World's Best Scientists 2026 revealed!

D-Index & Metrics

Environmental Sciences

D-Index
61
Citations
20305
World Ranking
2707
National Ranking
1082

Chengquan Huang 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 Chengquan Huang 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: 204 publications — 66th percentile

66% of scientists in this discipline score the same or lower.

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

Chengquan Huang 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 Chengquan Huang 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: 61 D-Index — 72nd percentile

72% of scientists in this discipline score the same or lower.

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

Overview

Chengquan Huang is affiliated with the University of Maryland, College Park in the United States. Their research primarily focuses on environmental science, with significant contributions across several subfields including global and planetary change, environmental engineering, ecology, nature and landscape conservation, and atmospheric science.

The scientist's work extensively involves the application of remote sensing technologies and LiDAR for environmental monitoring and analysis. Major topics covered in their research include remote sensing and LiDAR applications, remote sensing in agriculture, fire effects on ecosystems, land use and ecosystem services, urban heat island mitigation, forest ecology and management, and plant water relations and carbon dynamics.

Chengquan Huang has published numerous articles, frequently appearing in journals such as Remote Sensing, Remote Sensing of Environment, Forests, Forest Ecosystems, and the SSRN Electronic Journal. These venues are central to disseminating findings on remote sensing and environmental monitoring.

  • Remote Sensing
  • Remote Sensing of Environment
  • Forests
  • Forest Ecosystems
  • SSRN Electronic Journal

Significant recent papers by Huang include:

  • "Rapid and robust monitoring of flood events using Sentinel-1 and Landsat data on the Google Earth Engine" (2020, Remote Sensing of Environment)
  • "Monthly mapping of forest harvesting using dense time series Sentinel-1 SAR imagery and deep learning" (2021, Remote Sensing of Environment)
  • "Monitoring Key Forest Structure Attributes across the Conterminous United States by Integrating GEDI LiDAR Measurements and VIIRS Data" (2021, Remote Sensing)
  • "Mapping Forested Wetland Inundation in the Delmarva Peninsula, USA Using Deep Convolutional Neural Networks" (2020, Remote Sensing)
  • "A LiDAR biomass index-based approach for tree- and plot-level biomass mapping over forest farms using 3D point clouds" (2023, Remote Sensing of Environment)

Their collaborative network includes frequent coauthors such as Jiaming Lu, Wenjuan Shen, Jiaying He, Tao He, and Megan Lang. These collaborations represent ongoing partnerships across multiple research projects.

  • Jiaming Lu
  • Wenjuan Shen
  • Jiaying He
  • Tao He
  • Megan Lang

Overall, Chengquan Huang's research integrates advanced remote sensing technologies and deep learning to address various environmental challenges, focusing particularly on forest ecosystems, land use changes, and the impact of environmental factors on ecosystems at multiple spatial scales.

Best Publications

  • An assessment of support vector machines for land cover classification

    C. Huang;L. S. Davis;J. R. G. Townshend

  • Development of a 2001 National land-cover database for the United States

    Collin G. Homer;Chengquan Huang;Limin Yang;Bruce K. Wylie

  • An automated approach for reconstructing recent forest disturbance history using dense Landsat time series stacks

    Chengquan Huang;Samuel N. Goward;Jeffrey G. Masek;Nancy Thomas

  • Derivation of a tasselled cap transformation based on Landsat 7 at-satellite reflectance

    Chengquan Huang;Bruce K. Wylie;Limin Yang;Collin G. Homer

  • Global, 30-m resolution continuous fields of tree cover: Landsat-based rescaling of MODIS vegetation continuous fields with lidar-based estimates of error

    Joseph O. Sexton;Xiao-Peng Song;Min Feng;Praveen Noojipady

  • An approach for mapping large-area impervious surfaces: synergistic use of Landsat-7 ETM+ and high spatial resolution imagery

    Limin Yang;Chengquan Huang;Collin G Homer;Bruce K Wylie

  • North American forest disturbance mapped from a decadal Landsat record

    Jeffrey G. Masek;Chengquan Huang;Robert Wolfe;Warren Cohen

  • Rapid and robust monitoring of flood events using Sentinel-1 and Landsat data on the Google Earth Engine

    Ben DeVries;Ben DeVries;Chengquan Huang;John Armston;Wenli Huang;Wenli Huang

  • Global Characterization and Monitoring of Forest Cover Using Landsat Data: Opportunities and Challenges

    John R. Townshend;Jeffrey G. Masek;ChengQuan Huang;Eric F. Vermote

  • Use of a dark object concept and support vector machines to automate forest cover change analysis

    Chengquan Huang;Kuan Song;Sunghee Kim;John R.G. Townshend

  • Annual Global Automated MODIS Vegetation Continuous Fields (MOD44B) at 250 m Spatial Resolution for Data Years Beginning Day 65, 2000 - 2010

    C.M. DiMiceli;M.L. Carroll;R.A. Sohlberg;C. Huang

  • Urban growth of the Washington, D.C.–Baltimore, MD metropolitan region from 1984 to 2010 by annual, Landsat-based estimates of impervious cover

    Joseph O. Sexton;Xiao-Peng Song;Chengquan Huang;Saurabh Channan

  • Forest disturbance across the conterminous United States from 1985-2012: The emerging dominance of forest decline

    Warren B. Cohen;Zhiqiang Yang;Stephen V. Stehman;Todd A. Schroeder

  • Global, Landsat-based forest-cover change from 1990 to 2000

    Do-Hyung Kim;Joseph O. Sexton;Praveen Noojipady;Chengquan Huang

  • Mapping forest change using stacked generalization: An ensemble approach

    Sean P. Healey;Warren B. Cohen;Zhiqiang Yang;C. Kenneth Brewer

  • Beware of per-pixel characterization of land cover

    J. R. G. Townshend;C. Huang;S. N. V. Kalluri;R. S. Defries

  • Characterizing the magnitude, timing and duration of urban growth from time series of Landsat-based estimates of impervious cover

    Xiao-Peng Song;Joseph O. Sexton;Chengquan Huang;Saurabh Channan

  • Wetland inundation mapping and change monitoring using Landsat and airborne LiDAR data

    Chengquan Huang;Yi Peng;Megan Lang;In-Young Yeo

  • Automated Extraction of Surface Water Extent from Sentinel-1 Data

    Wenli Huang;Ben DeVries;Chengquan Huang;Megan W. Lang

  • Conservation policy and the measurement of forests

    Joseph O. Sexton;Praveen Noojipady;Praveen Noojipady;Praveen Noojipady;Xiao-Peng Song;Min Feng

  • Observations and assessment of forest carbon dynamics following disturbance in North America

    Scott J. Goetz;Benjamin Bond-Lamberty;Beverly E. Law;J. Hicke

  • Impact of sensor's point spread function on land cover characterization: Assessment and deconvolution

    Chengquan Huang;John R.G. Townshend;Shunlin Liang;Satya N.V. Kalluri

Frequent Co-Authors

John R. Townshend
John R. Townshend University of Maryland, College Park
Jeffrey G. Masek
Jeffrey G. Masek Goddard Space Flight Center
Samuel N. Goward
Samuel N. Goward University of Maryland, College Park
Warren B. Cohen
Warren B. Cohen Oregon State University
Sean P. Healey
Sean P. Healey US Forest Service
Robert E. Kennedy
Robert E. Kennedy Oregon State University
Zhiliang Zhu
Zhiliang Zhu United States Geological Survey
Ralph Dubayah
Ralph Dubayah University of Maryland, College Park
Ruth S. DeFries
Ruth S. DeFries Columbia University
George C. Hurtt
George C. Hurtt University of Maryland, College Park

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