Data quality is a central theme of this blog and our book. Here, we focus on quality of geospatial information, which is most often in the form of maps. One of my favorite maps in terms of the richness of information and the choice of symbology is this “simple map of future population growth and decline” from my colleague at Esri, cartographer Jim Herries. Jim symbolized this map with red points indicating areas that are losing population and green points indicating areas that are gaining population. This map can be used to learn where population change is occurring, down to the local scale, and, with additional maps and resources, help people understand why it is changing and the implications of growth or decline.
But the map can also be an effective tool to help people understand issues of data collection and data quality. Pan and zoom the map until you see some rivers, lakes, or reservoirs, such as Littleton Colorado’s Marston Reservoir, shown on the map below. If you zoom in to a larger scale, you will see points of “population” in this and nearby bodies of water. Why are these points shown in certain lakes and rivers? Do these points represent “aqua people” who live on houseboats or who are perpetually on water skis, or could the points be something else?
The points are there not because people are living in or on the reservoir, but because the dots are randomly assigned to the statistical area that was used. In this case, the statistical areas are census tracts or block groups, depending on the scale that is being examined. The same phenomena can be seen with dot density maps at the county, state, or country level. And this phenomenon is not confined to population data. For example, dot density maps showing soybean bushels harvested by county could also be shown in the water, as could the number of cows or pigs, or even soil chemistry from sample boreholes. In each case, the dots do not represent the actual location where people live, or animals graze, or soil was tested. They are randomly distributed within the data collection unit. In this case, at the largest scale, the unit is the census block group, and randomly distributing the points means that some points fall “inside” the water polygons.
Helping your colleagues, clients, students, or some other audience you are working with understand concepts such as these may seem insignificant but is an important part of map and data interpretation. It can help them to better understand the web maps that we encounter on a daily basis. It can help people understand issues and phenomena, and better enable them to think critically and spatially. Issues of data collection, quality, and the geographic unit by which the data was collected–all of these matter. What other examples could you use from GIS and/or web based maps such as these?
The Marine Cadastre Data Viewer and Portal provides direct access to authoritative marine cadastral data from U.S. federal and state sources, including information on the tracks of vessels, bathymetry, administrative boundaries, and fish, bird, and other species. It provides baseline information needed for ocean planning efforts, particularly those that involve finding the best location for renewable energy projects. The MarineCadastre.gov National Viewer uses Esri web GIS technology and is also a helpful tool in the permit review process. Users can select the ocean geography of their choosing and quickly see the applicable jurisdictional boundaries, restricted areas, laws, critical habitat locations, and other important features. With the national viewer, potential conflicts can be identified and avoided early in the planning process.
The site offers two distinct advantages: 1) The ability to view over 75 data layers from a variety of sources in a single live ArcGIS Online-based web map viewer; 2) The ability to download those same layers from the map interface for additional analysis. We have been critical in this blog about sites that get the user tantalizingly close to downloading the data but never quite allow it. This one delivers. The only thing I have not been able to get to work during my review of the resource is the buffer tool.
See this site for additional information about the data layers and services. In addition, you can explore the set of layers on ArcGIS Online in the Marine Cadastre group.
A new web resource from Texas Tech University of playas and wetlands for the southern High Plains region of Texas, Oklahoma and New Mexico offers a wide variety of spatial data on this key resource and region. The playa and wetlands GIS data are available for download here, including shapefile, geodatabase, and layer package formats. The data include 64,726 wetland features, of which 21,893 are identified as playas and another 14,455 as unclassified wetlands; in other words, they appear to be a playa but have no evidence of a hydric soil. The remaining features include impoundments, riparian features lakes, and other wetlands.
As we discuss in our book, (1) Many spatial data depositories seem to have been created without the GIS user in mind. Not this one. Careful attention has been paid to the data analyst. That’s good news! (2) Resources such as this don’t appear without a great deal of time and expertise invested. Here, approximately 5,000 person hours were dedicated to create the geodatabase and website. This project was made possible by Texas Tech University with funding from the USDA Agricultural Research Service – Ogallala Aquifer Program.
For users who only wish to view playas and other wetlands, a web map application exists and can be launched via the playa viewer. A “citizen science” feature is that the map viewer allows interactive comments to be added to the map for future consideration.
Southern Ogallala Aquifer Playa and Wetlands Geodatabase.
An global but very detailed map set of world water stress and risks has recently been released by the World Resources Institute (WRI): http://aqueduct.wri.org/atlas.
The map is associated with a great deal of data in the associated “dashboard.” This “Aqueduct” data combines 12 water risk indicators to create maps of where and how water risks may be prevalent. An added bonus is that users can adjust the weights used in assessing risk. The source data is available as a downloadable Esri geodatabase. Users can also upload locations for study, and export the results to Excel. After spending time with these data sets and maps, I found them to be easily accessible and usable both online and downloaded and used in a desktop GIS.
An article describing the map and data and the reasons behind creating them:
This is an important and much-needed resource. How might you use it in your own work?