellite-derived snow water equivalent (SWE) climatologies and similar. These data can be obtained for norhtern and southern hemisphere at resolution of 25 km.
 
 
 
== Ecoregions/Biogeographic regions ==
 
 
 
Ecoregions are terrestrial, freshwater and/or marine areas with characteristic combinations of soil and landform that characterize that region. [http://www.worldwildlife.org/science/ecoregions/WWFBinaryitem6498.pdf Olson et al. (2001)] produced the [http://www.worldwildlife.org/science/ecoregions/item1267.html Terrestrial Ecoregions] global data set, which shows some 867 distinct eco-units, including the relative richness of terrestrial species by ecoregion. The legend for the map shown down-below is attached to the original grid map. A somewhat more generalized is the [http://cdiac.ornl.gov/ftp/global_carbon/ecofloristic_zones.zip FAO's map of Eco-floristic regions] (e.g. boreal coniferous forest, tropical rainforest, boreal mountain system etc.).
 
 
 
NOAA's NGDC prodives a [ftp://ftp.ngdc.noaa.gov/Solid_Earth/Ecosystems/ free access] to several global ecosystem maps including the [ftp://ftp.ngdc.noaa.gov/Solid_Earth/Ecosystems/CEOS_Ecoregions/datasets/b03/bec.htm Bailey (1993) Ecoregions of the Continents]. From their [http://www.ngdc.noaa.gov/ngdcinfo/onlineaccess.html website], you can either choose to [http://www.ngdc.noaa.gov/maps/interactivemaps.html browse the maps interactively] via a WMS or using KML files, or access it directly via [ftp://ftp.ngdc.noaa.gov/ ftp].
 
 
 
{| border=0
 
|- align=left
 
| [[Image:wwfeco.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/wwfeco.zip Terrestrial ecoregions]: 867 distinct eco-units.]]
 
|}
 
 
 
{| border=0
 
|- align=left
 
| [[Image:ecoflor.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/ecoflor.zip Global Eco-floristic regions]: 22 distinct units.]]
 
|}
 
 
 
== Soil/geology maps ==
 
 
 
Soil and geology maps are especially important for SDM of vascular plants. One harmonized global soil-type map is the [http://soils.usda.gov/use/worldsoils/mapindex/order.html USGS Global Soil Regions] map at resolution of 60 arcsec (FAO-UNESCO, 2005). The USDA global soil data is also available via [ftp://ftp-fc.sc.egov.usda.gov/NHQ/pub/outgoing/soils/ ftp]. FAO, IIASA, ISRIC, ISSCAS, JRC have recently produced a 1 km resolution gridded map, by merging various national soil maps, which is also known as the [http://www.fao.org/nr/water/news/soil-db.html Harmonized World Soil Database (v 1.1)]. Global HWSD-derived soil property maps for top- and sub-soil can be download as geotifs from [http://spatial-analyst.net/worldmaps/HWSD_.zip here]. A list of seven gridded soil property maps (at resolution of 5 arc-minutes) - soil-carbon density, total nitrogen density, field capacity, wilting point, profile available water capacity, thermal capacity, and bulk density - is available via the [http://daac.ornl.gov/SOILS/guides/igbp-surfaces.html IGBP-DIS data set]. Some additional soil property maps such as [http://www.sage.wisc.edu/atlas/data.php?incdataset=Soil%20pH pH] and [http://www.sage.wisc.edu/atlas/data.php?incdataset=Soil%20Moisture soil moisture], can be also obtained from the [http://www.sage.wisc.edu/atlas/data.php Atlas of Biosphere project]. Status of the soil information in the world can be also followed via David G. Rossiter's [http://www.itc.nl/~rossiter/research/rsrch_ss_digital.html compendium of On-Line Soil Survey Information].
 
 
 
USDA Soil Survey Division also distributes the global map of wetlands (includes: upland, lowland, organic, permafrost and salt affected wetlands). ISRIC maintains [http://www.isric.org/UK/About+Soils/Soil+data/Geographic+data/Global/Global+soil+profile+data.htm a global soil profile database] with over 12,000 profiles and over 50 analytical and descriptive parameters ([http://www.isric.org/isric/webdocs/Docs/ISRIC_Report_2008_02.pdf Batjes, 2008]). [http://earthtrends.wri.org/text/forests-grasslands-drylands/map-226.html Global Carbon storage in soils] is available from the WRI website. 
 
 
 
The only global geological map available at the moment is the [http://ccgm.free.fr/index_gb.html 1:25M Geological Map of the World] ([http://ccgm.free.fr/doc/Expl%20Notes%20Geol%20Map%20World.pdf Bouysse, 2009]; maps not available publicly). The geological maps are now being integrated via the [http://www.onegeology.org/ OneGeology] project which aims at producing a consistent Geological map of the world in approximate scale 1:1M; progress can be followed via their interactive [http://portal.onegeology.org/ portal]. USGS has several data [http://energy.usgs.gov portals], e.g. that allow browsing of the [http://certmapper.cr.usgs.gov/data/envision/index.html International Surace Geology] (split into South Asia, South America, Iran, Gulf of Mexico, Former Soviet Union, Europe, Carribean, Bangladesh, Asia Pacific, Artic, Arabian Peninsula, Africa and Afganistan).
 
 
 
 
 
{| border=0
 
|- align=left
 
| [[Image:hwsd.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/hwsd.zip Major FAO soil groups] based on the Harmonized World Soil Database ([http://spatial-analyst.net/worldmaps/HWSD_.zip download soil property maps]).]]
 
|}
 
 
 
== Natural Hazards ==
 
 
 
A number of institutions have jointly produced a [http://www.seismo.ethz.ch/GSHAP/ Global Seismic Hazard map] ([http://hdl.handle.net/2122/1391 Giardini, 1999]). This map, although slightly outdated and of limited detail, can be obtained directly from the project [http://www.seismo.ethz.ch/GSHAP/ webite]. From the [http://ngdc.noaa.gov/hazard/earthqk.shtml NOAA's National Geophysical Data Center] one can obtain a point map with all major earth quakes (Significant Earthquake Database; cca 5000 quakes), and generate a (kernel density) map for Earthquake magnitude (shown below).  University of Hawaii maintains a [http://www.pdc.org/mde/ Global Hazards Information Network], which contains a number of global layers including a [http://www.pdc.org/geodata/world/airports_dafif.zip map of Global Airports], locations of [http://www.pdc.org/geodata/world/earthquake.zip significant earthquakes] and earthquake zones.
 
 
 
{| border=0
 
|- align=left
 
| [[Image:quakein.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/quakein.zip Earthquake intensity (magnitude)].]]
 
|}
 
 
 
{| border=0
 
|- align=left
 
| [[Image:burned.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/burned.zip Burned vegetation for years 2002-2004].]]
 
|}
 
 
 
{| border=0
 
|- align=left
 
| [[Image:stormtr.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/stormtr.zip Density of Tropical Cyclone Storm Tracks (historical)].]]
 
|}
 
 
 
{| border=0
 
|- align=left
 
| [[Image:Lightning map.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/LISOTD.zip Lightning combined Flash Rate].]]
 
|}
 
 
 
 
 
[http://thunder.msfc.nasa.gov/data/index.html NASA's Climate Center Lightning Team] maintains a global map of Lightning Activity. The average yearly counts of lightning flashes per square kilometer based on data collected by NASA satellites between 1995 and 2002 can be obtained from [http://thunder.msfc.nasa.gov/data/ here].
 
 
 
==  World forest/wildlife resources ==
 
 
 
FAO periodically (every 5 years) organizes the so called [http://www.fao.org/forestry/fra/en/ Forest Resources Assessment] (FRA) - an international compilation of forest resource assessment (forest maps, heatlh and vitality status, forest functions and policies connected with forest management). This assessment typically results in a comprehensive report that includes both graphical and tabular data (see e.g. [ftp://ftp.fao.org/docrep/fao/008/a0400e FRA2005 report]). Global maps (projected in the [http://en.wikipedia.org/wiki/Goode_homolosine_projection Goode Homolosine Interrupted projection]) for year 2000 (FRA2000) can be obtained from the [http://edc2.usgs.gov/glcc/fao/ USGS website]. The most recent [http://www.fao.org/forestry/fra/fra2005/en/ FRA2005] can be ordered on a CD (not for public distribution).
 
 
 
There are two additional important global forest/wildlife datasets: (1) [http://www.intactforests.org The world map of intact forest landscapes] (hardly touched by mankind) at scale 1:1,000,000 (includes four classes of intact forests: 1. intact closed forests; 2. intact open forests, 3. woodlands and savannas, closed forests; and 4. open forests, woodlands and savannas) --- maintained by the Greenpeace (2006) organization ([http://www.ecologyandsociety.org/vol13/iss2/art51/ Potapov, et al. 2008]), and (2) [http://geodata.grid.unep.ch/ World Wilderness Areas] at scale 1:1,000,000 --- distributed via the UNEP GEO Data Portal (McClosey, and Spalding, 1998).
 
 
 
{| border=0
 
|- align=left
 
| [[Image:iflworld.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/iflworld.zip The world map of intact forest landscapes].]]
 
|}
 
 
 
{| border=0
 
|- align=left
 
| [[Image:wildness.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/wildness.zip World wilderness areas] (hardly touched by mankind).]]
 
|}
 
 
 
{| border=0
 
|- align=left
 
| [[Image:treecov.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/treecov.zip Vegetation (Percent Tree Cover)] according to the [http://www.iscgm.org/GM_ptc.html ISCGM].]]
 
|}
 
 
 
== Biodiversity / human impacts maps ==
 
 
 
[http://data.gbif.org GBIF] provides global maps showing the distribution of all flora and fauna species. The density maps are available only at resolution of 1 arcdegree (about 100 km). Global maps of biodiversity measures for various groups of taxa (e.g. vascular plants, birds and mammals) can be browsed using the [http://stort.unep-wcmc.org/imaps/gb2002/book/viewer.htm World Atlas of Biodiversity viewer] (showing mainly the data published in Groombridge and Jenkins, 2002). Similar type of maps can be browsed via the [http://www.unep-wcmc.org/ UNEP's World Conservation Monitoring Centre]. National and international protected sites and attributes can be downloaded (ESRI Shapefiles; after registering on the website) via the [http://www.wdpa.org/WDPAMapFlex.aspx World Database On Protected Areas]. International Union for Conservation of Nature and Natural Resources (IUCN) has recently released a Red List of Threatened Species that contains assessments for 49,000 species. Distribution maps (presence) for these species (with limited coverage) can be downloaded from the [http://www.iucnredlist.org/technical-documents/spatial-data IUCN website].
 
 
 
A shape file showing location of hotspot regions is distributed by the [http://www.biodiversityhotspots.org/ Conservation International]. The NEES Institute for Plants in Bonn has produced a number of [http://www.nees.uni-bonn.de/biomaps/worldmaps.html global biodiversity maps] including the map of plant species richness zones and floristic knowledge ([http://dx.doi.org/10.1111/j.1365-2699.2005.01272.x Kier et al, 2005]). Unfortunately the GIS data is not available publicly from the Institute's website, but only high resolution figures. [http://www.pnas.org/content/104/14/5925.abstract Kreft and Jetz (2007)] recently produced a global map of plant species diversity (number of plant species) by using field records from 1,032 locations (map is available only in coarse resolution of 120 km). [http://www.birdlife.org/datazone/index.html BirdLife International] publishes a number of global maps indicating so called "[http://earthtrends.wri.org/text/biodiversity-protected/map-222.html Endemic and Important Bird Areas]" (IBAs and EBAs). 
 
 
 
{| border=0
 
|- align=left
 
| [[Image:gaccessm.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/gaccessm.zip Estimated travel time to major cities (>50k) in hours].]]
 
|}
 
 
 
{| border=0
 
|- align=left
 
| [[Image:himpact.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/himpact.zip Areas of human impacts on the Biosphere] (roads, railways and settlement density).]]
 
|}
 
 
 
{| border=0
 
|- align=left
 
| [[Image:biodvhot.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/biodvhot.zip Hotspot biodiversity regions in the world based on the Conservation International].]]
 
|}
 
 
 
Partners in the [http://www.globio.info GLOBIO consortium] created a World Map of Human Impacts on the Biosphere for various time periods. This is basically a map showing a current status of the roads, railways and settlement density (UNEP, 2002). Human impact maps can be browsed via the [http://maps.grida.no UNEP Grid Arendal]. Andy Nelson ([http://dx.doi.org/10.2788/95835 2008]) has computed [http://bioval.jrc.ec.europa.eu/products/gam/ a global map of accessibility], i.e. a map showing travel time to major cities, using a variety of [http://bioval.jrc.ec.europa.eu/products/gam/sources.htm GIS layers] (all these are publicly available). The International Biosphere-Geosphere Programme, the Stockholm Environment Institute, the Stockholm Resilience Center, the CSIRO in Australia and the International Human Dimensions Programme on Global Environmental
 
Change are producing qan outreach project on the Anthropocene and planetary boundaries. One of the objectives of this project is to make a detailed inventory of the [http://www.globaia.org/en/anthropocene/gts.jpg Global Transportation System].
 
 
 
A comprehensive global assessment of the human impacts to marine ecosystems can be followed via the work of the [http://www.nceas.ucsb.edu/ National Center for Ecological Analysis and Synthesis] in Santa Barbara. This group have produced [http://www.nceas.ucsb.edu/globalmarine a Global Map of Human Impacts to Marine Ecosystems] by using a number of connected input GIS layers ([http://dx.doi.org/10.1126/science.1149345 Halpern et al. 2008]). These layers are available for [http://www.nceas.ucsb.edu/globalmarine/impacts download] as GeoTiff and/or ESRI grids. Distribution of global airports and flight routes can be freely accessed from the [http://openflights.org/data.html openflights.org] (maintained by Conentshare company). A global map of flight routes can be ordered via the [http://www.lx97.com/maps/ LX97 company]. Chris Harrison produced the [http://www.chrisharrison.net/projects/InternetMap/index.html world map] of internet connectivity and traffic.
 
 
 
{| border=0
 
|- align=left
 
| [[Image:Shipping_routes.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/shipping.zip Shipping density (commercial)].]]
 
|}
 
 
 
{| border=0
 
|- align=left
 
| [[Image:Airroute.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/airroute.zip Estimated density of airline routes] (based on the [http://openflights.org/data.html OpenFlights data]).]]
 
|}
 
 
 
[http://cdiac.ornl.gov/ftp/ The Carbon Dioxide Information Analysis Center] provides access to numerous ecological layers and data of interest to global ecologists. One such product is the Global Biomass Carbon Map (Carbon density tones of C / ha), prepared for year 2000 ([http://cdiac.ornl.gov/epubs/ndp/global_carbon/carbon_documentation.html Ruesch et al. 2008]). From their [http://cdiac.ornl.gov/ftp/ ftp], you can download a number of GIS layers of interest for ecological modelling (e.g. map of Eco-floristic zones, GLC2000 dataset etc).
 
 
 
{| border=0
 
|- align=left
 
| [[Image:gcarb.png|center|thumb|500px|Figure: [http://spatial-analyst.net/worldmaps/gcarb.zip Global Biomass Carbon Map]: Carbon density tones of C / ha.]]
 
|}
 
 
 
= References =
 
 
 
* Amante, C., Eakins, B. W., 2008. [http://www.ngdc.noaa.gov/mgg/global/relief/ETOPO1/docs/ETOPO1.pdf ETOPO1 1 Arc-Minute Global Relief Model: Procedures, Data Sources and Analysis]. National Geophysical Data Center, NESDIS, NOAA, U.S. Department of Commerce, Boulder, CO.
 
* Bartholome at al., 2002. [http://www-tem.jrc.it/glc2000/ GLC 2000 Global Land Cover mapping for the year 2000]. European Commission, DG Joint Research Centre, EUR 20524 EN, pp. 62.
 
* Batjes, N.H., 2008. [http://www.isric.org/isric/webdocs/Docs/ISRIC_Report_2008_02.pdf ISRIC-WISE global soil profile dataset (ver. 3.1)]. Report 2008/02, ISRIC - World Soil Information, Wageningen, p. 57.
 
* Becker, J. J., D. T. Sandwell, W. H. F. Smith, J. Braud, B. Binder, J. Depner, D. Fabre, J. Factor, S. Ingalls, S-H. Kim, R. Ladner, K. Marks, S. Nelson, A. Pharaoh, G. Sharman, R. Trimmer, J. vonRosenburg, G. Wallace, P. Weatherall., 2009. [http://topex.ucsd.edu/sandwell/publications/124_MG_Becker.pdf Global Bathymetry and Elevation Data at 30 Arc Seconds Resolution: SRTM30_PLUS, revised for Marine Geodesy], Marine Geodesy, in press.
 
* Bengtsson, M., Shen, Y., Oki, T., 2006. [http://dx.doi.org/10.1007/s11111-007-0035-8 A SRES-based Gridded Global Population Dataset for 1990–2100]. Population and Environment, 28(2): 113-131.
 
* Blakey, R. C., 2008. [http://dx.doi.org/10.1130/2008.2441(01)​ Gondwana paleogeography from assembly to breakup - a 500 million year odyssey], in: Fielding, Christopher R., Frank, Tracy D., and Isbell, John L. (eds), Resolving the Late Paleozoic Ice Age in Time and Space: Geological Society of America, Special Paper 441, p. 1-28.
 
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