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Environmental Sciences

D-Index
48
Citations
34404
World Ranking
5379
National Ranking
1965

Overview

Russell G. Congalton is affiliated with the University of New Hampshire in the United States. Their research primarily focuses on environmental science, with a particular emphasis on ecology, environmental engineering, and global and planetary change. Their work spans several subfields, including insect science and nature and landscape conservation.

The scientist's research topics cover multiple areas related to remote sensing and ecosystem studies. Main topics include:

  • Remote Sensing in Agriculture
  • Remote Sensing and LiDAR Applications
  • Land Use and Ecosystem Services
  • Forest Ecology and Biodiversity Studies
  • Forest Insect Ecology and Management
  • Forest ecology and management
  • 3D Surveying and Cultural Heritage

Russell G. Congalton has contributed extensively to academic journals, with frequent publications in venues such as:

  • Remote Sensing
  • Forests
  • Geographies
  • Photogrammetric Engineering & Remote Sensing
  • ISPRS Journal of Photogrammetry and Remote Sensing

Their recent papers include:

  • Mapping croplands of Europe, Middle East, Russia, and Central Asia using Landsat, Random Forest, and Google Earth Engine (2020), published in ISPRS Journal of Photogrammetry and Remote Sensing
  • Global cropland-extent product at 30-m resolution (GCEP30) derived from Landsat satellite time-series data for the year 2015 using multiple machine-learning algorithms on Google Earth Engine cloud (2021), published in USGS professional paper
  • Monitoring Fine-Scale Forest Health Using Unmanned Aerial Systems (UAS) Multispectral Models (2021), published in Remote Sensing
  • A Comparison of Multi-Temporal RGB and Multispectral UAS Imagery for Tree Species Classification in Heterogeneous New Hampshire Forests (2021), published in Remote Sensing
  • Evaluating ecosystem service trade-offs along a land-use intensification gradient in central Veracruz, Mexico (2020), published in Ecosystem Services

Russell G. Congalton frequently collaborates with several co-authors, including:

  • Benjamin T. Fraser
  • Heather Grybas
  • Jianyu Gu
  • Kamini Yadav
  • Aparna Phalke

Best Publications

  • A review of assessing the accuracy of classifications of remotely sensed data

    Russell G. Congalton

  • Assessing the accuracy of remotely sensed data : principles and practices

    Russell G. Congalton;Kass Green

  • Accuracy assessment: a user's perspective

    M. Story;R. G. Congalton

  • Assessing Landsat classification accuracy using discrete multivariate analysis statistical techniques.

    R G Congalton;R G Oderwald;R A Mead

  • A Quantitative Method to Test for Consistency and Correctness in Photointerpretation

    R. G. Congalton

  • Application of remote sensing and geographic information systems to forest fire hazard mapping.

    Emilio Chuvieco;Russell G. Congalton

  • A Quantitative Comparison of Change-Detection Algorithms for Monitoring Eelgrass from Remotely Sensed Data

    Robb D. Macleod;Russell G. Congalton

  • Remote sensing and Geographic Information System data integration: error sources and research issues

    R. S. Lunetta;R. G. Congalton;L. K. Fenstermaker;J. R. Jensen

  • Accuracy assessment and validation of remotely sensed and other spatial information

    Russell G. Congalton

  • A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform

    Pardhasaradhi Teluguntla;Pardhasaradhi Teluguntla;Prasad S. Thenkabail;Adam Oliphant;Jun N. Xiong

  • Automated cropland mapping of continental Africa using Google Earth Engine cloud computing

    Jun N. Xiong;Prasad S. Thenkabail;Murali Krishna Gumma;Pardhasaradhi G. Teluguntla

  • Determining Forest Species Composition Using High Spectral Resolution Remote Sensing Data

    M.E Martin;S.D Newman;J.D Aber;R.G Congalton

  • A Comparison of Urban Mapping Methods Using High-Resolution Digital Imagery

    Nancy Thomas;Chad Hendrix;Russell G. Congalton

  • 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 Engine

    Jun N. Xiong;Prasad S. Thenkabail;James C. Tilton;Murali Krishna Gumma

  • Evaluating the potential for measuring river discharge from space

    David M. Bjerklie;S. Lawrence Dingman;Charles J. Vorosmarty;Carl H. Bolster

  • Global Land Cover Mapping: A Review and Uncertainty Analysis

    Russell G. Congalton;Jianyu Gu;Kamini Yadav;Prasad S. Thenkabail

  • A practical look at the sources of confusion in error matrix generation

    R. G Congalton;K Green

  • Using spatial autocorrelation analysis to explore the errors in maps generated from remotely sensed data

    R.G. Congalton

  • Effects of landscape characteristics on amphibian distribution in a forest-dominated landscape

    H.L. Herrmann;K.J. Babbitt;M.J. Baber;R.G. Congalton

  • Mapping and inventory of forest fires from digital processing of tm data

    Emilio Chuvieco;Russell G. Congalton

Frequent Co-Authors

Prasad S. Thenkabail
Prasad S. Thenkabail United States Geological Survey
Murali Krishna Gumma
Murali Krishna Gumma International Crops Research Institute for the Semi-Arid Tropics
Joel N. Hartter
Joel N. Hartter University of Colorado Boulder
Mutlu Ozdogan
Mutlu Ozdogan University of Wisconsin–Madison
Lawrence C. Hamilton
Lawrence C. Hamilton University of New Hampshire
Randall K. Kolka
Randall K. Kolka US Forest Service
Daniel S. Maynard
Daniel S. Maynard University of Chicago
Heidi Asbjornsen
Heidi Asbjornsen University of New Hampshire
Sadie J. Ryan
Sadie J. Ryan University of Florida
Charles J. Vörösmarty
Charles J. Vörösmarty City College of New York

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