World's Best Scientists 2026 revealed!

D-Index & Metrics

Environmental Sciences

D-Index
41
Citations
7729
World Ranking
7632
National Ranking
726

Hongliang Fang 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 Hongliang Fang 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: 99 publications — 13th percentile

13% of scientists in this discipline score the same or lower.

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

Hongliang Fang 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 Hongliang Fang 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: 41 D-Index — 22nd percentile

22% of scientists in this discipline score the same or lower.

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

Overview

Hongliang Fang is a researcher affiliated with the Chinese Academy of Sciences in China. Their primary field of study is Environmental Science, with a focused body of work in Ecology, Global and Planetary Change, Environmental Engineering, Plant Science, and Nature and Landscape Conservation.

The research of Hongliang Fang spans various topics within environmental science, emphasizing Remote Sensing in Agriculture, Remote Sensing and LiDAR Applications, Plant Water Relations and Carbon Dynamics, Leaf Properties and Growth Measurement, Land Use and Ecosystem Services, Forest Ecology and Management, and Urban Heat Island Mitigation.

Frequent co-authors collaborating with Hongliang Fang include:

  • Yao Wang
  • Sijia Li
  • Yinghui Zhang
  • Yu Li
  • Tian Ma

The main publication venues where Hongliang Fang's work appears most frequently are:

  • Remote Sensing
  • Agricultural and Forest Meteorology
  • Science of Remote Sensing
  • Remote Sensing of Environment
  • SSRN Electronic Journal

Representative recent papers authored or co-authored by Hongliang Fang include:

  • "Estimation of LAI with the LiDAR Technology: A Review," 2020, Remote Sensing
  • "Canopy clumping index (CI): A review of methods, characteristics, and applications," 2021, Agricultural and Forest Meteorology
  • "A Bibliometric Visualization Review of the MODIS LAI/FPAR Products from 1995 to 2020," 2021, Journal of Remote Sensing
  • "Critical analysis of methods to estimate the fraction of absorbed or intercepted photosynthetically active radiation from ground measurements: Application to rice crops," 2020, Agricultural and Forest Meteorology
  • "Vegetation coverage of desert ecosystems in the Qinghai-Tibet Plateau is underestimated," 2022, Ecological Indicators

Best Publications

  • An Overview of Global Leaf Area Index (LAI): Methods, Products, Validation, and Applications

    Hongliang Fang;Frédéric Baret;Stephen Plummer;Gabriela Schaepman-Strub

  • Atmospheric correction of Landsat ETM+ land surface imagery. I. Methods

    S. Liang;H. Fang;M. Chen

  • Validating MODIS land surface reflectance and albedo products: methods and preliminary results

    Shunlin Liang;Hongliang Fang;Mingzhen Chen;Chad J Shuey

  • Narrowband to broadband conversions of land surface albedo: II. Validation

    Shunlin Liang;Chad J Shuey;Andrew L Russ;Hongliang Fang

  • Retrieving leaf area index using a genetic algorithm with a canopy radiative transfer model

    Hongliang Fang;Shunlin Liang;Andres Kuusk

  • Validation of MODIS and CYCLOPES LAI products using global field measurement data

    Hongliang Fang;Shanshan Wei;Shanshan Wei;Shunlin Liang;Shunlin Liang

  • Estimation of incident photosynthetically active radiation from Moderate Resolution Imaging Spectrometer data

    Shunlin Liang;Tao Zheng;Ronggao Liu;Hongliang Fang

  • A comparison of empirical and neural network approaches for estimating corn and soybean leaf area index from Landsat ETM+ imagery ☆

    Charles Walthall;Wayne Dulaney;Martha Anderson;John Norman

  • Inconsistencies of interannual variability and trends in long-term satellite leaf area index products

    Chongya Jiang;Youngryel Ryu;Hongliang Fang;Ranga Myneni

  • Corn-yield estimation through assimilation of remotely sensed data into the CSM-CERES-Maize model

    Hongliang Fang;Shunlin Liang;Gerrit Hoogenboom;John Teasdale

  • Integration of MODIS LAI and vegetation index products with the CSM-CERES-Maize model for corn yield estimation

    Hongliang Fang;Shunlin Liang;Gerrit Hoogenboom

  • Characterization and intercomparison of global moderate resolution leaf area index (LAI) products: Analysis of climatologies and theoretical uncertainties

    Hongliang Fang;Chongya Jiang;Wenjuan Li;Shanshan Wei

  • A hybrid inversion method for mapping leaf area index from MODIS data: experiments and application to broadleaf and needleleaf canopies

    Hongliang Fang;Shunlin Liang

  • Retrieving leaf area index with a neural network method: simulation and validation

    Hongliang Fang;Shunlin Liang

  • Atmospheric correction of Landsat ETM+ land surface imagery. II. Validation and applications

    Shunlin Liang;Hongliang Fang;J.T. Morisette;Mingzhen Chen

  • Spatially and temporally continuous LAI data sets based on an integrated filtering method: Examples from North America

    Hongliang Fang;Shunlin Liang;John R. Townshend;Robert Earl Dickinson

  • Theoretical uncertainty analysis of global MODIS, CYCLOPES, and GLOBCARBON LAI products using a triple collocation method

    Hongliang Fang;Shanshan Wei;Shanshan Wei;Chongya Jiang;Klaus Scipal

  • Atmospheric correction of Landsat ETM+ land surface imagery: Part I: Methods

    Shunlin Liang;Hongliang Fang;Mingzhen Chen

  • Seasonal variation of leaf area index (LAI) over paddy rice fields in NE China: Intercomparison of destructive sampling, LAI-2200, digital hemispherical photography (DHP), and AccuPAR methods

    Hongliang Fang;Wenjuan(李文娟) Li;Shanshan Wei;Chongya Jiang

  • Using NOAA AVHRR and landsat TM to estimate rice area year-by-year

    Hongliang Fang;Bingfang Wu;Haiyan Liu;Xuan Huang

Frequent Co-Authors

Shunlin Liang
Shunlin Liang University of Hong Kong
Craig S. T. Daughtry
Craig S. T. Daughtry Agricultural Research Service
Jing M. Chen
Jing M. Chen University of Toronto
Frédéric Baret
Frédéric Baret INRAE : Institut national de recherche pour l'agriculture, l'alimentation et l'environnement
Robert E. Dickinson
Robert E. Dickinson The University of Texas at Austin
Ranga B. Myneni
Ranga B. Myneni Boston University
Gerrit Hoogenboom
Gerrit Hoogenboom University of Florida
Bernard Longdoz
Bernard Longdoz University of Liège
Stefan K. Arndt
Stefan K. Arndt University of Melbourne
Youngryel Ryu
Youngryel Ryu Seoul National University

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