Positions

Research Areas research areas

Overview

  • 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.
  • Selected Publications

    Academic Article

    Year Title
    2024 Early Detection of Southern Pine Beetle Attack by UAV-Collected Multispectral ImageryRemote Sensing.  16:2608-2608. 2024
    2023 Using Imagery Collected by an Unmanned Aerial System to Monitor Cyanobacteria in New Hampshire, USA, LakesRemote Sensing.  15:2839-2839. 2023
    2022 Evaluating the Impacts of Flying Height and Forward Overlap on Tree Height Estimates Using Unmanned Aerial SystemsForests.  13:1462-1462. 2022
    2022 Individual Tree Crown Delineation From UAS Imagery Based on Region Growing by Over-Segments With a Competitive MechanismIEEE Transactions on Geoscience and Remote Sensing.  60:1-11. 2022
    2021 Monitoring Fine-Scale Forest Health Using Unmanned Aerial Systems (UAS) Multispectral ModelsRemote Sensing.  13:4873-4873. 2021
    2021 The impact of landscape characteristics on the performance of upscaled mapsGeocarto International.  36:1905-1922. 2021
    2021 A Comparison of Methods for Determining Forest Composition from High-Spatial-Resolution Remotely Sensed ImageryForests.  12:1290-1290. 2021
    2021 Evaluating the Capability of Unmanned Aerial System (UAS) Imagery to Detect and Measure the Effects of Edge Influence on Forest Canopy Cover in New EnglandForests.  12:1252-1252. 2021
    2021 Mapping and Monitoring Forest CoverForests.  12:1184-1184. 2021
    2021 Estimating Primary Forest Attributes and Rare Community Characteristics Using Unmanned Aerial Systems (UAS): An Enrichment of Conventional Forest InventoriesRemote Sensing.  13:2971-2971. 2021
    2021 A Comparison of Multi-Temporal RGB and Multispectral UAS Imagery for Tree Species Classification in Heterogeneous New Hampshire ForestsRemote Sensing.  13:2631-2631. 2021
    2020 Analysis of the Impact of Positional Accuracy When Using a Single Pixel for Thematic Accuracy AssessmentRemote Sensing.  12:4093-4093. 2020
    2020 Using Geospatial Analysis to Map Forest Change in New Hampshire: 1996-PresentJournal of Forestry.  118:598-612. 2020
    2020 Evaluating ecosystem service trade-offs along a land-use intensification gradient in central Veracruz, MexicoEcosystem Services: science, policy and pratice.  45:101181-101181. 2020
    2020 Extending Crop Type Reference Data Using a Phenology-Based ApproachFRONTIERS IN SUSTAINABLE FOOD SYSTEMS.  4. 2020
    2020 Mapping croplands of Europe, Middle East, Russia, and Central Asia using Landsat, Random Forest, and Google Earth EngineISPRS Journal of Photogrammetry and Remote Sensing.  167:104-122. 2020
    2020 Individual Tree Crown Delineation from UAS Imagery Based on Region Growing and Growth Space ConsiderationsRemote Sensing.  12:2363-2363. 2020
    2020 A Comparison of Forest Tree Crown Delineation from Unmanned Aerial Imagery Using Canopy Height Models vs. Spectral LightnessForests.  11:605-605. 2020
    2020 Using agent-based models to inform the dynamics of winter tick parasitism of mooseEcological Complexity.  41:100813-100813. 2020
    2019 Using a simulation analysis to evaluate the impact of crop mapping error on crop area estimation from stratified samplingInternational Journal of Digital Earth: a new journal for a new vision.  12:1046-1066. 2019
    2019 Mapping cropland extent of Southeast and Northeast Asia using multi-year time-series Landsat 30-m data using a random forest classifier on the Google Earth Engine CloudInternational Journal of Applied Earth Observation and Geoinformation.  81:110-124. 2019
    2019 A regional evaluation of the effectiveness of Mexico's payments for hydrological servicesRegional Environmental Change.  19:1751-1764. 2019
    2019 Evaluating Sampling Designs for Assessing the Accuracy of Cropland Extent Maps in Different Cropland Proportion RegionsJournal of Geography, Environment and Earth Science International.  1-20. 2019
    2019 Accuracy Assessment of Global Food Security-Support Analysis Data (GFSAD) Cropland Extent Maps Produced at Three Different Spatial Resolutions (vol 10, 1800, 2018)Remote Sensing.  11:630-630. 2019
    2019 Characterizing Non-Industrial Private Forest Landowners' Forest Management Engagement and Advice SourcesSociety and Natural Resources.  32:204-221. 2019
    2019 Evaluating the Effectiveness of Unmanned Aerial Systems (UAS) for Collecting Thematic Map Accuracy Assessment Reference Data in New England ForestsForests.  10:24-24. 2019
    2019 Using a simulation analysis to evaluate the impact of crop mapping error on crop area estimation from stratified sampling.Int. J. Digit. Earth.  12:1046-1066. 2019
    2018 Integrating cloud-based workflows in continental-scale cropland extent classificationRemote Sensing of Environment: an interdisciplinary journal.  219:162-179. 2018
    2018 Accuracy Assessment of Global Food Security-Support Analysis Data (GFSAD) Cropland Extent Maps Produced at Three Different Spatial ResolutionsRemote Sensing.  10:1800-1800. 2018
    2018 A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platformISPRS Journal of Photogrammetry and Remote Sensing.  144:325-340. 2018
    2018 Habitat use of moose during critical periods in the winter tick life cycle in Northern New EnglandAlces : a Journal Devoted to the Biology and Management of Moose.  54:85-100. 2018
    2018 Post-socialist cropland changes and abandonment in MongoliaLand Degradation and Development.  29:2808-2821. 2018
    2018 Issues in Unmanned Aerial Systems (UAS) Data Collection of Complex Forest EnvironmentsRemote Sensing.  10:908-908. 2018
    2018 The impact of industrial oil development on a protected area landscape: demographic and social change at Murchison Falls Conservation Area, UgandaPopulation and Environment.  39:197-218. 2018
    2018 Using a Similarity Matrix Approach to Evaluate the Accuracy of Rescaled MapsRemote Sensing.  10:487-487. 2018
    2018 Improving the Upscaling of Land Cover Maps by Fusing Uncertainty and Spatial Structure InformationPhotogrammetric Engineering and Remote Sensing.  84:88-101. 2018
    2018 A quantitative performance comparison of paddy rice acreage estimation using stratified sampling strategies with different stratification indicatorsInternational Journal of Digital Earth: a new journal for a new vision.  11:1001-1019. 2018
    2018 A quantitative performance comparison of paddy rice acreage estimation using stratified sampling strategies with different stratification indicators.Int. J. Digit. Earth.  11:1001-1019. 2018
    2018 Issues with Large Area Thematic Accuracy Assessment for Mapping Cropland Extent: A Tale of Three ContinentsRemote Sensing.  10:53-53. 2018
    2018 Landsat's Enduring Legacy: Pioneering Global Land Observations from SpacePhotogrammetric Engineering and Remote Sensing.  84:9-10. 2018
    2017 Nominal 30-m Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth EngineRemote Sensing.  9:1065-1065. 2017
    2017 MODIS phenology-derived, multi-year distribution of conterminous US crop typesRemote Sensing of Environment: an interdisciplinary journal.  198:490-503. 2017
    2017 The Impact of Mapping Error on the Performance of Upscaling Agricultural MapsRemote Sensing.  9:901-901. 2017
    2017 Automated cropland mapping of continental Africa using Google Earth Engine cloud computingISPRS Journal of Photogrammetry and Remote Sensing.  126:225-244. 2017
    2017 A comparison of unsupervised segmentation parameter optimization approaches using moderate- and high-resolution imageryGIScience and Remote Sensing.  54:515-533. 2017
    2017 Spectral matching techniques (SMTs) and automated cropland classification algorithms (ACCAs) for mapping croplands of Australia using MODIS 250-m time-series (2000-2015) dataInternational Journal of Digital Earth: a new journal for a new vision.  10:944-977. 2017
    2017 The impact of industrial oil development on a protected area landscape: population pressure and struggles for land at Murchison Falls conservation area, UgandaPopulation and Environment2017
    2016 Future Landsat Data Needs at the Local and State Levels: An AmericaView PerspectivePhotogrammetric Engineering and Remote Sensing.  82:617-623. 2016
    2016 Future Landsat Data Needs at the Local and State Levels: An AmericaView PerspectivePhotogrammetric Engineering and Remote Sensing.  82:617-623. 2016
    2015 Land Cover Change Image Analysis for Assateague Island National Seashore Following Hurricane SandyJOURNAL OF IMAGING.  1:85-114. 2015
    2015 A comparison of landscape fragmentation analysis programs for identifying possible invasive plant species locations in forest edgeLandscape Ecology.  30:1241-1256. 2015
    2015 Remote Sensing and Image Interpretation. 7th EditionPhotogrammetric Engineering and Remote Sensing.  81:615-616. 2015
    2015 Soliciting Special Issues For Pe&RsPhotogrammetric Engineering and Remote Sensing.  81:194-196. 2015
    2015 Uncertainty Analysis in the Creation of a Fine-Resolution Leaf Area Index (LAI) Reference Map for Validation of Moderate Resolution LAI ProductsRemote Sensing.  7:1397-1421. 2015
    2015 Incipient Invasion of Urban and Forest Habitats in New Hampshire, USA, by the Nonnative Tree, Kalopanax septemlobusInvasive Plant Science and Management.  8:111-121. 2015
    2015 Modelling associations between public understanding, engagement and forest conditions in the Inland Northwest, USA.PLoS One.  10:e0117975. 2015
    2015 Optimal Land Cover Mapping and Change Analysis in Northeastern Oregon Using Landsat ImageryPhotogrammetric Engineering and Remote Sensing.  81:37-47. 2015
    2015 The Impact of Positional Errors on Soft Classification Accuracy Assessment: A Simulation AnalysisRemote Sensing.  7:579-599. 2015
    2014 Global Land Cover Mapping: A Review and Uncertainty AnalysisRemote Sensing.  6:12070-12093. 2014
    2014 Vertical point sampling with a digital camera: Slope correction and field evaluationComputers and Electronics in Agriculture.  100:131-138. 2014
    2013 Analyst variation associated with land cover image classification of Landsat ETM plus data for the assessment of coarse spatial resolution regional/global land cover productsGIScience and Remote Sensing.  50:604-622. 2013
    2013 Modeling Forest Canopy Structure and Density by Combining Point Quadrat Sampling and Survival AnalysisForest Science.  59:681-692. 2013
    2013 PolyFrag: a vector-based program for computing landscape metricsGIScience and Remote Sensing.  50:591-603. 2013
    2013 Requirements for labelling forest polygons in an object-based image analysis classificationInternational Journal of Remote Sensing.  34:2531-2547. 2013
    2013 Applicability of Multi-date Land Cover Mapping using Landsat-5 TM Imagery in the Northeastern USPhotogrammetric Engineering and Remote Sensing.  79:359-368. 2013
    2013 Spatio-statistical Predictions of Vernal Pool Locations in Massachusetts: Incorporating the Spatial Component into Ecological ModelingPhotogrammetric Engineering and Remote Sensing.  79:25-35. 2013
    2013 UntitledPhotogrammetric Engineering and Remote Sensing.  79:2-2. 2013
    2012 ASSESSING FUTURE RISKS TO AGRICULTURAL PRODUCTIVITY, WATER RESOURCES AND FOOD SECURITY: HOW CAN REMOTE SENSING HELP?Photogrammetric Engineering and Remote Sensing.  78:773-782. 2012
    2012 Incorporating the Downscaled Landsat TM Thermal Band in Land-cover Classification using Random ForestPhotogrammetric Engineering and Remote Sensing.  78:129-137. 2012
    2011 Writing a Scientific Journal Paper: Preparation through PublicationPhotogrammetric Engineering and Remote Sensing.  77:445-450. 2011
    2011 Investigating Issues in Map Accuracy When Using an Object-Based Approach to Map Benthic HabitatsGIScience and Remote Sensing.  48:457-477. 2011
    2010 Remote Sensing: An OverviewGIScience and Remote Sensing.  47:443-459. 2010
    2008 Leaf Area Index (LAI) Change Detection Analysis on Loblolly Pine (Pinus taeda) Following Complete Understory RemovalPhotogrammetric Engineering and Remote Sensing.  74:1389-1400. 2008
    2008 Validation of an Integrated Estimation of Loblolly Pine (Pinus taeda L.) Leaf Area Index (LAI) Using Two Indirect Optical Methods in the Southeastern United StatesSouthern Journal of Applied Forestry.  32:101-110. 2008
    2005 Effects of landscape characteristics on amphibian distribution in a forest-dominated landscapeBiological Conservation.  123:139-149. 2005
    2004 The ASPRS - ISPRS connectionPhotogrammetric Engineering and Remote Sensing.  70:1339-+. 2004
    2004 2000-2004 National Report ASPRS: The Imaging and Geospatial Information SocietyPhotogrammetric Engineering and Remote Sensing.  70:775-778. 2004
    2003 A comparison of urban mapping methods using high-resolution digital imageryPhotogrammetric Engineering and Remote Sensing.  69:963-972. 2003
    2003 Evaluating the potential for measuring river discharge from spaceJournal of Hydrology.  278:17-38. 2003
    2003 Sampling method and sample placement: How do they affect the accuracy of remotely sensed maps?Photogrammetric Engineering and Remote Sensing.  69:289-297. 2003
    2002 Evaluating remotely sensed techniques for mapping riparian vegetationComputers and Electronics in Agriculture.  37:113-126. 2002
    2002 Spatial and temporal analysis of a tidal floodplain landscape - Arnapi, Brazil - Using geographic information systems and remote sensingPhotogrammetric Engineering and Remote Sensing.  68:463-472. 2002
    2002 Tools for Successful Student–Teacher–Scientist PartnershipsJournal of Science Education and Technology.  11:277-287. 2002
    2002 Tools for successful student-teacher-scientist partnerships: Lessons from GLOBEJournal of Science Education and Technology.  11:113-126. 2002
    2001 Landscape change in tidal floodplains near the mouth of the Amazon RiverForest Ecology and Management.  154:383-393. 2001
    2001 An assessment of reference data variability using a "virtual field reference database"Photogrammetric Engineering and Remote Sensing.  67:707-715. 2001
    2001 Applying spatial autocorrelation analysis to evaluate error in new England forest-cover-type maps derived from Landsat Thematic Mapper dataPhotogrammetric Engineering and Remote Sensing.  67:613-620. 2001
    2001 Accuracy assessment and validation of remotely sensed and other spatial informationInternational Journal of Wildland Fire.  10:321-328. 2001
    1998 Mapping and monitoring agricultural crops and other land cover in the Lower Colorado River BasinPhotogrammetric Engineering and Remote Sensing.  64:1107-1113. 1998
    1998 Determining forest species composition using high spectral resolution remote sensing dataRemote Sensing of Environment: an interdisciplinary journal.  65:249-254. 1998
    1998 Quantitative comparison of change-detection algorithms for monitoring eelgrass from remotely sensed dataPhotogrammetric Engineering and Remote Sensing.  64:207-216. 1998
    1998 Classification of multi-temporal SPOT-XS satellite data for mapping rice fields on a West African floodplainInternational Journal of Remote Sensing.  19:21-41. 1998
    1998 A GLOBE collaboration to develop land cover data collection and analysis protocolsJournal of Science Education and Technology.  7:85-96. 1998
    1997 Exploring and evaluating the consequences of vector-to-raster and raster-to-vector conversionPhotogrammetric Engineering and Remote Sensing.  63:425-434. 1997
    1996 Predicting rare orchid (Small whorled Pogonia) habitat using GISPhotogrammetric Engineering and Remote Sensing.  62:1269-1279. 1996
    1995 EVALUATING SEASONAL VARIABILITY AS AN AID TO COVER-TYPE MAPPING FROM LANDSAT THEMATIC MAPPER DATA IN THE NORTHEASTPhotogrammetric Engineering and Remote Sensing.  61:321-327. 1995
    1993 Mapping deer habitat suitability using remote sensing and geographic information systemsGeocarto International.  8:23-33. 1993
    1993 A PRACTICAL LOOK AT THE SOURCES OF CONFUSION IN ERROR MATRIX GENERATIONPhotogrammetric Engineering and Remote Sensing.  59:641-644. 1993
    1993 MAPPING OLD GROWTH FORESTS ON NATIONAL FOREST AND PARK LANDS IN THE PACIFIC-NORTHWEST FROM REMOTELY SENSED DATAPhotogrammetric Engineering and Remote Sensing.  59:529-535. 1993
    1993 Mapping deer habitat suitability using remote sensing and GISGeocarto International.  8:23-33. 1993
    1992 A PILOT-STUDY EVALUATING GROUND REFERENCE DATA-COLLECTION EFFORTS FOR USE IN FOREST INVENTORYPhotogrammetric Engineering and Remote Sensing.  58:1669-1671. 1992
    1992 AN INTRODUCTION TO GEOGRAPHIC INFORMATION-SYSTEMSJournal of Forestry.  90:13-20. 1992
    1991 A REVIEW OF ASSESSING THE ACCURACY OF CLASSIFICATIONS OF REMOTELY SENSED DATARemote Sensing of Environment: an interdisciplinary journal.  37:35-46. 1991
    1991 REMOTE-SENSING AND GEOGRAPHIC INFORMATION-SYSTEM DATA INTEGRATION - ERROR SOURCES AND RESEARCH ISSUESPhotogrammetric Engineering and Remote Sensing.  57:677-687. 1991
    1990 USING THEMATIC MAPPER IMAGERY TO EXAMINE FOREST UNDERSTORYPhotogrammetric Engineering and Remote Sensing.  56:1285-1290. 1990
    1989 SATELLITE AND GEOGRAPHIC INFORMATION-SYSTEM ESTIMATES OF COLORADO RIVER BASIN SNOWPACKPhotogrammetric Engineering and Remote Sensing.  55:1629-1635. 1989
    1989 APPLICATION OF REMOTE-SENSING AND GEOGRAPHIC INFORMATION-SYSTEMS TO FOREST FIRE HAZARD MAPPINGRemote Sensing of Environment: an interdisciplinary journal.  29:147-159. 1989
    1989 GIS LIS 88 - 30 NOVEMBER - 2 DECEMBER 1988, SAN ANTONIO, TEXAS - USAPhotogrammetria.  43:286-287. 1989
    1988 Mapping and inventory of forest fires from digital processing of tm dataGeocarto International.  3:41-53. 1988
    1988 The use of LANDSAT data in forestryEarth-Science Reviews.  25:253-254. 1988
    1988 USING CLUSTER-ANALYSIS TO IMPROVE THE SELECTION OF TRAINING STATISTICS IN CLASSIFYING REMOTELY SENSED DATAPhotogrammetric Engineering and Remote Sensing.  54:1275-1281. 1988
    1988 A COMPARISON OF SAMPLING SCHEMES USED IN GENERATING ERROR MATRICES FOR ASSESSING THE ACCURACY OF MAPS GENERATED FROM REMOTELY SENSED DATAPhotogrammetric Engineering and Remote Sensing.  54:593-600. 1988
    1988 USING SPATIAL AUTO-CORRELATION ANALYSIS TO EXPLORE THE ERRORS IN MAPS GENERATED FROM REMOTELY SENSED DATAPhotogrammetric Engineering and Remote Sensing.  54:587-592. 1988
    1988 A METHODOLOGY FOR MAPPING FOREST LATENT-HEAT FLUX DENSITIES USING REMOTE-SENSINGRemote Sensing of Environment: an interdisciplinary journal.  24:405-418. 1988
    1987 CORRECT FORMULATION OF THE KAPPA COEFFICIENT OF AGREEMENT - COMMENTPhotogrammetric Engineering and Remote Sensing.  53:422-422. 1987
    1986 ACCURACY ASSESSMENT - A USERS PERSPECTIVEPhotogrammetric Engineering and Remote Sensing.  52:397-399. 1986
    1986 A REVIEW OF 3 DISCRETE MULTIVARIATE-ANALYSIS TECHNIQUES USED IN ASSESSING THE ACCURACY OF REMOTELY SENSED DATA FROM ERROR MATRICESIEEE Transactions on Geoscience and Remote Sensing.  24:169-174. 1986
    1983 A QUANTITATIVE METHOD TO TEST FOR CONSISTENCY AND CORRECTNESS IN PHOTOINTERPRETATIONPhotogrammetric Engineering and Remote Sensing.  49:69-74. 1983
    1983 ASSESSING LANDSAT CLASSIFICATION ACCURACY USING DISCRETE MULTIVARIATE-ANALYSIS STATISTICAL TECHNIQUESPhotogrammetric Engineering and Remote Sensing.  49:1671-1678. 1983
    A Comparison of Unpiloted Aerial System Hardware and Software for Surveying Fine-Scale Oak Health in Oak–Pine ForestsForests.  15:706-706.
    Analysis of Unmanned Aerial System (UAS) Sensor Data for Natural Resource Applications: A ReviewGeographies.  2:303-340.
    Analysis of the Impact of Positional Accuracy When Using a Block of Pixels for Thematic Accuracy AssessmentGeographies.  1:143-165.

    Book

    Year Title
    2019 Assessing the Accuracy of Remotely Sensed Data: Principles and Practices 2019
    2017 Imagery and GIS Best Practices for Extracting Information from Imagery 2017
    2013 Meeting Environmental Challenges with Remote Sensing Imagery 2013
    2009 Assessing the Accuracy of Remotely Sensed Data: Principles and Practices 2009
    2003 Quantifying spatial uncertainty in natural resources: theory and applications for GIS and Remote Sensing 2003
    1998 Assessing the Accuracy of Remotely Sensed Data Principles and Practices 1998

    Chapter

    Year Title
    2019 Unmanned Aerial Systems (UAS) and Thematic Map Accuracy Assessment.  17-34. 2019
    2019 Lessons Learned About Collaborating Across Coupled Natural-Human Systems Research on Mexico’s Payments for Hydrological Services Program.  35-77. 2019
    2016 Assessing Positional and Thematic Accuracies of Maps Generated from Remotely Sensed Data.  583-601. 2016
    2016 Global Food Security Support Analysis Data at Nominal 1 km (GFSAD1km) Derived from Remote Sensing in Support of Food Security in the Twenty-First Century: Current Achievements and Future Possibilities.  131-159. 2016
    2010 How to Assess the Accuracy of Maps Generated from Remotely Sensed Data.  403-421. 2010
    2009 Accuracy and Error Analysis of Global and Local Maps.  441-458. 2009
    2009 Accuracy Assessment of Spatial Data Sets.  225-234. 2009
    2009 Accuracy and Error Analysis of Global and Local Maps: Lessons Learned and Future Considerations.  441-458. 2009
    2004 Putting the Map Back in Map Accuracy Assessment.  1-11. 2004
    2004 An error matrix approach to fuzzy accuracy assessment: The NIMA geocover project.  163-172. 2004
    2001 Quality assurance and accuracy assessment of information derived from remotely sensed data.  349-363. 2001
    1999 Sampling Systems for Change Detection Accuracy Assessment.  281-308. 1999
    1999 Multi-Scale Resource Data.  125-139. 1999
    1997 Validating Student Data for Scientific Use: An Example from the GLOBE Program.  133-156. 1997
    1997 Validating Student Data for Scientific Use.  133-156. 1997

    Conference Paper

    Year Title
    2019 Comparing the impact of mapping error on the representation of landscape pattern on upscaled agricultural maps2019 8TH INTERNATIONAL CONFERENCE ON AGRO-GEOINFORMATICS (AGRO-GEOINFORMATICS). 1-6. 2019
    2010 MAPPING AND ANALYSIS OF FRAGMENTATION IN SOUTHEASTERN NEW HAMPSHIREInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives. 2010
    2004 Putting the map accuracy map back in assessmentREMOTE SENSING AND GIS ACCURACY ASSESSMENT. 1-11. 2004
    2002 An Approach to Estimating River Discharge from SpaceHydraulic Measurements and Experimental Methods 2002. 1-9. 2002
    2000 GLOBE MUC-A-THON: A method for effective student land cover data collectionIGARSS 2000: IEEE 2000 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOL I - VI, PROCEEDINGS. 551-553. 2000
    2000 Sampling methodology, sample placement, and other important factors in assessing the accuracy of remotely sensed forest mapsACCURACY 2000, PROCEEDINGS. 117-124. 2000
    1996 Monitoring global environmental resources: The globe perspectiveGIS/LIS '96 - ANNUAL CONFERENCE AND EXPOSITION PROCEEDINGS. 740-747. 1996
    1995 Using quantitative accuracy assessment techniques to compare various change detection algorithms for monitoring eelgrass distributions in Great Bay, NH generated from Landsat TM data1995 ACSM/ASPRS ANNUAL CONVENTION & EXPOSITION TECHNICAL PAPERS, VOL 3: ASPRS. 876-885. 1995
    1991 ANALYSIS OF REMOTELY SENSED DATA - WHERE DO WE GO FROM HEREPROCEEDINGS : THE INTEGRATION OF REMOTE SENSING AND GEOGRAPHIC INFORMATION SYSTEMS. 129-135. 1991
    1990 BEWARE THE BLACK-BOXGIS/LIS 90 : PROCEEDINGS, VOLS 1 AND 2. 851-853. 1990
    1990 DEVELOPMENT OF REMOTE-SENSING TECHNOLOGIES FOR USE IN FOREST INVENTORYGLOBAL NATURAL RESOURCE MONITORING AND ASSESSMENTS : PREPARING FOR THE 21ST CENTURY, VOLS 1-3. 1241-1249. 1990
    1990 MAPPING POTENTIAL OLD GROWTH FORESTS AND OTHER RESOURCES ON NATIONAL FOREST AND PARK LANDS IN OREGON AND WASHINGTONGIS/LIS 90 : PROCEEDINGS, VOLS 1 AND 2. 712-723. 1990
    1989 Considerations And Techniques For Assessing The Accuracy Of Remotely Sensed Data12th Canadian Symposium on Remote Sensing Geoscience and Remote Sensing Symposium,. 1847-1850. 1989

    Principal Investigator On

  • StateView Program Development  awarded by AmericaView Inc 2023 - 2025
  • NH StateView Program  awarded by AmericaView Inc 2018 - 2023
  • StateView Program Development and Operations for the State of New Hampshire  awarded by AmericaView Inc 2018 - 2022
  • Mapping Forest Type and Structure from Unmanned Aerial Systems (UAS) Imagery  awarded by USDA New Hampshire Agricultural Experiment Station (McIntire-Stennis) 2018 - 2021
  • Using GeoSpatial Analysis to Map Forest Change in New Hampshire: 1996-Present  awarded by Society of American Foresters 2018 - 2019
  • Validating Remotely Sensed Forest and Other Land Cover Maps Generated Using Object-based Image Analysis and Over Large Areas  awarded by NH Agricultural Experiment Station 2014 - 2018
  • Global Cropland Area Database from Remotely Sensed Data  awarded by US DOI, US Geological Survey 2013 - 2018
  • Stateview Program Development and Operations for NH  awarded by AmericaView Inc 2013 - 2017
  • Stateview Program Development and Operations for NH  awarded by AmericaView Inc 2012 - 2013
  • State View program Development and Operations for New Hampshire  awarded by AmericaView Inc 2008 - 2013
  • New Hampshire View Setup 07  awarded by AmericaView Inc 2007
  • Scientific Support for Globe Land Cover Investigation  awarded by National Science Foundation (NSF) 2002 - 2007
  • Geographic Information System for Cultural Features  awarded by Stefan Claesson Associates 2001 - 2002
  • Scientific Protocols for Land Cover/Biology Globe Program  awarded by National Science Foundation (NSF) 1997 - 2002
  • Change Detection Accuracy Investigation  awarded by Analytic Sciences Corporation, The 1995 - 1997
  • Integrating Reference Data and Accuracy Assessment for Globe  awarded by National Science Foundation (NSF) 1994 - 1997
  • Accuracy Assessment of Multispectral Imagery  awarded by Analytic Sciences Corporation, The 1993 - 1994
  • Using Spatial Analysis to Map Black Bear Habitat in NH  awarded by NH Department of Fish & Game 1992 - 1994
  • Advanced Techniques for Mapping & Monitoring Ecosystems  awarded by Environmental Protection Agency (EPA) 1991 - 1994
  • Accuracy Assessment Procedures for Change Detection Analysis  awarded by US DOC, National Oceanic & Atmospheric Administration (NOAA) 1992 - 1993
  • Teaching Activities

  • Intro Geographic Info Systems Taught course
  • Intro Geographic Info Systems Taught course
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  • Remote Sensing of the Environ Taught course 2024
  • Remote Sensing of the Environ Taught course 2024
  • Work Experience Taught course 2024
  • Work Experience Taught course 2024
  • Intro Geographic Info Systems Taught course 2023
  • Intro Geographic Info Systems Taught course 2023
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  • Intro Geographic Info Systems Taught course 2023
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  • Intro Geographic Info Systems Taught course 2023
  • Intro Geographic Info Systems Taught course 2023
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  • Remote Sensing of the Environ Taught course 2022
  • Remote Sensing of the Environ Taught course 2022
  • Remote Sensing of the Environ Taught course 2022
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  • Work Experience Taught course 2022
  • Digital Image Process Nat Res Taught course 2022
  • Digital Image Process Nat Res Taught course 2022
  • Intro Geographic Info Systems Taught course 2022
  • Intro Geographic Info Systems Taught course 2022
  • Intro Geographic Info Systems Taught course 2022
  • Intro Geographic Info Systems Taught course 2022
  • Intro Geographic Info Systems Taught course 2022
  • Intro Geographic Info Systems Taught course 2022
  • Intro Geographic Info Systems Taught course 2022
  • Intro Geographic Info Systems Taught course 2022
  • Intro Geographic Info Systems Taught course 2022
  • Work Experience Taught course 2022
  • Remote Sensing of Environment Taught course 2021
  • Remote Sensing of Environment Taught course 2021
  • Remote Sensing of Environment Taught course 2021
  • Work Experience Taught course 2021
  • Work Experience Taught course 2021
  • Intro Geographic Info Systems Taught course 2021
  • Intro Geographic Info Systems Taught course 2021
  • Intro Geographic Info Systems Taught course 2021
  • Intro Geographic Info Systems Taught course 2021
  • Intro Geographic Info Systems Taught course 2021
  • Intro Geographic Info Systems Taught course 2021
  • Intro Geographic Info Systems Taught course 2021
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  • Remote Sensing of Environment Taught course 2020
  • Remote Sensing of Environment Taught course 2020
  • Remote Sensing of Environment Taught course 2020
  • Work Experience Taught course 2020
  • Work Experience Taught course 2020
  • Digital Image Process Nat Res Taught course 2020
  • Digital Image Process Nat Res Taught course 2020
  • Intro Geographic Info Systems Taught course 2020
  • Intro Geographic Info Systems Taught course 2020
  • Intro Geographic Info Systems Taught course 2020
  • Intro Geographic Info Systems Taught course 2020
  • Intro Geographic Info Systems Taught course 2020
  • Intro Geographic Info Systems Taught course 2020
  • Intro Geographic Info Systems Taught course 2020
  • Investigations Taught course 2020
  • Work Experience Taught course 2020
  • Remote Sensing of Environment Taught course 2019
  • Remote Sensing of Environment Taught course 2019
  • Remote Sensing of Environment Taught course 2019
  • Work Experience Taught course 2019
  • Work Experience Taught course 2019
  • The Science of Where Taught course 2019
  • GIS in Natural Resources Taught course 2019
  • GIS in Natural Resources Taught course 2019
  • Intro Geographic Info Systems Taught course 2019
  • Intro Geographic Info Systems Taught course 2019
  • Intro Geographic Info Systems Taught course 2019
  • Intro Geographic Info Systems Taught course 2019
  • Intro Geographic Info Systems Taught course 2019
  • Intro Geographic Info Systems Taught course 2019
  • Intro Geographic Info Systems Taught course 2019
  • Remote Sensing of Environment Taught course 2018
  • Remote Sensing of Environment Taught course 2018
  • Remote Sensing of Environment Taught course 2018
  • Work Experience Taught course 2018
  • Work Experience Taught course 2018
  • Digital Image Process Nat Res Taught course 2018
  • Digital Image Process Nat Res Taught course 2018
  • Intro Geographic Info Systems Taught course 2018
  • Intro Geographic Info Systems Taught course 2018
  • Intro Geographic Info Systems Taught course 2018
  • Intro Geographic Info Systems Taught course 2018
  • Intro Geographic Info Systems Taught course 2018
  • Intro Geographic Info Systems Taught course 2018
  • Intro Geographic Info Systems Taught course 2018
  • Intro Geographic Info Systems Taught course 2018
  • Work Experience Taught course 2018
  • Remote Sensing of Environment Taught course 2017
  • Remote Sensing of Environment Taught course 2017
  • Remote Sensing of Environment Taught course 2017
  • GIS in Natural Resources Taught course 2017
  • GIS in Natural Resources Taught course 2017
  • Intro Geographic Info Systems Taught course 2017
  • Intro Geographic Info Systems Taught course 2017
  • Intro Geographic Info Systems Taught course 2017
  • Intro Geographic Info Systems Taught course 2017
  • Intro Geographic Info Systems Taught course 2017
  • Intro Geographic Info Systems Taught course 2017
  • Intro Geographic Info Systems Taught course 2017
  • Work Experience Taught course 2016
  • Digital Image Process Nat Res Taught course 2016
  • Intro Geographic Info Systems Taught course 2016
  • Intro Geographic Info Systems Taught course 2016
  • Intro Geographic Info Systems Taught course 2016
  • Intro Geographic Info Systems Taught course 2016
  • Intro Geographic Info Systems Taught course 2016
  • Intro Geographic Info Systems Taught course 2016
  • Intro Geographic Info Systems Taught course 2016
  • Remote Sensing of Environment Taught course 2015
  • Remote Sensing of Environment Taught course 2015
  • Remote Sensing of Environment Taught course 2015
  • Remote Sensing of the Environ Taught course 2015
  • The Science of Where Taught course 2015
  • GIS in Natural Resources Taught course 2015
  • GIS in Natural Resources Taught course 2015
  • Intro Geographic Info Systems Taught course 2015
  • Intro Geographic Info Systems Taught course 2015
  • Intro Geographic Info Systems Taught course 2015
  • Intro Geographic Info Systems Taught course 2015
  • Intro Geographic Info Systems Taught course 2015
  • Intro Geographic Info Systems Taught course 2015
  • Intro Geographic Info Systems Taught course 2015
  • Remote Sensing of Environment Taught course 2014
  • Remote Sensing of Environment Taught course 2014
  • Remote Sensing of Environment Taught course 2014
  • The Science of Where Taught course 2014
  • Digital Image Process Nat Res Taught course 2014
  • Digital Image Process Nat Res Taught course 2014
  • Intro Geographic Info Systems Taught course 2014
  • Intro Geographic Info Systems Taught course 2014
  • Intro Geographic Info Systems Taught course 2014
  • Intro Geographic Info Systems Taught course 2014
  • Intro Geographic Info Systems Taught course 2014
  • Intro Geographic Info Systems Taught course 2014
  • Intro Geographic Info Systems Taught course 2014
  • Education And Training

  • B.S. Natural Resources Management, Rutgers University
  • M.S. Forest Biometrics and Remote Sensing, Virginia Polytechnic Institute and State University
  • Ph.D. Forest Biometrics and Remote Sensing, Virginia Polytechnic Institute and State University
  • Full Name

  • Russell Congalton
  • Mailing Address

  • University of New Hampshire

    Department of Natural Resources & the Environment

    56 College Road, 114 James Hall

    Durham, NH  03824

    United States