World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
45
Citations
6671
World Ranking
7306
National Ranking
51

Yifang Ban 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 Yifang Ban 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: 206 publications — 48th percentile

48% of scientists in this discipline score the same or lower.

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

Yifang Ban 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 Yifang Ban 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: 45 D-Index — 51st percentile

51% of scientists in this discipline score the same or lower.

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

Overview

Yifang Ban is affiliated with the Royal Institute of Technology in Sweden and specializes in Environmental Science and Engineering. Their research predominantly addresses areas within Global and Planetary Change, Atmospheric Science, Media Technology, Ecology, and Computer Vision and Pattern Recognition. The scientist's work integrates advanced remote sensing technologies and deep learning techniques applied to environmental monitoring and land use assessment.

The scientific output includes frequent contributions to journals and conferences such as:

  • arXiv (Cornell University)
  • IEEE Transactions on Geoscience and Remote Sensing
  • International Journal of Applied Earth Observation and Geoinformation
  • Remote Sensing
  • IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium

Their research topics reflect an emphasis on remote sensing applications in various environmental contexts, including:

  • Remote-Sensing Image Classification
  • Fire effects on ecosystems
  • Remote Sensing in Agriculture
  • Remote Sensing and Land Use
  • Flood Risk Assessment and Management
  • Land Use and Ecosystem Services
  • Remote Sensing and LiDAR Applications

Yifang Ban has collaborated frequently with a group of co-authors, which includes:

  • Andrea Nascetti
  • Sebastian Häfner
  • Ritu Yadav
  • Puzhao Zhang
  • Yu Zhao

Recent publications highlight the application of remote sensing and deep learning in environmental monitoring and wildfire detection. Some notable recent papers include:

  • "Multisource Data Reconstruction-Based Deep Unsupervised Hashing for Unisource Remote Sensing Image Retrieval" (2022), IEEE Transactions on Geoscience and Remote Sensing
  • "Near Real-Time Wildfire Progression Monitoring with Sentinel-1 SAR Time Series and Deep Learning" (2020), Scientific Reports
  • "Sentinel-1 InSAR Coherence for Land Cover Mapping: A Comparison of Multiple Feature-Based Classifiers" (2020), IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  • "Learning U-Net without forgetting for near real-time wildfire monitoring by the fusion of SAR and optical time series" (2021), Remote Sensing of Environment
  • "Uni-Temporal Multispectral Imagery for Burned Area Mapping with Deep Learning" (2021), Remote Sensing

Best Publications

  • Multisource Data Reconstruction-Based Deep Unsupervised Hashing for Unisource Remote Sensing Image Retrieval

    Unknown

  • Complex Network Topology of Transportation Systems

    Jingyi Lin;Yifang Ban

  • Global land cover mapping using Earth observation satellite data: Recent progresses and challenges

    Yifang Ban;Peng Gong;Chandra Giri

  • Near Real-Time Wildfire Progression Monitoring with Sentinel-1 SAR Time Series and Deep Learning.

    Yifang Ban;Puzhao Zhang;Andrea Nascetti;Alexandre R. Bevington

  • Multitemporal Spaceborne SAR Data for Urban Change Detection in China

    Yifang Ban;O. A. Yousif

  • Simulation and analysis of urban growth scenarios for the Greater Shanghai Area, China

    Qian Zhang;Yifang Ban;Jiyuan Liu;Yunfeng Hu

  • Fusion of Quickbird MS and RADARSAT SAR data for urban land-cover mapping: object-based and knowledge-based approach

    Yifang Ban;Hongtao Hu;I. M. Rangel

  • Multi-temporal RADARSAT-2 polarimetric SAR data for urban land-cover classification using an object-based support vector machine and a rule-based approach

    Xin Niu;Yifang Ban

  • Spaceborne SAR data for global urban mapping at 30 m resolution using a robust urban extractor

    Yifang Ban;Alexander Jacob;Paolo Gamba

  • Improving Urban Change Detection From Multitemporal SAR Images Using PCA-NLM

    O. Yousif;Yifang Ban

  • Dimensionality Reduction and Feature Selection for Object-Based Land Cover Classification based on Sentinel-1 and Sentinel-2 Time Series Using Google Earth Engine

    Oliver Stromann;Andrea Nascetti;Osama A. Yousif;Yifang Ban

  • Synergy of multitemporal ERS-1 SAR and Landsat TM data for classification of agricultural crops

    Yifang Ban

  • Improving SAR-Based Urban Change Detection by Combining MAP-MRF Classifier and Nonlocal Means Similarity Weights

    Osama Yousif;Yifang Ban

  • Unsupervised Change Detection in Multitemporal SAR Images Over Large Urban Areas

    Hongtao Hu;Yifang Ban

  • Object-Based Fusion of Multitemporal Multiangle ENVISAT ASAR and HJ-1B Multispectral Data for Urban Land-Cover Mapping

    Yifang Ban;A. Jacob

  • Sentinel-1 InSAR Coherence for Land Cover Mapping: A Comparison of Multiple Feature-Based Classifiers

    Alexander W. Jacob;Claudia Notarnicola;Gopika Suresh;Oleg Antropov

  • Learning U-Net without forgetting for near real-time wildfire monitoring by the fusion of SAR and optical time series

    Puzhao Zhang;Yifang Ban;Andrea Nascetti

  • Uni-Temporal Multispectral Imagery for Burned Area Mapping with Deep Learning

    Xikun Hu;Yifang Ban;Andrea Nascetti

  • GCDB-UNet: A novel robust cloud detection approach for remote sensing images

    Unknown

  • Continuous Monitoring of Urban Land Cover Change Trajectories with Landsat Time Series and LandTrendr-Google Earth Engine Cloud Computing

    Theodomir Mugiraneza;Andrea Nascetti;Yifang Ban

  • A multiple representation data structure for dynamic visualisation of generalised 3D city models

    Bo Mao;Yifang Ban;Lars Harrie

  • The evolving network structure of US airline system during 1990–2010

    Jingyi Lin;Yifang Ban

  • Sentinel-1A SAR and sentinel-2A MSI data fusion for urban ecosystem service mapping

    Jan Haas;Yifang Ban

  • Urban Observing Sensors

    Q. Weng;P. Gamba;G. Mountrakis;M. Pesaresi

  • Sentinel-2 MSI data for active fire detection in major fire-prone biomes: A multi-criteria approach

    Xikun Hu;Yifang Ban;Andrea Nascetti

Frequent Co-Authors

Paolo Gamba
Paolo Gamba University of Pavia
Peijun Du
Peijun Du Nanjing University
Jiyuan Liu
Jiyuan Liu Chinese Academy of Sciences
Zheng Niu
Zheng Niu Chinese Academy of Sciences
Peng Gong
Peng Gong University of Hong Kong
Maoguo Gong
Maoguo Gong Xidian University
Gavin D. Perkins
Gavin D. Perkins University of Warwick
Qihao Weng
Qihao Weng Hong Kong Polytechnic University
Janet E. Nichol
Janet E. Nichol University of Sussex
Michael Oppenheimer
Michael Oppenheimer Princeton University

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