Glacier Bay National Park and Preserve - Mapping Coastal Resources at Glacier Bay (U.S. National Park Service)

Introduction
The 1989 Exxon Valdez oil spill (EVOS) demonstrated that accurate baseline information about existing coastal resources is crucial to managing the response, cleanup, and restoration of a major environmental disaster. One of the most important lessons that emerged from the EVOS experience is that an ongoing resources inventory and monitoring program is an absolute necessity for preparing ourselves for such "unscheduled events" as well as for general resource protection. Other activities taking place in coastal areas may also have effects on the environment that are less spectacular than a major spill but just as profound in the long run. Managers must understand what resources exist in a given area as well as their ranges of natural variation (both spatial and temporal) if they are to protect them from human-caused change.

A coastal resources inventory is one basic component of any program to protect Alaska's miles of pristine coastline. Yet until now, no readily useable coastal mapping protocol has existed. After evaluating the needs of Alaskan parks, resource managers in the region determined that any coastal mapping effort had to be accurate, flexible, and repeatable. It also had to be affordable for parks that do not have the means to acquire expensive mapping expertise. The result has been the development at Glacier Bay National Park of a coastal resources inventory and mapping protocol designed for coastal parks in Alaska. This protocol and its resulting GIS (Geographic Information System) layers can be used by coastal parks throughout the nation to collect, analyze, and display biological and physical shoreline data.

The Alaska Coastal Resources Inventory and Mapping Protocol provides coastal inventory information to resource managers to assist decision-making on issues such as:

Evaluation and response to natural vs. anthropogenic change;
Response to large environmental disasters such as oil spills;
Protection of sensitive natural resources;
Identification and preservation of archaeological and cultural resources;
Design and selection of a companion long-term monitoring protocol and sampling sites.

This protocol provides a level of information more detailed than NOAA's Environmental Sensitivity Index but less detailed than a typical monitoring project.

An article on this coastal inventory and mapping protocol appeared in the National Park Service's Natural Resource Year in Review--1997 (Yerxa 1998) with a mapping program update appearing in the 2002 issue (Vanselow 2003).

Field Work
The field inventory is performed by two-person teams walking the shore during low-tide "windows" and delineating polygons based on areas of similar surface beach substrate. Wet, rainy, rugged field conditions demand that data collection techniques be simple and reliable. Field crews map the coast by delineating segments as polygons on aerial photographs. Polygons are drawn directly onto 200% enlargement plastic photocopies of 1:24,000 color infra-red photos. Additional field data is recorded onto plastic paper data sheets.

For each polygon, field data collected includes:

Surface substrate characterization;
A four-minute timed biological inventory of key intertidal flora and fauna;
A transect from the water’s edge to the woody vegetation to document vertical zonation patterns;
A quick stream inventory designed to capture major stream characteristics;
Three documenting photographs - one looking up from the water’s edge toward the woody vegetation, and two taken looking left and right (down the beach) from mid-beach;
Presence/absence of a variety of special-interest resource attributes such as archeological sites, offshore reefs, kelp beds, clam habitat, urchin recruitment areas, tidepools, seabird colonies, and pinniped haulouts.

Global Positioning System (GPS) control points are collected in the field and used to georeference aerial photos.

Data Processing
The data processing portion of the protocol provides a complete guide to processing inventory data, ground photos, and GPS points as well as for georeferencing aerial photos. The protocol is designed to enable technicians to complete all data entry and data processing by the end of the field season.

Aerial photos are georeferenced using ArcView™ with the Image Analysis Extension™. Polygons are heads-up digitized with the georeferenced aerial photos as a background in ArcView™.

The inventory produces thousands of ground photos. The organization method, database design, and processing protocol provide an efficient and quick means of dealing with these images. All images are stored external to the database. By linking images into the database rather than storing them within the database, gigabytes of images are available but do not affect database performance.

Field data is stored in a Microsoft Access™ relational database and is linked to the ArcView™ polygon shapefile via a single key field.

The Coastal Database contains graphs of transect data, ground photos, locator maps and queries to summarize data. Ground photos and georeferenced aerial photos are stored external to the database but are displayed in the database as each polygon is displayed. In this way the database can provide very rapid spatial access to gigabytes of image data.

The Data Kiosk - Getting the Data to the Manager
From any computer on the park's network, managers can quickly and easily pull up the database, view maps of the coast embedded in database forms, zoom to selected polygons, and view data, photographs, and hyperlinked descriptions of data fields. Over 960 miles of intertidal coast have been mapped in Glacier Bay National Park using this protocol, resulting in over 6,000 beach polygons with over 21,000 ground photos. In addition to this, the relatively short coastlines of Klondike Gold Rush and Sitka National Historical Parks have also been mapped. The methodology is relatively simple and low-tech. It was developed to work under rugged field conditions. It is easily adapted and could be used to inventory coastal resources in many other settings around the world. The information is available in a manager-friendly data kiosk format that utilizes MapObjectsLt2™ locator maps embedded into a Microsoft Access™ form. The georeferenced aerial photos are viewable in the MapObjectsLt2™ locator maps in the database. The data kiosk (click to open example in new window) provides a unique, simple method of presenting data with visual keys - maps, images, graphs, and hyperlinks - to explanatory text and diagrams.

Locator maps provide simple access to all the data, aerial photos and ground photos.
Low resolution thumbnails across the top of the data viewer provide a continuous visual context to the tabular and graphic data. The thumbnails are linked to high resolution versions of the images.
Graphs simplify complex tabular data.
Background information supplements the data.
Hyperlinks provide instant access to the methods and example photos.

Conclusion
The data collection methods and data processing methods described here provide a simple yet effective means of collecting valuable coastal data using relatively simple technology. The methodology is adaptable and could find use in many countries around the world. The database provides managers with very quick, easy access to hundreds of miles of coastal data and gigabytes of coastal images.

The complete protocols describing how to conduct the work and process the GIS and field data will soon be available on DVD. For more information contact: e-mail us

Acknowledgements
A host of individuals has contributed to the conception, design, and implementation of this protocol. Key among them is Carl Schoch of the Prince William Sound Oil Spill Recovery Institute, who generously shared his experience in developing similar protocols focusing on physical features of coasts elsewhere. Some of the key elements and approaches here have been adapted from his work. Bill Eichenlaub, GIS Specialist at Glacier Bay National Park and Preserve, was very instrumental in the design and development of the end product tool (the interactive computer interface). Coastal mapping team members during the life of this project have each contributed: Lewis Sharman, Bill Eichenlaub, Dan Van Leeuwen, Scott Croll, Scott Grover, Gary Lenhart, Gayle Neufeld, Paul Hillman, Alyssa Reischauer, Sean Bohac, Liza Graham, Michelle Anderson, Jenni Burr, Phoebe Vanselow, Cynthia Malleck, Tim Troccoli, Whitney Rapp, and Bonnie Harris.

Selected References
National Oceanic and Atmospheric Administration (NOAA). 1999. Introduction to the ESI Project. Office of Response and Restoration, National Ocean Service, National Oceanic and Atmospheric Administration. At: http://response.restoration.noaa.gov/

National Park Service (NPS). 2003. Inventory and Monitoring Home Page. National Park Service, U.S. Department of the Interior. At: http://science.nature.nps.gov/im/

Schoch, G.C. 1994. Geomorphological shoreline classification and habitat sensitivity analysis for Katmai National Park and Preserve, Alaska. Proceedings: The Coastal Society, Charleston, SC, 4 pp.

Schoch, G.C. and M.N. Dethier. 1996. Scaling up: the statistical linkage between organismal abundance and geomorphology on rocky intertidal shorelines. Journal of Experimental Marine Biology and Ecology, 201:37-72.

Schoch, G.C. 1996. The classification of nearshore habitats: a spatial distribution model. M.S. Thesis, Oregon State University, Corvallis, OR.

Vanselow, Phoebe. 2003. Inventory and mapping of coastal resources in Glacier Bay National Park. Natural Resource Year in Review-2002. National Park Service, U.S. Department of the Interior (publication D-2283) and at: http://www2.nature.nps.gov/YearInReview/yir2002/05_J.html

Yerxa, Rusty. 1998. Mapping Alaska's coastline. Natural Resource Year in Review-1997. National Park Service, U.S. Department of the Interior (publication D-1247) and at: http://www2.nature.nps.gov/YearInReview/yr_rvw97/chapter02/chapter02_a01.html

Zacharias, M.A., M.C. Morris and D.E. Howes. 1999. Large scale characterization of intertidal communities using a predictive model. Journal of Experimental Marine Biology and Ecology, 239:223-242.