Dana Peterson
Academic degrees
M.A., Geography, University of Kansas, 1999
B.G.S., Environmental Studies, University of Kansas, 1996
Program affiliation
Kansas Applied Remote Sensing
Areas of specialization
Land use/land cover mapping of crop types, grassland types, wetlands and woody encroachment using:
- object-based image analysis (OBIA);
- data fusion;
- hierarchical classifications using multi-temporal and multi-resolution data,
- using a variety of remotely-sensed data (MODIS NDVI time-series, Landsat, NAIP aerial imagery, LiDAR –derived products) and other geospatial datasets.
Skills include:
- managing large-scale (e.g. statewide) land cover mapping projects;
- geospatial analysis;
- enterprise GIS database development.
Courses taught
Geog 526: Remote Sensing of Environment I, Lab Instructor
Geog 658: Object-Based Image Analysis, Co-Instructor
Research interests
Mapping difficult-to-map landscape features using a data fusion approach (software: See5, eCognition, ERDAS Imagine, ArcGIS, ArcSDE, SQL)
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Peterson, D., S. Egbert. 2010. KLCP2005 fact sheet.
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Peterson, D., J. Whistler, S. Egbert, E. A. Martinko. 2010. 2005 Kansas Land Cover Patterns: Phase II--final report. Kansas Biological Survey, Lawrence, KS Report No. 167:49 pp.
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Peterson, D.L., J.L.Whistler, S.L. Egbert, E.A. Martinko, E.A. 2010. 2005 Kansas land cover patterns: Phase II Final Report. Open-File Report 167. Kansas Biological Survey, Lawrence, KS, 49 pp.
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Peterson, D., J. Whistler, C. Bishop, S. Egbert, E. A. Martinko. 2009. The Kansas next-generation land use/land cover mapping initiative. Proceedings, American Society for Photogrammetry and Remote Sensing 12 pp.
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Martinko, E. A., S. Egbert, M. Jakubauskas, K. Dobbs, J. Lomas, J. Whistler, D. Peterson. 2008. 2005 Kansas Land Cover Patterns Phase I--final report. Kansas Biological Survey, Lawrence, KS Open-file Report No. 150.
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Cully, J.F., K.M. McNyset, S. Egbert, D. Peterson, J.C. Kostelnick. 2007. Ecological niche modeling of black-tailed prairie dog habitats in Kansas using geographic information systems (GIS), remote sensing, and the Genetic Algorithm for Rule-set Prediction (GARP). Transactions of the Kansas Academy of Science 110(3/4):187-200.
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Martinko, E. A., J. Whistler, D. Peterson, J. Kastens, R. Hagen, D. Huggins, M. Jakubauskas. 2007. A watershed classification system for tiered diagnosis of biological impairments: A scalable, Central Plains focus with national applicability: Final report to the U.S. Environmental Protection Agency STAR Program. Kansas Biological Survey, Lawrence, KS Report No. 141:153 pp.
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Jakubauskas, M., D. Peterson, S. Campbell, S. Campbell, D. Penny, J. deNoyelles. 2003. Remote sensing of invasive aquatic plant obstruction in navigable waterways. U.S. Department of Transportation Research and Special Programs Administration 30 pp.