Russell G. Congalton
Professor, Remote Sensing & Geographics Information Systems
My research interests are divided almost equally between basic research on spatial data uncertainty/map accuracy and applied research applying the tools of remote sensing, GIS, and spatial data analysis to solving natural resource problems. These projects have included deer and bear habitat mapping, endangered plant habitat analysis, mapping forest change, fire and fuels management, and eelgrass mapping, to name just a few. Currently, I am conducting both basic and applied research on land cover/vegetation mapping and validation of New England forest cover types in Pawtuckaway State Park, NH using various sources of remotely sensed data and different automated image processing methodologies. I have recently concluded a NSF-funded environmental science and education project called the GLOBE Program. I was the principal investigator of the Land Cover component (one quarter of the GLOBE Program) for over ten years. This research is international and involves developing scientific protocols and educational learning activities for GLOBE schools to perform land cover mapping and collect scientifically valid data. Over 25,000 schools in more than 100 countries participate in this program. While not funded to work with GLOBE currently, I am still very active in educational outreach to many of the colleagues I worked with during the GLOBE Project and am actively writing proposals to continue this work. Lastly, I am the Director of the New Hampshire View Program, a part of AmericaView, that is dedicated to promoting and enhancing the use of spatial data analysis and education throughout the US. Curriculum Vitae
- 1984 Ph.D. Remote Sensing & Forest Biometrics, Virginia Polytechnic Institute and State University
- 1981 M.S. Remote Sensing & Forest Biometrics, Virginia Polytechnic Institute and State University
- 1979 B.S. Natural Resource Management, Rutgers University
- NR 658: Introduction to Geographic Information Systems
- NR 757/857, GEOG 757: Remote Sensing of the Environment
- NR 759/859, GEOG 759: Digital Image Processing
- NR 760/860, GEOG 860: Geographic Information Systems
|M.S. Students||Alumni: 2005 - present||Year||Degree|
|Bob Champoux||Katie Jacques||2009||M.S.|
|Christina Czarnecki||Meghan Graham||2008||M.S.|
|Shawn Herrick||Brianna Heath||2008||M.S.|
|Alexis Rudko||Alastair Lough||2008||Ph.D.|
|Michael Campbell||Tina Cormier||2007||M.S.|
|Daniel Maynard (co-chair)||Jesse Bishop||2006||M.S.|
|Ph.D. Students||John Iiames||2006||Ph.D.|
|Meghan MacLean||Peter Tardie||2005||M.S.|
Mowrer, H. T. and R. G. Congalton. (eds.) 2000. Quantifying Spatial Uncertainty in Natural Resources: Theory and Applications for GIS and Remote Sensing. Ann Arbor Press, Chelsea, Michigan. 244p
Pugh, S. and R. Congalton. 2001. Applying spatial autocorrelation analysis to evaluate error in New England forest cover type maps derived from Landsat Thematic Mapper Data. Photogrammetric Engineering and Remote Sensing. Vol. 67, No. 5. pp. 613-620.
Congalton, R. 2001. Accuracy assessment and validation of remotely sensed and other spatial information. The International Journal of Wildland Fire. Vol 10. pp. 321-328.
Lunetta, R. J. Iiames, J. Knight, R. Congalton, and T. Mace. 2001. An assessment of reference data variability using a "virtual field reference database". Photogrammetric Engineering and Remote Sensing. Vol. 67, No. 6. pp. 707-715.
Pereira, V., R. Congalton, and D. Zarin. 2002. Spatial and temporal analysis of a tidal floodplain landscape – Amapa, Brazil using geographic information systems and remote sensing. Photogrammetric Engineering and Remote Sensing. Vol. 68, No. 5, pp. 463-472.
Wormstead, S., M. Becker, and R. Congalton. 2002. Tools for successful student-teacher-scientist partnerships: Lessons from GLOBE. Journal of Science Education and Technology. Vol. 11, No. 3. pp. 277-287.
Congalton, R., K. Birch, R. Jones, and J. Schriever. 2002. Evaluating remotely sensed techniques for mapping riparian vegetation. Computers and Electronics in Agriculture. Vol. 37. pp. 113-126.
Congalton, R. and L. Plourde. 2002. Quality Assurance and Accuracy Assessment of Information Derived from Remotely Sensed Data. IN: Manual of Geospatial Science and Technology. John Bossler. (Editor). Taylor & Francis, London. pp. 349-361.
Plourde, L. and R. Congalton. 2003. Sampling method and sample placement: How do they affect the accuracy of remotely sensed maps? Photogrammetric Engineering and Remote Sensing. Vol. 69, No. 3, pp. 289-297.
Thomas, N., C. Hendrix, and R. Congalton. 2003. A comparison of urban mapping methods using high-resolution digital imagery. Photogrammetric Engineering and Remote Sensing. Vol. 69, No. 9. pp. 963-972.
Bjerklie, D., S. Dingman., C. Vorosmarty, C. Bolster, and R. Congalton. 2003. Evaluating the potential for measuring river discharge from space. Journal of Hydrology. Vol. 278. pp. 17-38.
Congalton, R. 2004. Putting the map back in map accuracy assessment. A peer-reviewed chapter IN: Lunetta, R.S., and J.G. Lyon (Eds.), Remote Sensing and GIS Accuracy Assessment, CRC Press, Boca Raton, FL 304p.
Green, K and R. Congalton. 2004. An error matrix approach to fuzzy accuracy assessment: the NIMA Geocover project. A peer-reviewed chapter IN: Lunetta, R.S., and J.G. Lyon (Eds.), Remote Sensing and GIS Accuracy Assessment, CRC Press, Boca Raton, FL 304p.
Hermann, H., K. Babbitt, M. Baber, and R. Congalton. 2005. Effects of landscape characteristics on amphibian distribution in a forest-dominated landscape. Biological Conservation. Vol. 123. pp. 139-149.
Iiames, J., R. Congalton, A. Pilant, and T. Lewis. 2008. Leaf area index (LAI) change detection analysis on Loblolly Pine (Pinus taeda) following complete understory removal. Photogrammetric Engineering and Remote Sensing. Vol. 74. No. 11. pp. 1389-1400.
Iiames, J., R. Congalton, A. Pilant, and T. Lewis. 2008. Validation of an integrated estimation of Loblolly Pine (Pinus taeda L.) leaf area index (LAI) utilizing two indirect optical methods in the southeastern United States. Southern Journal of Applied Forestry Vol. 32. No. 3. pp 101 – 110.
Congalton, R. and K. Green. 2009. Assessing the Accuracy of Remotely Sensed Data: Principles and Practices. 2nd Edition. CRC/Taylor & Francis, Boca Raton, FL 183p.
Congalton, R. 2009. Accuracy Assessment of Spatial Data Sets. IN: Manual of Geographic Information Systems. M. Madden (Editor). American Society for Photogrammetry and Remote Sensing, Bethesda, MD. pp. 225 – 233.
Congalton, R. 2009. Accuracy and Error Analysis of Global and Local Maps: Lessons Learned and Future Considerations. IN: Remote Sensing of Global Croplands for Food Security. P. Thenkabail, J. Lyon, H. Turral, and C. Biradar. (Editors). CRC/Taylor & Francis, Boca Raton, FL pp. 441-458.
Congalton, R. 2010. How to Assess the Accuracy of Maps Generated from Remotely Sensed Data. IN: Manual of Geospatial Science and Technology, 2nd Edition. John Bossler. (Editor). Taylor & Francis, Boca Raton, FL pp. 403-421.
Selected Service Activities
- Editor-in-Chief, Photogrammetric Engineering & Remote Sensing, January 2008 - present
- American Society for Photogrammetry and Remote Sensing
- Fellow - 2007
- National Workshop Director 1997 – 2008
- Immediate Past President 2005-2006
- President 2004-2005
- President-elect 2003 –2004
- Vice President 2002 – 2003
- Secretary/Treasurer, New England Region 2004 - present
- Board of Directors, New England Region 1995 – 1997
- National Board of Directors, 1989-1991
- National GIS Division Director, 1989-1991
- President of Northern California Region, 1990 - 1991
- Vice President of Northern California Region, 1988 - 1989
- Board of Directors, Northern California Region 1986 – 1987
Society of American Foresters, Associate Editor for Remote Sensing & GIS, Northern Journal
of Applied Forestry 1996 - 2002
The Sanborn Map Company, Academic Advisory Council, Chair 2006 - present