In a recent article published in the ISPRS International Journal of Geo-Information, Quality Evaluation of VGI Using Authoritative Data—A Comparison with Land Use Data in Southern Germany, the authors investigated some of the concerns regarding data quality and data usability often levelled at Volunteered Geographic Information (VGI) data sources.
The objective of the study, based in the Rhine-Neckar region of southern Germany, was to compare OSM data to the authoritative land use and land cover (LULC) data set ATKIS Base DLM version 6.0. published by the LGL mapping agency (Baden-Württemberg State Office for Geoinformation and State development).
The results for the OSM data completeness and correctness comparison were variable across the different classes of land use in the study area. However some general trends emerged including:
- Areas with a high percentage of forest cover were the areas with the highest level of completeness and correctness.
- Other classes (incl. farmland and urban areas) had low levels of completeness but higher levels of correctness; features present were mapped accurately but some features were missing.
- Other areas (incl. quarry and lakes) had high levels of completeness (most features mapped) but had a greater percentage of incorrectly mapped features.
- There was a marked difference between rural and urban areas; the study identified higher OSM coverage and thematic accuracy in densely populated areas (more people available/interested in collecting the data?).
- Some land use classes demonstrated both high levels of completeness and correctness, suggesting they had been mapped for a specific purpose.
Although not intended as a definitive statement of OSM data quality, the study suggested that if full coverage and accurate LULC data was a requirement for a project, then OSM data (at present) may not be the best option. However for certain land use classes, where the LULC information was available it was mostly correct so depending on project requirements OSM data may be a suitable alternative.
As we’ve said many times before on Spatial Reserves, it is not whether the data are good, but rather if they are good enough to meet your requirements.
Dorn, H.,Törnros, T. and Zipf, A. (2015). Quality Evaluation of VGI Using Authoritative Data—A Comparison with Land Use Data in Southern Germany. ISPRS Int. J. Geo-Inf. 4, pp. 1657 – 1670
A few years ago, I walked on the pier at Manitowoc, Wisconsin, and after mapping my route, reflected on issues of resolution and scale in this blog. After recording my track on my smartphone in an application called RunKeeper, it appeared on the map as though I had been walking on the water! This, of course, was because the basemap did not show the pier or the fill adjacent to the marina. Recently, following the annual meeting of the Association of American Geographers, I had the opportunity to retrace my steps and revisit my field site. What has changed in the past 2 1/2 years? Much.
As shown below, the basemap used by RunKeeper has vastly improved in that short amount of time. The pier and fill is now on the map, and note the other differences between the new map and the one from 2012 below that appears below it–schools, trails, contour lines, and other features are now available. A 3-D profile is available now as well. Why? The continued improvement of maps and geospatial data from local, regional, federal, and international government agencies plays a role. We have a plethora of data sources to choose from, as is evident in our recent post about Dr Karen Payne’s list of geospatial data and the development of Esri’s Living Atlas of the World. The variety and resolution of base maps in ArcGIS Online and in other platforms continues to expand and improve at an rapid pace.
Equally significant, and some might argue more significant, is the role that crowdsourcing is having on the improvement of maps and services (such as traffic and weather feeds). In fact, even in this example, note the “improve this map” text that appears in the lower right of the map, allowing everyday fitness app users the ability to submit changes that will be reviewed and added to RunKeeper’s basemap. What does all of this mean for the the data user and GIS analyst? Maps are improving at a dizzying pace due to efforts by government agencies, nonprofit organizations, academia, private companies, and the ordinary citizen. Yet, scale and resolution still matter. Critically thinking about data and where it comes from still matters. Fieldwork that uses ordinary apps can serve as an effective instructional technique. It is indeed an exciting time to be in the field of geotechnologies.
The map from 2012 is below.
The advent of crowd-sourcing and volunteered geographic information (VGI), facilitated by easy access to relatively cheap, GPS-enabled devices and cloud-based mapping services, have transformed our ability to record and respond to natural and man-made hazards and emergencies. VGI can provide an invaluable local commentary on rapidly changing situations that would otherwise be bereft of real-time, detailed observation.
This VGI resource is also increasingly valued in the documentation of more insidious regional and global phenomenon such as climate change. The high cost of traditional scientific data capture and the lack of a consistent, regional overview prompted a re-think of how such information should be captured. The pan-European research Citizen Observatory Web (COBWEB) project, launched at the end of 2012 and due to be released in 2016, aims to develop an observation framework to support the collection of crowd-sourced environmental data throughout Europe. The emerging COBWEB infrastructure is set to be trialled in study areas that come under the UNESCO World Network of Biosphere reserves (WNBR). The COBWEB consortium (made up of 13 European organisations) hopes the motivation to retain the unique characteristics of the biosphere reserves will encourage local citizens to become involved in monitoring the local environment.
To address some of the inherent problems with VGI – data quality, interoperability and validation – COBWEB will integrate the crowd-sourced observations with authoritative reference data published by public authorities under the INSPIRE directive, from compliant spatial data infrastructures (SDI) and the Global Earth Organisation System of Sensors (GEOSS). If these integrated data sources are accepted as a reliable source of information to support further research and as a basis for policy making, this will be significant a achievement for COBWEB. Another major challenge for the project is to develop a workable accessibility framework for the data sources, which will combine publicly available crowd-sourced data with information from more restricted sources.