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Research and Development in the National Mapping Division, USGS Trends and Prospects (1991) / Chapter Skim
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3 Research Opportunities
Pages 25-37

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From page 25...
... Still other needs or desires require innovative R&D to extend data handling and modelir g capabilities. Although some results are several years away from the marketplace, the private sector has demonstrated its rapidity to incorporate new spatial data handling advances into commercial products.
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From page 26...
... From this analysis, it is apparent that the needs for research on spatial data handling and analysis are driven by applications and decisionmakers who use the resultant information. The remainder of this chapter attempts to identify an appropriate role for NMD in addressing the research agenda of the nation's spatial data user community.
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From page 27...
... TECHNICAL CONCERNS Data Base Development · Lower data capture costs through improvements in scanning technology and better utilization of remotely sensed data, especially through incorporation of artificial intelligence techniques.
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From page 28...
... Make GIS software accessible to users with different levels of technical expertise through the use of artificial intelligence, help screens, relational data bases, and software layering. Analyze the needs of planners and other public officials, see what potential applications they have for this technology, and develop specifications for products to meet those needs.
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From page 29...
... 9. Institutions Sharing Spatial Information: Explore existing policies, problems, and prospects for sharing data; develop models of political support for sharing.
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From page 30...
... Existing thematic data products such as land-use and land-cover data sets produced by the USGS are at least 10 years old. To develop an intermediate-scale thematic mapping program based on current data, NMD will need to consider new data sources, innovative digital mapping techniques, state-of-the-art image processing techniques, automated cartography, advanced change detection algorithms, and automated procedures for assessing the accuracy of specific thematic data.
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From page 31...
... documenting characteristic scales of spatial and temporal changes in various environments for basic social, natural, and applied sciences processes, (2) developing a taxonomy of space-time statistical models to help select appropriate data base structures for representing temporal variability of specific social and natural processes,
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From page 32...
... Because future NMD data users would like to access seamless and scale-independent digital data bases, research on multiple representations is important. This research could focus on, for example: (1)
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From page 33...
... identify formal cognitive/semantic models of spatial concepts/relationships in natural languages, (2) develop advanced methods for determining reference frames for spatial languages, (3)
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From page 34...
... In addition to maintaining and distributing data products, NMD also needs to keep abreast of changes in the analytical capabilities of automated systems. Commercially available spatial analysis tools today probably fall short of the needs (as expressed in the URISA research agendas; see Table 8)
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From page 35...
... the investigation of map/ image scanning technologies for effective capture of map linework and/or continuous tone images, (7) the development of methods for effectively structuring spatial search algorithms within a GIS framework, (8)
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From page 36...
... In addition, other significant research topics include: (1) developing techniques for near-real time indexing and browsing of map and image data of important Earth surface features (e.g., vegetation greenness, biomass, and albedo)
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From page 37...
... 37 environments is critical. A robust national mapping infrastructure is vital to achieving this goal.
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Key Terms

  • data products
  • sensed data
  • remotely sensed
  • spatial information
  • thematic data

  • decision support
  • digital data
  • statistical models
  • data handling
  • gis data

  • artificial intelligence
  • geographic features
  • base structures
  • image processing
  • nmd data

  • multiple representations
  • data structures
  • urisa research
  • gis software
  • spatial decision

  • implementing methods
  • user community
  • change research
  • software layering
  • software accessible

  • indirect benefits
  • appropriate data
  • image scanning
  • data aggregation
  • data capture


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