government of obtaining and maintaining data and information for decision making, and it means that the local governments within Metro that are working on land use policy can concern themselves with specific issues rather than arguing about data sources or quality. One official said that in Portland Metro, data management is not a technical issue; it is about relationships.

The Portland Metro effort is complicated by the difficulties the local weather creates for obtaining remotely sensed images of the area. Because of frequent rainfall in the area, it is often difficult to obtain cloud-free remote sensing images. Moreover, aerial photography is generally obtained in July and August, when the trees are in full leaf, making it difficult to use the images to observe aspects of the built environment like the transportation infrastructure or utilities.

Cost was identified as the most significant constraint to using satellite remote sensing in the Portland metropolitan area. Metro officials would like to use high-resolution, multispectral commercial imagery because it gives significantly more information than aerial photography,¹⁰ but the satellite data are considerably more expensive. Metro officials hope that by pooling their resources and data needs across the region, it will be possible in the future to obtain the high-resolution data they need.

In the spring of 1997, as the record snowfall of the winter of 1996-1997 began to melt and the waters ran north toward areas where the ice and snow were just beginning to melt, the Red River flooded its basin along the North Dakota-Minnesota boundary. The floods were the worst on record, inundating farms and communities in the Red River Valley and forcing over 100,000 people to evacuate their homes. The flood blocked regional transportation routes, disabled power systems, and disrupted water and sewage systems. After the floodwaters receded, estimates of damages were between $1 billion and $2 billion.¹¹

Standard USGS topographic maps are used to forecast floods by providing estimates of crests on the rivers of the Red River Valley. Changes of only a few feet in the flat topography of the Great Plains can be significant in terms of flooding, but these changes cannot be discerned on USGS maps, which provide

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)