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In cooperation with the Michigan Army National Guard’s Fort Custer Training Center, Battle Creek, Michigan

Scientific Investigations Report 2006–5051

Wetland Delineation with IKONOS High-Resolution Satellite Imagery, Fort Custer Training Center, Battle Creek, Michigan, 2005

By L.M. Fuller, T.R. Morgan, and S.S. Aichele

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Abstract

The Michigan Army National Guard’s Fort Custer Training Center (FCTC) in Battle Creek, Mich., has the responsibility to protect wetland resources on the training grounds while providing training opportunities, and for future development planning at the facility. The National Wetlands Inventory (NWI) data have been the primary wetland-boundary resource, but a check on scale and accuracy of the wetland boundary information for the Fort Custer Training Center was needed. In cooperation with the FCTC, the U.S. Geological Survey (USGS) used an early spring IKONOS pan-sharpened satellite image to delineate the wetlands and create a more accurate wetland map for the FCTC. The USGS tested automated approaches (supervised and unsupervised classifications) to identify the wetland areas from the IKONOS satellite image, but the automated approaches alone did not yield accurate results. To ensure accurate wetland boundaries, the final wetland map was manually digitized on the basis of the automated supervised and unsupervised classifications, in combination with NWI data, field verifications, and visual interpretation of the IKONOS satellite image. The final wetland areas digitized from the IKONOS satellite imagery were similar to those in NWI; however, the wetland boundaries differed in some areas, a few wetlands mapped on the NWI were determined not to be wetlands from the IKONOS image and field verification, and additional previously unmapped wetlands not recognized by the NWI were identified from the IKONOS image.

 


Citation:

Fuller, L.M., Morgan T.R., and Aichele, S.S., 2006, Wetland Delineation with IKONOS High-Resolution Satellite Imagery, Fort Custer Training Center, Battle Creek, Michigan, Date Posted: March 3, 2006, 2005: U.S. Geological Survey, Scientific Investigations Report 2006-5051, 8 p.
[https://pubs.water.usgs.gov/SIR2006–5051]

Contents

Abstract

Introduction

Study Area

Background

Materials and Methods

IKONOS Satellite Imagery

Training Sites

Automated Techniques

Supervised Classification

Unsupervised Classification

Separation of Land-Cover Classes

Manual Digitizing

Verification Process

Effectiveness of Wetland-Delineation Approaches

Summary and Conclusions

Acknowledgments

References Cited

Figures

1-4. Maps showing:

1. Fort Custer Training Center in Battle Creek, Michigan, shown with an April 25, 2005, IKONOS satellite image

2. National Wetlands Inventory wetlands shown with an IKONOS April 25, 2005, satellite image of the Fort Custer Training Center in Battle Creek, Michigan

3. View of the northeast part of Fort Custer Training Center in which the National Wetlands Inventory data are compared to the new digitized wetland map from the IKONOS April 25, 2005, satellite image

4. Wetlands mapped from IKONOS satellite imagery April 25, 2005, surrounded by a 200-meter buffer, Fort Custer Training Center, Battle Creek, Michigan

References

Antunes, A.Z.B., Lingnau, C., and Da Silva, J.C., 2003, Object-oriented analysis and semantic network for high resolution image classification: Anais XI SBSR, Belo Horizonte, Brasil, v. 9, no. 2, p. 273–279.

Cowardin, L.M, Carter, Virginia, Golet, F.C., and LaRoe, E.T., 1979, Classification of wetlands and deepwater habitats of the United States: Washington, D.C., U.S. Fish and Wildlife Service, Office of Biological Services, FWS/OBS–79/31, 131 p.

Ernst-Dottavio, C.L., Hoffer, R.M., and Mroczynski, R.P., 1981, Spectral characteristics of wetland habitats: Photogrammetric Engineering and Remote Sensing, v. 47, no. 2, p. 223–227.

ESRI, 2004, ArcGIS 9.0, Using ArcMap: Redlands, Calif., 585 p. [Additional information at http://www.esri.com/]

Hodgson, M.E., Jensen, J.R., Halkard, E.M., and Malcolm, C.C., 1987, Remote sensing of wetland habitat–A wood stork example: Photogrammetric Engineering and Remote Sensing, v. 53, no. 8, p. 1075–1080.

Jensen, J., Christensen, E., and Sharitz, R., 1984, Nontidal wetland mapping in South Carolina using airborne multispectral scanner data: Remote Sensing of the Environment, v. 16, p. 1–12.

Jensen, J.R., Ramsey, E.W., Mackey, H.E., Christensen, E.J., and Shairtz, R.R., 1987, Inland wetland change detection using aircraft MSS data: Photogrammetric Engineering and Remote Sensing, v. 53, no. 5, p. 521–529

Leica Geosystems, 1999, Erdas Imagine 8.5, ERDAS Field Guide (5th edition): Atlanta, Georg., 698 p. [Additional information at http://gis.leica-geosystems.com/]

Lillesand, T.M., and Kiefer, R.W., 2000, Remote sensing and image interpretation (4th edition): New York, John Wiley and Sons, p. 534–561.

Lunetta, R.S., and Balogh, M.E., 1999, Application of multi-temporal Landsat 5 TM imagery for wetland identification: Photogrammetric Engineering and Remote Sensing, v. 65, no. 11, p. 1303–1310.

Olmanson, L.G., Bauer, M.E., and Brezonik, P.L., 2002, Aquatic vegetation surveys using high-resolution IKONOS imagery: American Society for Photogrammetry & Remote Sensing Future Intelligent Earth Observing Satellites Conference Proceedings.

U.S. Fish and Wildlife Service, 2004, National Wetlands Inventory polygon data (accessed October, 2004 at http://wetlands.fws.gov/mapper_tool.htm)


For further information, contact:

 

U.S. Geological Survey

Michigan Water Science Center

6520 Mercantile Way, Suite 5

Lansing, MI 48911-5991

mi_dc@usgs.gov

 

or visit our Web site at:

 

http://mi.water.usgs.gov



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