World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

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

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
Qihao Weng
Qihao Weng Hong Kong Polytechnic University
Janet E. Nichol
Janet E. Nichol University of Sussex
Maoguo Gong
Maoguo Gong Xidian University
Paul Treitz
Paul Treitz Queen's University
Michael Oppenheimer
Michael Oppenheimer Princeton University

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