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Effective environmental management requires an accurate inventory of the resources to be managed. Decision makers often lack the technical expertise necessary to understand the limitations of environmental data. The State of North Carolina is re-surveying elevations using Light Detection and Ranging to re-delineate floodplains. These data allow analysts to predict flood inundation extents of design storms in order to better manage flood-prone terrain. Conversely, many environmental management functions in North Carolina, such as calculating stream length for hydrologic modeling and riparian buffer protection, rely upon outdated paper maps such as the USGS topographic map series for the determination of the location of stream "blue lines". These cartographic products are inadequate for use in headwater stream mapping when compared to field observations yet no better data source has been found to achieve the accuracy needed for local site planning. This research evaluated the horizontal accuracy and completeness of currently available stream maps compared to stream networks derived from DEMs obtained from the USGS, the North Carolina Floodplain Mapping Program, and interpolated from LiDAR bare-earth elevation points. A unique system combining software and hardware was developed to map headwater catchments with global positioning systems and was used to perform field data collection at nine catchments distributed across four physiographic regions. A method of determining the horizontal accuracy of stream lines shown on maps was developed and used to show that stream networks delineated using high-resolution, interpolated DEMs are more accurately positioned than those on previously published maps or stream networks delineated from currently available DEMs.

The National Park Service (NPS) maintains and supports various databases relevant to its mission. These include archeological sites, cultural objects, and exotic species inventories, to name a few. Data associated with each of these domains forms the basis on which NPS policy is formulated. However these databases often exist in independently maintained systems, often at different locations. Additionally these domains often contain spatial data in which data objects can possess spatial characteristics and location information. Currently most National Park Service non spatial attribute databases (e.g. ASMIS, CLAIMS, FMSS, and LCS) are centralized at regional or national headquarters, whereas most spatial information is generally created and maintained at the park. It is left to the data user to connect to these data entities, and this is at best cumbersome and at times, impossible. This project is a feasibility study that analyzes the use of GIS to integrate of park service attribute databases with locally collected park spatial data. The core procedure focuses on the application of computer aided software engineering tools to National Park Service GIS database design. This includes modeling database relationships and generating the database schema. The resultant prototype database was tested in two National Parks, Valley Forge National Historic Park and Appomattox Court House National Historic Park. In both instances, locally generated spatial data were imported successfully into a standardized ESRI geodatabase and integrated with other enterprise, non local data through the use of reusable objects.