Exercises: finding datasets, global coverage:
Data acquisition methods for anthropological research.
Exercises: finding datasets, global coverage:
Data acquisition methods for anthropological research.
This class session will focus on means of incorporating new and existing datasets into a GIS environment.
Incorporating new and existing data into a GIS is a major obstacle to applying digital analysis methods to anthropological research. How do you acquire digital data in remote locations with poor access to electricity? How do you reconcile the differences in scale between
These methods deserve a one quarter class apiece and there is insufficient time to go into detail on remote sensing or total station data acquisition.
This week we will focus on the input of digital data. There are a variety of imagery and scanned map sources available on the web and in the first exercise you will georeference a scanned map of South America (7mb).
Note that this JPG map has Lat/Long coordinates on the margins of the map. These will allow us georeference the data provided we know the coordinate system and datum that the Lat/Long gradicule references. If we did not have the Lat/long gradicule we may be able to do without it by georeferencing features in the map such as the hydrology network, major road junctions and other landscape features to satellite imagery in a similar way. But what projection and coordinate system were they using? Notice that the lines of longitude are converging towards the south. This is a projection used for displaying entire continents known as "Azimuthal Equidistant"
Note that there is a lot of error in the result. These are shown as blue Error lines in Arcmap. Perhaps we should have georeferenced this map to a Conic projection. There are helpful resources online for learning about map projections. These include
As you'll see in the exercise below, it's much easier to georeference GoogleEarth imagery because the latitude/longitude graticule consists of right-angles. It is a flat geographic projection.
Acquiring and Georeferencing data for your study area.
Visit the area in GoogleEarth (download free GoogleEarth installer, if necessary) and georeference data using these instructions
Finally, as part of this assignment:
Incidentally, with ArcGIS 9.2 the GoogleEarth vector format (KML) is supported for direct read/write from within Arcmap.
1. Next, we will acquire topographic data for your study area from the SRTM data (CGIAR).
Instructions for converting GeoTIFF DEM data to GRID (for both SRTM and ASTER DEM data)
setnull ( [GRIDNAME] < 0 , [GRIDNAME] )
That command sets all topographic values less than 0 (sea level) and the no-data collar area to <NULL>.
If your study area is on the edge of various tiles you can merge them into a single large GRID by using the following method:
Zoom out to show the whole study area and go to "Options..." in the Spatial Analyst, choose "Extent" tab, and scroll the list upward to "Set the Extent to the same as Display".
Return to the Spatial Analyst > Raster Calculator and do this
mosaic ( [GRIDNAME1] , [ GRIDNAME2], [GRIDNAME3] )
with as many grids as you need.
2. To get topographic data that is 30m (3x higher resolution than SRTM), try to acquire topographic data from ASTER. The problem with ASTER is that it is from individual satellite images and so there are a lot of edge issues, and also any clouds will appear as big holes in your dataset. However, ASTER is probably the best free DEM layer you'll get in less-developed nations of the world, and you also can get a 15m resolution satellite image that registers perfectly to the DEM for further analysis. It's definitely worth the time searching for ASTER imagery.
To be clear: by locating a cloud free ASTER scene you can get both 30m DEM (topography) and 15m multiband imagery from that particular scene.
ASTER DEM arrives as GeoTiff and it can be converted to GRID using the same instructions mentioned above (section B1) for SRTM data.
ASTER imagery processed to the L1B level and acquired in a multiband format called HDF-EOS Swath. The HDF format can not be directly imported into ArcGIS but you can convert these filese to GeoTIFF using free software following the directions posted here.
Visit the Univ of Maryland data depot and acquire a scene of Landsat TM+ imagery for your area using Map search.
Some countries serve geographic datasets online and you may download these from government-specific servers. For example, there are many datasets for regions in the United States on federal and state GIS servers and the European Union serves a variety of datasets online as well.
Research taking place in other countries will find that policies vary widely for two principal reasons. First, in the case of many less-developed countries, there may be few detailed digital data available for the public. Secondly, many countries have strict copyright restrictions on government data and serving those datasets on line for reuse in a GIS and maps for publication would violate copyright laws.
In these cases, global datasets like the raster data presented above and a few global vector data sources, are particularly valuable. Vector data at 1:1 million and 1:250,000 scale are available in the public domain from an older US Government project known as Vector Smartmap (VMAP).
The official server for VMAP data is NIMA's Raster Roam server, however it is easier to acquire VMAP0 and VMAP1 datasets from MapAbility.com. These data are in WGS84, decimal degree. ArcGIS can read the VPF format directly and you can save them out as Geodatabase or Shapefile.
You can download the VMAP0 level data on a country by country basis, rather than in large tiles, at the Digital Chart of the World.
The less-detailed VMAP0 data is largely consistent with the ESRI World dataset that you may have on your computer. The 2006 edition of ESRI Data and Maps comes on five DVDs with the global SRTM topographic data set included.
There have been efforts to get the US Government to release the entire VMAP1 dataset because it is not technically classified (it is "limited distribution") and as an unclassified, tax-payer funded project there is an obligation to release the data under the Freedom of Information Act.
Other useful sources of free geographical data are indexed online at websites like GlobalMapper. Searching the web with terms like your geographical area and "shapefile" can sometimes turn up useful project-specific datasets served online.
These US Government data are in the public domain, but in publications and websites using these data you should include a line thanking the source. It might read something like this
"We want to thank NASA and JPL for allowing the use of their ASTER and Landsat Images."
