Geographic data: sources and considerations

Geographical Concepts:

• Geographic coordinate system: defines locations on the earth using an angular unit of measure, a prime meridian, and a datum

- datum: defines the position of the origin and the orientation of latitude and longitude lines

• Map projection: mathematical transformation of the three-dimensional surface of the earth into a flat map sheet

Types of spatial data in GIS

• Vector data: points, lines, polygons (shapefiles)

• Raster data: used in ecological niche modeling for representing environmental conditions (grids)

Example of interpolated surface from point data using Inverse Distance Weighting technique. Courtesy: Science Applications International Corporation

Raster obtained through interpolation Raster obtained through remote sensing

Characteristics of geographic data

• Quality: →Interpolated vs. remotely sensed

→Scale at which interpolation was done

• Spatial resolution – has to match the scale of the

questions we try to address with ENM

• Temporal resolution: can represent daily,

monthly, annual, or multi-annual averages

• Type: categorical vs. continuous (some

ecological niche modeling algorithms don't work

well with categorical data)

1.Quality: interpolation

WorldClim dataset: locations of climate stations with precipitation data - 47,554 stations

IPPC climate dataset: precipitation data from 19,800 stations

Mean annual precipitation (1960-1990)

WorldClim 1.4

2. Spatial resolution

• size of the cells in the raster

IPPC mean annual precipitation 0.5° resolution WorldClim mean annual precipitation 0.008° resolution

Florida panhandle

3. Temporal resolution

• time period averaged (days, months, decades, etc)

MODIS EVI 15-30 October MODIS EVI 30 October-15November

NASA/GSFC/University of Arizona

Climate projections

Past climate scenarios (e.g. Pleistocene)

Future climate scenarios

Mean maximum temperature (1960-1990)

4. Type• Continuous data – surfaces, used for natural (physical phenomena); the values are assigned to the points and represent the actual measured value

Land cover 2000

• Categorical data – correspond to discrete fields; the values are assigned to the entire cell area and represent the category number

Digital elevation model

Points to keep in mind when selecting geographic data for ENM

• Temporal and spatial resolution of geographic data has to match those of species occurrence data; also, select a spatial resolution that matches the question asked (e.g. continental spread of an invasive species, vs. predicted distribution of a local endemic species)

• Categorical data doesn’t work well with some niche modeling algorithms; it is also difficult to match its temporal resolution with occurrence data

• Remotely sensed data is powerful (no interpolation), but can only be used with recent, up to date, species occurrence datasets

• When downloading geographic data, pay attention to projection and datum, and any metadata available; some transformations may be necessary

Sources of data

•Climatic (Global) data:

WorldClim current (1960-1990) climate data http://www.worldclim.org/

IPCC current and future climate datahttp://www.ipcc-data.org/obs/get_30yr_means.htmlhttp://www.ipcc-data.org/ddc_climscen.html

Climatic Research Unit http://www.cru.uea.ac.uk/cru/data/hrg.htm

Paleoreconstructions PMIP http://pmip.lsce.ipsl.fr/NOAA: http://www.ncdc.noaa.gov/paleo/

Sources of data

•Topographic and bathymetric:

USGS Hydro 1k http://edc.usgs.gov/products/elevation/gtopo30/hydro/

NOAA ETOPO www.ngdc.noaa.gov/mgg/global/seltopo.htmlBathymetry http://ibis.grdl.noaa.gov/cgi-bin/bathy/bathD.pl

•Marine data:

NOAA World Ocean Atlas http://www.nodc.noaa.gov/OC5/indprod.html

Climate Prediction Center http://www.cpc.noaa.gov/products/predictions/30day/SSTs/sst_clim.html

•Satellite-derived (free):

Global Vegetation Indices:

MODIS http://edcdaac.usgs.gov/dataproducts.asp(EVI and NDVI) 2000 to present

AVHRR http://edcsns17.cr.usgs.gov/1KM/1kmhomepage.html(NDVI): 1985 to present

Global Land Cover:

IES Global Landcover 2000 http://www-gvm.jrc.it/glc2000/

University of Maryland (1992) http://glcf.umiacs.umd.edu/data/

Sources of data

Other data

WWF Ecoregions http://www.worldwildlife.org/science/data.cfm

UNEP IUCN Protected Areas http://sea.unep-wcmc.org/wdbpa/