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Environmental Sciences
China
2023

D-Index & Metrics

Environmental Sciences

D-Index
68
Citations
29678
World Ranking
1836
National Ranking
172

Dengsheng Lu 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 Dengsheng Lu 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: 180 publications — 56th percentile

56% of scientists in this discipline score the same or lower.

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

Dengsheng Lu 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 Dengsheng Lu 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: 68 D-Index — 81st percentile

81% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2023 - Research.com Environmental Sciences in China Leader Award

Overview

Dengsheng Lu is affiliated with Fujian Normal University in China and focuses research efforts predominantly within the field of Environmental Science, with particular attention to several subfields. These include Ecology, Environmental Engineering, Global and Planetary Change, Nature and Landscape Conservation, and Soil Science.

The scientist's work covers multiple topics related to remote sensing and environmental management. Key areas of research include:

  • Remote Sensing in Agriculture
  • Remote Sensing and LiDAR Applications
  • Land Use and Ecosystem Services
  • Forest ecology and management
  • Remote Sensing and Land Use
  • Forest Ecology and Biodiversity Studies
  • Species Distribution and Climate Change

Publication output is distributed across various venues, with frequent appearances in the following journals:

  • Remote Sensing
  • GIScience & Remote Sensing
  • Geo-spatial Information Science
  • Forests
  • Forest Ecosystems

Among recent papers authored or co-authored by Dengsheng Lu are:

  • "Cropland redistribution to marginal lands undermines environmental sustainability" (2021, National Science Review)
  • "A 30 m resolution dataset of China's urban impervious surface area and green space, 2000-2018" (2021, Earth System Science Data)
  • "Global observation of urban expansion and land-cover dynamics using satellite big-data" (2020, Science Bulletin)
  • "Stratification-Based Forest Aboveground Biomass Estimation in a Subtropical Region Using Airborne Lidar Data" (2020, Remote Sensing)
  • "Examining the Roles of Spectral, Spatial, and Topographic Features in Improving Land-Cover and Forest Classifications in a Subtropical Region" (2020, Remote Sensing)

Dengsheng Lu collaborates frequently with a group of co-authors, including:

  • Guiying Li
  • Dengqiu Li
  • Xiandie Jiang
  • Yaoliang Chen
  • Wenhui Kuang

Best Publications

  • Change detection techniques

    D. Lu;P. Mausel;E. Moran

  • A survey of image classification methods and techniques for improving classification performance

    D. Lu;Q. Weng

  • Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies

    Qihao Weng;Dengsheng Lu;Jacquelyn Schubring

  • The potential and challenge of remote sensing‐based biomass estimation

    Dengsheng Lu

  • Use of impervious surface in urban land-use classification

    Dengsheng Lu;Qihao Weng

  • A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems

    Dengsheng Lu;Qi Chen;Guangxing Wang;Lijuan Liu

  • Aboveground biomass estimation using Landsat TM data in the Brazilian Amazon

    D. Lu

  • Spectral Mixture Analysis of the Urban Landscape in Indianapolis with Landsat ETM+ Imagery

    Dengsheng Lu;Qihao Weng

  • Relationships between forest stand parameters and Landsat TM spectral responses in the Brazilian Amazon Basin

    Dengsheng Lu;Paul Mausel;Eduardo Brondı́zio;Emilio Moran

  • Mapping soil erosion risk in Rondônia, Brazilian Amazonia: using RUSLE, remote sensing and GIS

    D. Lu;G. Li;G. S. Valladares;M. Batistella

  • Assessment of atmospheric correction methods for Landsat TM data applicable to Amazon basin LBA research

    D. Lu;P. Mausel;E. Brondizio;E. Moran

  • Regional mapping of human settlements in southeastern China with multisensor remotely sensed data

    Dengsheng Lu;Hanqin Tian;Guomo Zhou;Hongli Ge

  • Linear mixture model applied to Amazonian vegetation classification

    Dengsheng Lu;Emilio Moran;Mateus Batistella;Mateus Batistella

  • A sub-pixel analysis of urbanization effect on land surface temperature and its interplay with impervious surface and vegetation coverage in Indianapolis, United States

    Qihao Weng;Dengsheng Lu

  • Aboveground Forest Biomass Estimation with Landsat and LiDAR Data and Uncertainty Analysis of the Estimates

    Dengsheng Lu;Qi Chen;Guangxing Wang;Emilio Moran

  • A comparative analysis of megacity expansions in China and the U.S.: Patterns, rates and driving forces

    Wenhui Kuang;Wenfeng Chi;Dengsheng Lu;Yinyin Dou

  • Urban classification using full spectral information of landsat ETM+ imagery in Marion County, Indiana

    Dengsheng Lu;Qihao Weng

  • Spectral mixture analysis of ASTER images for examining the relationship between urban thermal features and biophysical descriptors in Indianapolis, Indiana, USA

    Dengsheng Lu;Qihao Weng

  • Examining Spectral Reflectance Saturation in Landsat Imagery and Corresponding Solutions to Improve Forest Aboveground Biomass Estimation

    Panpan Zhao;Dengsheng Lu;Guangxing Wang;Chuping Wu

  • Land Cover Classification in a Complex Urban-Rural Landscape with Quickbird Imagery.

    Dengsheng Lu;Scott Hetrick;Emilio Moran

  • Aboveground biomass estimation using Landsat TM data in the

    Brazilian Amazon;D. Lu

Frequent Co-Authors

Emilio F. Moran
Emilio F. Moran Michigan State University
Mateus Batistella
Mateus Batistella Brazilian Agricultural Research Corporation
Qihao Weng
Qihao Weng Hong Kong Polytechnic University
Guangxing Wang
Guangxing Wang Southern Illinois University Carbondale
Eduardo S. Brondizio
Eduardo S. Brondizio Indiana University
Qi Chen
Qi Chen University of Hawaii at Manoa
Chi Zhang
Chi Zhang Linyi University
Jiyuan Liu
Jiyuan Liu Chinese Academy of Sciences
Hanqin Tian
Hanqin Tian Auburn University
Guangsheng Chen
Guangsheng Chen Zhejiang A & F University

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