Russell G. Congalton, Ph.D.

Russell G. Congalton, Ph.D.

Program Coordinator for Environmental Conservation & Sustainability, Professor

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, loon, 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 southeastern NH using various sources of remotely sensed data including unmanned aerial systems (UAS) and different automated image processing methodologies.  I was part of an 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 the 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.  In addition, I am working on an NSF-funded multi-investigator project evaluating the effectiveness of payments for ecological services in Mexico and also a NASA MEaSUREs multi-investigator project mapping agricultural crops worldwide at Landsat 30m resolution.  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.

 

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, GEOG 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 Students
 
M.S. Students
Christine Healy (Co-Chair)
Linnea Dwyer
Katie Moran (Co-Chair)
 
Ph.D. Students
Kamini Yadav
Heather Grybas
Ben Fraser

 

Alumni

2005 - present          
 

Year

Degree

 

Year

Degree

Ben Fraser  2017 M.S. Alexis Rudko 2010 MS.
Nicholas Dowhaniuk (Co-Chair) 2016 M.S. Katie Jacques 2009 M.S.
Morgan Crowley (Co-Chair) 2015 M.S. Meghan Graham 2008 M.S. 
Heather Grybas 2015 M.S. Brianna Heath 2008 M.S.
Lindsay Ledoux 2015 M.S. Alastair Lough 2008 Ph.D.
Jenna Kovacs 2014 M.S.              Tina Cormier 2007 M.S.
Bob Champoux 2013 M.S. Jesse Bishop 2006 M.S.
Michael Campbell 2012 M.S. John Iiames 2006 Ph.D.
Christina Czarnecki 2012 M.S. Peter Tardie 2005 M.S.
Daniel Maynard (Co-Chair) 2012 M.S. Michael Toepfer 2005 M.S.
Meghan MacLean 2012 Ph.D. Mark Brennan 2005 Ph.D.
Shawn Herrick 2011 M.S.      
           

Selected Publications

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

Congalton, R. J. Gu, K. Yadav, P. Thenkabail, and M. Osdogan. 2014. Global land cover mapping: A review and uncertainty analysis. Remote Sensing, 6, pp. 12070-12093; doi:10.3390/rs61212070

Gu, J. R. G. Congalton, and Y. Pan. 2015. The impact of positional errors on soft classification accuracy assessment: A simulation analysis. Remote Sensing. 7, pp. 579-599; doi:10.3390/rs70100579

Campbell, M., R. Congalton, J. Hartter, and M. Ducey. 2015. Optimal land cover mapping and change analysis in northeastern Oregon using Landsat imagery. Photogrammetric Engineering and Remote Sensing. Vol. 81, No. 1, pp. 37-47. doi:10.14358/PERS.81.1.37

Iiames, J.S., R.G. Congalton, T.E. Lewis, and A. Pilant. 2015. Uncertainty analysis in the creation of a fine-resolution leaf area index (LAI) reference map for validation of moderate resolution LAI products. Remote Sensing. 7, pp. 1397-1421; doi:10.3390/rs70201397

Hartter, J., F. Stevens, L. Hamilton, R. Congalton, M. Ducey,  and P. Oester. 2015. Modelling associations between public understanding, engagement and forest conditions in the Inland Northwest, USA. PLoS ONE 10(2): e0117975. doi:10.1371/journal.pone.0117975

Sivanpillai, R. and R. Congalton. 2016. Future Landsat data needs at the local and state levels: An AmericaView perspective. Photogrammetric Engineering and Remote Sensing.  Vol. 82, No. 8. pp. 617-623.

Teluguntla, Pardhasaradhi,  Prasad S. Thenkabail, Jun Xiong, Murali Krishna Gumma, Russell G. Congalton, Adam Oliphant, Justin Poehnelt, Kamini Yadav, Mahesh Rao and Richard Massey. 2017. Spectral matching techniques (SMTs) and automated cropland classification algorithms (ACCAs) for mapping croplands of Australia using MODIS 250-m time-series (2000–2015) data. International Journal of Digital Earth. DOI: 10.1080/17538947.2016.1267269

Xiong, Jun, Prasad S. Thenkabail, Murali K. Gumma, Pardhasaradhi Teluguntla, Justin Poehnelt, Russell G. Congalton,  and Kamini Yadav. 2017. Automated cropland mapping of continental Africa using Google Earth Engine cloud computing. ISPRS Journal of Photogrammetry and Remote Sensing. 126:225-244. http://dx.doi.org/10.1016/j.isprsjprs.2017.01.019.

Grybas, Heather, Lindsay Melendy, and Russell G. Congalton. 2017. A comparison of unsupervised segmentation optimization approaches using moderate- and high-resolution imagery. GIScience and Remote Sensing. DOI: 10.1080/15481603.2017.1287238

Massey, Richard, Temuulen T. Sankey, Russell G. Congalton, Kamini Yadav, Prasad S. Thenkabail, Mutlu Odzogan, and Andrew J. Sanchez Meador. 2017. MODIS phenology-derived, multi-year distribution of conterminous U.S. crop types. Remote Sensing of Environment. Vol. 198. pp.490-503. http://dx.doi.org/10.1016/j.rse.2017.06.033.

 

Selected Service Activities 

Editor-in-Chief, Photogrammetric Engineering & Remote Sensing
                           ​January, 2008 – March 2016

American Society for Photogrammetry and Remote Sensing
                           Honorary Member/Lifetime Achievement - 2016
                           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 – 2016
                           Secretary, Board of Directors 2016 - 2017

Russell G. Congalton
James Hall, Room 164
Durham, NH 03824
Phone: 
603-862-4644