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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
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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
Example of interpolated surface from point data using Inverse Distance Weighting technique. Courtesy: Science Applications International Corporation Types of spatial data in GIS • Vector data: points, lines, polygons (shapefiles) • Raster data: used in ecological niche modeling for representing environmental conditions (grids) 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 WorldClim 1.4 Mean annual precipitation (1960-1990) IPPC climate dataset: precipitation data from 19,800 stations
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
MODIS EVI 15-30 October MODIS EVI 30 October-15November 3. Temporal resolution • time period averaged (days, months, decades, etc)
Climate projections Mean maximum temperature (1960-1990) Past climate scenarios (e.g. Pleistocene) Future climate scenarios
4. Type • Categorical data – correspond to discrete fields; the values are assigned to the entire cell area and represent the category number • Continuous data – surfaces, used for natural (physical phenomena); the values are assigned to the points and represent the actual measured value Land cover 2000 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 data • http://www.ipcc-data.org/obs/get_30yr_means.html • http://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 • 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 • Topographic and bathymetric: • USGS Hydro 1k http://edc.usgs.gov/products/elevation/gtopo30/hydro/ • NOAA ETOPO www.ngdc.noaa.gov/mgg/global/seltopo.html • Bathymetry http://ibis.grdl.noaa.gov/cgi-bin/bathy/bathD.pl
Sources of data • 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/
Other data WWF Ecoregions http://www.worldwildlife.org/science/data.cfm UNEP IUCN Protected Areas http://sea.unep-wcmc.org/wdbpa/