Local government planning, management, and operations provide fertile ground for new applications of remote sensing data and information. Because they are responsible for geographically small areas that often have high population densities, city and county governments generally require high-resolution spatial data for a number of purposes such as cadastral or mapping applications, identification of changes in land use, and maintenance of the transportation infrastructure. Although local governments relied on aerial photography for high-resolution data in the past, some are finding that satellite remote sensing data are now available at similar levels of spatial resolution with broader spectral coverage. Many city and county governments already have in-house GIS capabilities; data from satellite remote sensing, like data from some forms of airborne remote sensing, can be used in conjunction with digital data available in existing GIS databases. The possibility of integrating remote sensing data into local GIS databases and using the databases in conjunction with locational GPS data has created opportunities for new types of information applications that were not possible using photographic remote sensing data alone.

The city of Baltimore initially looked to remote sensing to obtain urban data for a state map of forested areas in Maryland and to update the city’s planimetric maps.¹ City planners had long depended on 19th- and early-20th-century maps for information on building and street locations in the city. In the 1980s and 1990s, as GIS software became easier to use, there were efforts in Baltimore to develop an integrated GIS, accessible to all agencies in Baltimore City, that would support planimetric map production and allow for GIS analysis. This effort was not initially successful. The early GIS products seemed crude next to the old-fashioned but artistically designed planimetric maps, and few people knew how to use GIS products for analysis. However, GIS offered the possibility of providing digital data for spatial analysis and decision making, as the static and inflexible planimetric maps, with their emphasis on fixed physical structures in the built environment, did not.

The city took its first steps into the world of remote sensing in order to obtain data for a map of vegetation cover. Maryland had acquired Landsat data to create a “greenprint” that identified the state’s larger forests. The state’s forest identification methodology, when combined with the resolution of the Landsat data, caused the urbanized areas of Baltimore City and Baltimore County to become blank spots on the state’s forest map. Because Baltimore had forested areas in its

Front Matter (R1-R14)

Executive Summary (1-7)

1. Introduction (8-15)

2. Public Sector Applications of Remote Sensing Data (16-37)

3. Getting Started in Remote Sensing: Common Barriers and Bottlenecks (38-49)

4. Beyond State and Local Government (50-61)

5. Findings and Recommendations (62-70)

Appendix A: Transforming Remote Sensing Data into Information and Applications, Executive Summary (71-78)

Appendix B: Biographical Information on Steering Committee Members, Workshop Speakers, and Panelists (79-89)

Appendix C: Workshop Agenda and Participants (90-95)

Appendix D: Acronyms (96-97)