TopoView Database of Historic USGS Topographic Maps Online

Ever since those years I worked at the US Geological Survey, I have been hoping that the thousands of USGS historical topographic maps would someday be easily accessible for the geospatial data user.  These maps, representing an enormous investment in documenting the landscape at great detail, were compiled over nearly a 100 year period.  TopoView has just been launched that provides this type of service:   http://ngmdb.usgs.gov/maps/TopoView/.

1962 Topographic Map at 1:24,000-scale of Grand Junction, Colorado, from the TopoView database.

TopoView is intended to serve the immediate need for the older printed topographic maps to become easily searched, viewed, and downloaded.  The approximately 163,000 maps at different scales including 1:24,000, 1:48,000, 1:63,360, 1:100,000, 1:250,000, and a few others, available through this interface were scanned by the USGS Historical Topographic Mapping Collection project.   They are provided in GeoPDF and in JPG formats.   Users can use the map index interface to access a chosen location, and then browse all of the maps, scales, and formats available for that location.

Currently, the interface is best for viewing and downloading one map at a time, and the Flash interface may hinder users working on the Mac platform.  This  index does not include all historical USGS maps.  I would like to see these maps in formats that are  easier for the GIS community to use.  I also would like to see all of these maps offered as a seamless service in ArcGIS Online.

Nevertheless, I recognize that this is only the first draft of this interface and it still represents a huge leap forward.  It is a wonderful resource for comparing past to present agricultural and urban land use changes, coastal processes, changes in glaciers, the movement of and channelization of rivers, and so much more.

Partnerships for spatial data provision

In The GIS Guide to Public Domain Data one of the topics discussed is the increasing role partnerships have to play in the provision of new spatial data. Whether collaborating to work towards a common goal, share resources or help promote and distribute data, many public, private, academic, non-governmental organisations and individuals, have been combining effectively in recent years to collect, collate and disseminate spatial data. Two examples of successful collaboration include OpenStreetMap and Google Earth.

The advent of internet-based spatial data collection and distribution has revolutionised how we access and work with spatial data. It has also altered what we expect from spatial data providers and some have questioned the traditional role of national mapping organisations (NMOs). Bhanu, writing in Geospatial World, commented recently on the proliferation of the personal geospatial data market and the forecast global revenues for spatial data related services (geoservices). In her article, Should governments continue to invest in national mapping organisations?, she considers who will be best placed to deliver these geoservices and wonders if NMOs operating the traditional ‘topographic map’ delivery model are still best placed to meet the demand.

With the increasing availability of a range of spatial data products, end users are no longer constrained to use a single data provider and NMOs must adapt to survive. Whether that adaptation is through partnership with other organisations or privatisation remains to be seen.

Geospatial Data for Marine Protected Areas

Scientific attention to the oceans has been gaining strength over the past few years and with it a recognized need for  expanding the spatial data covering the oceans.  A few organizations are leading the way in providing these resources.  For example, registering on this website allows access to the World Database on Protected Areas (WDPA), which includes all nationally designated (such as national parks and nature reserves) and internationally recognized protected areas (such as UNESCO World Heritage Sites, Ramsar Wetlands of International Importance, including protected areas in the oceans.  As another example, the Protected Planet site allows individual preserves to be downloaded as KMZ, CSV, and shapefiles.

More protected area data in the ocean exists now than ever before, but more is needed.  Photo by Joseph Kerski.

A global dataset of warm water coral reefs is maintained by the UNEP’s World Conservation Monitoring Centre, but as of this writing, their ArcGIS Online map link was broken and it was much easier on the site to find books rather than  spatial data.   I found the portal maintained by Reefbase to be much easier to use, including point data for monitoring sites, reef locations, and even coral diseases.  However, unfortunately, the data are only available in Excel or CSV formats:  Therefore, they need a bit of tinkering to get them into a GIS.

Despite the difficulties that some of these sites pose, the amount and variety of protected area spatial data for the oceans is growing.  And just in time, too, as it is needed now more than ever.

Free volcanic eruptions database published

The Volcano Global Risk Identification and Analysis Project (VOGRIPA) recently announced the release of the LaMEVE (Large Magnitude Explosive Volcanic Eruptions) database. VOGRIPA, a component of the Global Volcano Model international collaboration, aims to provide freely available, sustainable and accessible information on volcanic hazard and risk. The data has been contributed by a number of organisations, including the Smithsonian Institute and the Geological Survey of Japan, and contains information on nearly 3,000 volcanoes and more than 1,800 eruption records of magnitude four or greater, dating back to the start of the Quaternary period.

The eruptions database is publicly available on-line, hosted by the British Geological Survey, and may be queried using spatial and attributes tools.

The results may be downloaded in spreadsheet, csv or tab delimited file format.

The database has been developed to support research into global, regional and local patterns of volcanic activity to improve hazard assessment and risk analysis. The information provided should also useful for emergency response and crisis management teams in the event of an eruption.

Is your data “CRAAP”?

Is your data any good or is it “CRAAP”?  Assessing spatial data quality grows in importance as it grows in volume and diversity and as it becomes easier to access.  Research and development on metrics and standards to measure data quality took off during the mid-1990s, and thus there is no shortage of evaluation instruments to choose from.  Even so, it often is difficult to evaluate the quality of a data set you are considering using.

People in library science really understand data and their implications, and some of the metrics I find most useful come from the library and information science community.  My colleague Linda Zellmer, Government Information and Data Services Librarian at Western Illinois University, uses a “CRAAP” test, originally from CSU Chico and based on the CRAP test from LOEX.  This is a schema to evaluate information:  Currency, Relevance, Authority, Accuracy, and Purpose.   When I teach with or about GIS, to get across the point that assessing data quality ultimately depends on metadata, I frequently refer to the FGDC’s “top 10 metadata errors” document.  The document’s number one identified error is “not doing it!”:  ”If you think the cost of metadata production is too high, you haven’t compiled the costs of not creating metadata, including loss of information with staff changes, data redundancy, conflicts, liability, misapplications, and decisions based upon poorly documented data.”  Ouch!

Understanding your data.

One of my favorite papers examining measurement standards comes from Dr Jingfeng Xia of Indiana University, who, in his research published in Issues in Science and Technology Librarianship, proposed a set of dimensions for data quality measurement.  He discusses  measures such as accuracy, consistency, completeness, and integrity, but also accessibility, validity, timeliness, currency, conformance, uniqueness,  and others.  One of his main points is that both quantitative and qualitative metrics are essential for determining the quality of geospatial data.

As we point out in the book The GIS Guide to Public Domain Data, it is more important than ever before to document your data, and understand what you are using, because with each passing day it becomes easier to combine data from an amazing array of sources.  With opportunity comes responsibility!

Overhauling copyright

Interesting post last week from Greg Sandoval at The Verge on the subject of overhauling copyright legislation in the US. Maria Pallante, head of the US Copyright Office, is trying to convince Congress to review and revise current copyright legislation and in particular the Digital Millennium Copyright Act (DMCA), which was enacted to deal with Internet copyright issues.

Given that so many people now regularly access the Internet for all types of data and information, in ways not previously anticipated by the legislators such as via smartphones or by uploading user-generated content, copyright is an issue many Internet users run into on a daily basis, consciously or otherwise. Once again, it is another example of technological advances preceding a regulatory framework governing their use.

Copyright issues and the public domain are two of the major themes in The GIS Guide to Public Domain Data. Although vast amounts of spatial data are currently available via the Internet, just because the data are on-line that doesn’t mean to say they are free from copyright restrictions and in the public domain. Given the increasing focus from the US Copyright Office on illegal streaming and anti-piracy efforts, it is as important as ever to always check the terms and conditions for any copyright restrictions that may apply to spatial data, particularly if you intend to use the data for commercial purposes.

Geo-Wiki.org: Crowdsourcing to improve global land cover data

In our book The GIS Guide to Public Domain Data, we spend quite a bit of time discussing crowdsourcing, and rightly so:  Over the past few years, crowdsourcing has become a viable way not only to collect data, but also to verify and update existing data.  Reasons include budget constraints in those agencies that provide data and the subsequent need for field verification, a growing recognition that decisions based on spatial data are only as beneficial as the accuracy of the data sets themselves, the rapid expansion of citizen science, and growth in the number and variety of mobile and web-GIS tools that enable citizen scientists to contribute to the global community.

Examples of verifying and updating existing data are numerous, and a noteworthy one is from a group of researchers at the International Institute for Applied Systems Analysis (IIASA) in Austria who lead an effort to improve global land cover/land use data.   This effort, http://www.geo-wiki.org, verifies three land cover data sets, including GlobCover from the ESA, MODIS from NASA, and GLC 2000 from the IES Global Environment Monitoring Unit, through knowledge and photographs from people local to specific areas.

Geo-Wiki.org site.

Besides an improvement of the data and, it is hoped, in the decisions based on those data, some of these efforts feature innovative projects that provide benefit to local people.  For example, Geo-Wiki users were asked to identify the presence of cultivated land and settlements in samples in Ethiopia in a “hackathon” associated with USAID in an effort to improve local food security.

More information can be found on the Geo-Wiki site and in an article describing the project.