World's Best Scientists 2026 revealed!

D-Index & Metrics

Environmental Sciences

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

Russell G. Congalton publication distribution in Environmental Sciences in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Environmental Sciences in 2026. The highlighted bar marks where Russell G. Congalton sits on this spectrum.

41–50 publications: 21 scientists 51–60 publications: 62 scientists 61–70 publications: 133 scientists 71–80 publications: 257 scientists 81–90 publications: 361 scientists 91–100 publications: 440 scientists 101–110 publications: 492 scientists 111–120 publications: 541 scientists 121–130 publications: 617 scientists 131–140 publications: 544 scientists 141–150 publications: 541 scientists 151–160 publications: 539 scientists 161–170 publications: 444 scientists 171–180 publications: 444 scientists 181–190 publications: 400 scientists 191–200 publications: 377 scientists 201–210 publications: 318 scientists 211–220 publications: 283 scientists 221–230 publications: 263 scientists 231–240 publications: 220 scientists 241–250 publications: 217 scientists 251–260 publications: 180 scientists 261–270 publications: 181 scientists 271–280 publications: 155 scientists 281–290 publications: 130 scientists 291–300 publications: 127 scientists 301–310 publications: 130 scientists 311–320 publications: 85 scientists 321–330 publications: 106 scientists 331–340 publications: 80 scientists 341–350 publications: 83 scientists 351–360 publications: 75 scientists 361–370 publications: 69 scientists 371–380 publications: 52 scientists 381–390 publications: 54 scientists 391–400 publications: 56 scientists 401–410 publications: 44 scientists 411–420 publications: 40 scientists 421–430 publications: 36 scientists 431–440 publications: 25 scientists 441–450 publications: 25 scientists 451–460 publications: 32 scientists 461–470 publications: 29 scientists 471–480 publications: 21 scientists 481–490 publications: 26 scientists 491–500 publications: 25 scientists 501–510 publications: 17 scientists 511–520 publications: 18 scientists 521–530 publications: 15 scientists 531–540 publications: 22 scientists 541–550 publications: 12 scientists 551–560 publications: 15 scientists 561–570 publications: 11 scientists 571–580 publications: 19 scientists 581–590 publications: 9 scientists 591–600 publications: 9 scientists 601–610 publications: 7 scientists 611–620 publications: 11 scientists 621–630 publications: 5 scientists 631–640 publications: 5 scientists 641–650 publications: 6 scientists 651–660 publications: 3 scientists 661–670 publications: 3 scientists 671–680 publications: 4 scientists 681–686 publications: 3 scientists 687+ publications: 100 scientists
41 publications 687+

This scientist: 178 publications — 55th percentile

55% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 687 publications or more.

Russell G. Congalton D-index placement in Environmental Sciences in 2026

The chart shows the D-index (discipline H-index) distribution of Environmental Sciences scientists ranked by Research.com in 2026. The highlighted bar marks where Russell G. Congalton sits on this spectrum.

30 D-Index: 12 scientists 31 D-Index: 26 scientists 32 D-Index: 51 scientists 33 D-Index: 88 scientists 34 D-Index: 123 scientists 35 D-Index: 163 scientists 36 D-Index: 206 scientists 37 D-Index: 267 scientists 38 D-Index: 265 scientists 39 D-Index: 275 scientists 40 D-Index: 321 scientists 41 D-Index: 343 scientists 42 D-Index: 305 scientists 43 D-Index: 336 scientists 44 D-Index: 330 scientists 45 D-Index: 348 scientists 46 D-Index: 291 scientists 47 D-Index: 275 scientists 48 D-Index: 272 scientists 49 D-Index: 273 scientists 50 D-Index: 263 scientists 51 D-Index: 232 scientists 52 D-Index: 266 scientists 53 D-Index: 217 scientists 54 D-Index: 199 scientists 55 D-Index: 177 scientists 56 D-Index: 202 scientists 57 D-Index: 204 scientists 58 D-Index: 166 scientists 59 D-Index: 177 scientists 60 D-Index: 166 scientists 61 D-Index: 152 scientists 62 D-Index: 143 scientists 63 D-Index: 150 scientists 64 D-Index: 124 scientists 65 D-Index: 119 scientists 66 D-Index: 120 scientists 67 D-Index: 118 scientists 68 D-Index: 82 scientists 69 D-Index: 98 scientists 70 D-Index: 94 scientists 71 D-Index: 105 scientists 72 D-Index: 74 scientists 73 D-Index: 84 scientists 74 D-Index: 70 scientists 75 D-Index: 67 scientists 76 D-Index: 78 scientists 77 D-Index: 60 scientists 78 D-Index: 59 scientists 79 D-Index: 52 scientists 80 D-Index: 47 scientists 81 D-Index: 38 scientists 82 D-Index: 48 scientists 83 D-Index: 42 scientists 84 D-Index: 42 scientists 85 D-Index: 43 scientists 86 D-Index: 29 scientists 87 D-Index: 37 scientists 88 D-Index: 29 scientists 89 D-Index: 30 scientists 90 D-Index: 34 scientists 91 D-Index: 20 scientists 92 D-Index: 22 scientists 93 D-Index: 17 scientists 94 D-Index: 19 scientists 95 D-Index: 24 scientists 96 D-Index: 21 scientists 97 D-Index: 20 scientists 98 D-Index: 24 scientists 99 D-Index: 17 scientists 100 D-Index: 17 scientists 101 D-Index: 21 scientists 102 D-Index: 25 scientists 103 D-Index: 18 scientists 104 D-Index: 26 scientists 105 D-Index: 19 scientists 106 D-Index: 15 scientists 107 D-Index: 10 scientists 108 D-Index: 13 scientists 109 D-Index: 15 scientists 110 D-Index: 12 scientists 111 D-Index: 8 scientists 112 D-Index: 7 scientists 113 D-Index: 9 scientists 114 D-Index: 6 scientists 115 D-Index: 12 scientists 116 D-Index: 7 scientists 117 D-Index: 8 scientists 118 D-Index: 3 scientists 119 D-Index: 5 scientists 120 D-Index: 7 scientists 121 D-Index: 2 scientists 122 D-Index: 4 scientists 123 D-Index: 8 scientists 124 D-Index: 7 scientists 125+ D-Index: 99 scientists
30 D-Index 125+

This scientist: 48 D-Index — 44th percentile

44% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 125 D-Index or more.

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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