World's Best Scientists 2026 revealed!
Qunming Wang

Qunming Wang

D-Index & Metrics

Computer Science

D-Index
39
Citations
6017
World Ranking
9804
National Ranking
1229

Qunming Wang publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Qunming Wang sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 110 publications — 11th percentile

11% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Qunming Wang D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Qunming Wang sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 39 D-Index — 33rd percentile

33% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Qunming Wang is affiliated with Tongji University in China and has contributed extensively to the fields of engineering and environmental science. Their research primarily focuses on areas such as media technology, atmospheric science, ecology, computer vision and pattern recognition, and environmental engineering.

The main topics covered by their work include advanced image fusion techniques, remote-sensing image classification, remote sensing applications in agriculture and land use, soil moisture monitoring through remote sensing, cryospheric studies, and the use of LiDAR in remote sensing.

Wang has published in several prominent journals, with frequent appearances in:

  • IEEE Transactions on Geoscience and Remote Sensing
  • Remote Sensing of Environment
  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  • International Journal of Applied Earth Observation and Geoinformation
  • ISPRS Journal of Photogrammetry and Remote Sensing

Recent papers authored by Wang include:

  • "Virtual image pair-based spatio-temporal fusion" (2020), published in Remote Sensing of Environment
  • "Spatio-temporal spectral unmixing of time-series images" (2021), published in Remote Sensing of Environment
  • "Remote sensing image gap filling based on spatial-spectral random forests" (2022), published in Science of Remote Sensing

Collaboratively, Wang has frequently worked alongside researchers such as Peter M. Atkinson, Xiaohua Tong, Liguo Wang, Yijie Tang, and Haoxuan Yang, with collaboration counts ranging from 10 to 40 coauthored works.

Best Publications

  • Water bodies' mapping from Sentinel-2 imagery with Modified Normalized Difference Water Index at 10-m spatial resolution produced by sharpening the swir band

    Yun Du;Yihang Zhang;Feng Ling;Qunming Wang

  • Multisource and Multitemporal Data Fusion in Remote Sensing: A Comprehensive Review of the State of the Art

    Pedram Ghamisi;Behnood Rasti;Naoto Yokoya;Qunming Wang

  • Spatio-temporal fusion for daily Sentinel-2 images

    Qunming Wang;Peter M. Atkinson;Peter M. Atkinson;Peter M. Atkinson

  • Fusion of Sentinel-2 images

    Qunming Wang;Wenzhong Shi;Zhongbin Li;Peter Michael Atkinson;Peter Michael Atkinson;Peter Michael Atkinson

  • Fusion of Landsat 8 OLI and Sentinel-2 MSI Data

    Qunming Wang;George Alan Blackburn;Alex O. Onojeghuo;Jadunandan Dash

  • Downscaling MODIS images with area-to-point regression kriging

    Qunming Wang;Wenzhong Shi;Peter Michael Atkinson;Peter Michael Atkinson;Peter Michael Atkinson;Yuanling Zhao

  • Landslide mapping from aerial photographs using change detection-based Markov random field

    Zhongbin Li;Zhongbin Li;Wenzhong Shi;Ping Lu;Lin Yan

  • Mapping paddy rice fields by applying machine learning algorithms to multi-temporal Sentinel-1A and Landsat data

    Alex Okiemute Onojeghuo;George Alan Blackburn;Qunming Wang;Peter Michael Atkinson

  • Sub-pixel mapping of remote sensing images based on radial basis function interpolation

    Qunming Wang;Wenzhong Shi;Peter M. Atkinson

  • Semi-automated landslide inventory mapping from bitemporal aerial photographs using change detection and level set method

    Zhongbin Li;Wen Zhong Shi;Soe W. Myint;Ping Lu

  • Semi-supervised classification for hyperspectral imagery based on spatial-spectral Label Propagation

    Liguo Wang;Siyuan Hao;Qunming Wang;Ying Wang

  • Land Cover Change Detection at Subpixel Resolution With a Hopfield Neural Network

    Qunming Wang;Wenzhong Shi;Peter M. Atkinson;Zhongbin Li

  • Virtual image pair-based spatio-temporal fusion

    Qunming Wang;Yijie Tang;Xiaohua Tong;Peter M. Atkinson;Peter M. Atkinson

  • Spectral–Spatial Classification and Shape Features for Urban Road Centerline Extraction

    Wenzhong Shi;Zelang Miao;Qunming Wang;Hua Zhang

  • Allocating Classes for Soft-Then-Hard Subpixel Mapping Algorithms in Units of Class

    Qunming Wang;Wenzhong Shi;Liguo Wang

  • Particle swarm optimization-based sub-pixel mapping for remote-sensing imagery

    Qunming Wang;Liguo Wang;Danfeng Liu

  • SSA-SiamNet: Spectral-Spatial-Wise Attention-Based Siamese Network for Hyperspectral Image Change Detection

    Lifeng Wang;Liguo Wang;Qunming Wang;Peter M. Atkinson

  • A Novel Adaptive Fuzzy Local Information $C$ -Means Clustering Algorithm for Remotely Sensed Imagery Classification

    Hua Zhang;Qunming Wang;Wenzhong Shi;Ming Hao

  • Area-to-point regression kriging for pan-sharpening

    Qunming Wang;Qunming Wang;Wenzhong Shi;Peter Michael Atkinson;Peter Michael Atkinson;Peter Michael Atkinson

  • Seamless downscaling of the ESA CCI soil moisture data at the daily scale with MODIS land products

    Wei Zhao;Fengping Wen;Qunming Wang;Nilda Sanchez

  • Multisource and Multitemporal Data Fusion in Remote Sensing.

    Pedram Ghamisi;Behnood Rasti;Naoto Yokoya;Qunming Wang

Frequent Co-Authors

Peter M. Atkinson
Peter M. Atkinson Lancaster University
Wenzhong Shi
Wenzhong Shi Hong Kong Polytechnic University
Xiaohua Tong
Xiaohua Tong Tongji University
Xiaodong Li
Xiaodong Li Hunan University
Lorenzo Bruzzone
Lorenzo Bruzzone University of Trento
Naoto Yokoya
Naoto Yokoya University of Tokyo
Jon Atli Benediktsson
Jon Atli Benediktsson University of Iceland
Francesca Bovolo
Francesca Bovolo Fondazione Bruno Kessler
Richard Gloaguen
Richard Gloaguen Helmholtz-Zentrum Dresden-Rossendorf
Yuxin Miao
Yuxin Miao University of Minnesota

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

If you’re interested in Computer Science but have concerns about your academic background, there are online graduate schools with low gpa requirements that can help you take the next step without compromising on quality. These institutions provide flexible entry options and support a diverse range of students.

Looking to complete your studies quickly? Consider an accelerated computer science degree online. These programs allow you to earn your credentials faster and start building your career sooner.

Computer Science also pairs well with other fields. For example, combining it with environmental science can open up unique opportunities. Curious about potential roles in this area? Explore what can i do with an environmental science degree for insight into interdisciplinary career paths.

Interested in engineering and sustainability? An environmental engineer degree online is an affordable way to enter a growing field where computing skills are increasingly valuable.

Best Scientists Citing Qunming Wang

Trending Scientists

Recently Published Articles