Russell G. Congalton

Russ Congalton

Professor, Remote Sensing & Geographics Information Systems

Natural Resources Graduate Program Coordinator

Graduate Faculty Mentoring Award 2005

russ.congalton@unh.edu
603-862-4644

Research

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

Education

  • 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

Teaching Responsibilities

  • NR 458: The Science of Where
  • 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

Graduate Students

Current StudentsAlumni: 2005 - presentYearDegreeYearDegree
M.S. StudentsBob Champoux2013M.S.              Brianna Heath2008M.S.
Morgan Crowley(co-chair)Michael Campbell2012M.S.Alastair Lough2008Ph.D.
Nicholas Dowhaniak(co-chair)Christina Czarnecki2012M.S.Tina Cormier2007M.S
Heather GrybasDaniel Maynard (co-chair)2012M.S.Jesse Bishop2006M.S
Jenna KovacsMeghan MacLean2012Ph.D.John Iiames2006Ph.D.
Lindsay LedouxShawn Herrick2011M.S.Peter Tardie2005M.S.
 Alexis Rudko2010M.S.Michael Toepfer2005M.S.
Ph.D. StudentsKatie Jacques2009M.S. Mark Brennan2005Ph.D.
Kamini YadavMeghan Graham2008 M.S.   
       

Selected Publications

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.

Congalton, R. 2010. Remote sensing: An overview. GIScience and Remote Sensing. 47, No. 4. pp. 443-459.

Maclean, M. and R. Congalton. 2011. Investigating issues in map accuracy when using an object-based approach to map benthic habitats. GIScience and Remote Sensing. 48, No. 4. pp 457-477

Rodriquez-Galiano, V., B. Ghimire, E. Pardo-Iguzquiza, M. Chica-Olmo, and R. Congalton. 2012. Incorporating the Downscaled Landsat TM Thermal Band in Land-cover Classification using Random Forest. Photogrammetric Engineering and Remote Sensing. Vol. 78. No. 2. pp. 129-137.

Cormier, T., R. Congalton, and K. Babbitt. 2013. Spatial-statistical predictions of vernal pool locations in Massachusetts: Incorporating the spatial component into ecological modeling.  Photogrammetric Engineering and Remote Sensing. Vol. 79. No. 1. pp. 25-35.

MacLean, M. M. Campbell, D. Maynard, M. Ducey, and R. Congalton. 2013. Requirements for labeling forest polygons in an object-based image analysis classification.  International Journal of Remote Sensing.  Vol. 34 No. 7. pp. 2531-2547.

MacLean, M. and R. Congalton. 2013. Applicability of multi-date land cover mapping using Landsat 5 TM imagery in the Northeastern US. Photogrammetric Engineering and Remote Sensing. Vol. 79. No. 4. pp. 359-368.

Maynard, D. M. Ducey, R. Congalton, and J. Hartter. 2013. Modeling forest canopy structure and density by combining point quadrat sampling and survival analysis. Forest Science. Vol.59., No 6. pp. 681- 692. http://dx.doi.org/10.5849/forsci.12-086.

MacLean, M. and R. Congalton. 2013. PolyFrag: A vector-based program for computing landscape metrics. GIScience and Remote Sensing. Vol. 50, No. 6. pp. 591-603. http://dx.doi.org/10.1080/15481603.2013.856537.

Iiames, J, R. Congalton and R. Lunetta. 2013. Analyst variation associated with landcover image classification of Landsat ETM+ data for the assessment of coarse spatial resolution regional/global landcover products. GIScience and Remote Sensing. Vo. 50., No. 6. pp. 604-622.

Dodge, R. and R. Congalton 2013. Meeting Environmental Challenges with Remote Sensing Imagery. American Geosciences Institute. Alexandria, VA. 82p.

Maynard, D. M. Ducey, R. Congalton, J. Kershaw, and J. Hartter. 2014.  Vertical point sampling with a digital camera: Slope correction and field evaluation. Computers and Electronics in Agriculture. Vol. 100. pp. 131-138. http://dx.doi.org/10.1016/j.compag.2013.11.007

 

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 – 2011.

AmericaView

  • Board of Directors 2012 – present
  • Vice Chair, Board of Directors 2013-2014
  • Chair, Board of Directors 2014 - present