World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
60
Citations
14473
World Ranking
3238
National Ranking
434

Overview

Cheng Wang is a researcher affiliated with Xiamen University in China, with a focus primarily on Environmental Science. Their work spans several subfields including Environmental Engineering, Ecology, Global and Planetary Change, Geology, and Nature and Landscape Conservation.

The scientist's research topics encompass a range of areas within remote sensing and environmental monitoring. These include:

  • Remote Sensing and LiDAR Applications
  • Remote Sensing in Agriculture
  • 3D Surveying and Cultural Heritage
  • Forest Ecology and Management
  • Forest Management and Policy
  • Advanced Optical Sensing Technologies
  • Cryospheric Studies and Observations

Wang has published extensively in journals notable for remote sensing and earth observation studies. Common publication venues include:

  • Remote Sensing
  • Remote Sensing of Environment
  • Zenodo (CERN European Organization for Nuclear Research)
  • International Journal of Applied Earth Observation and Geoinformation
  • IEEE Geoscience and Remote Sensing Letters

Some of their recent published papers are:

  • A Noise Removal Algorithm Based on OPTICS for Photon-Counting LiDAR Data (2020) in IEEE Geoscience and Remote Sensing Letters
  • Retrieving building height in urban areas using ICESat-2 photon-counting LiDAR data (2021) in International Journal of Applied Earth Observation and Geoinformation
  • A Comparative Study of Water Indices and Image Classification Algorithms for Mapping Inland Surface Water Bodies Using Landsat Imagery (2020) in Remote Sensing
  • Mapping forest height using photon-counting LiDAR data and Landsat 8 OLI data: A case study in Virginia and North Carolina, USA (2020) in Ecological Indicators
  • Comprehensive LiDAR simulation with efficient physically-based DART-Lux model (I): Theory, novelty, and consistency validation (2022) in Remote Sensing of Environment

Wang has collaborated frequently with several coauthors, including:

  • Xiaohuan Xi
  • Sheng Nie
  • Xiaoxiao Zhu
  • Xuebo Yang
  • Jinliang Wang

Best Publications

  • GMAN: A Graph Multi-Attention Network for Traffic Prediction

    Chuanpan Zheng;Xiaoliang Fan;Cheng Wang;Jianzhong Qi

  • FAIR1M: A Benchmark Dataset for Fine-grained Object Recognition in High-Resolution Remote Sensing Imagery

    Unknown

  • deep learning on 3D point clouds

    Unknown

  • Using mobile laser scanning data for automated extraction of road markings

    Haiyan Guan;Jonathan Li;Jonathan Li;Yongtao Yu;Cheng Wang

  • Environmental Epidemiology, Volume 1: Public Health and Hazardous Wastes

    Unknown

  • QT interval variability in body surface ECG: measurement, physiological basis, and clinical value: position statement and consensus guidance endorsed by the European Heart�…

    Unknown

  • A novel extended local-binary-pattern operator for texture analysis

    Hui Zhou;Runsheng Wang;Cheng Wang

  • Voltammetric studies of the oxygen-titanium binary system in molten calcium chloride

    Unknown

  • LO-Net: Deep Real-Time Lidar Odometry

    Qing Li;Shaoyang Chen;Cheng Wang;Xin Li

  • Mobile Laser Scanned Point-Clouds for Road Object Detection and Extraction: A Review

    Lingfei Ma;Ying Li;Jonathan Li;Cheng Wang

  • Road extraction in remote sensing data: A survey

    Unknown

  • Semiautomated Extraction of Street Light Poles From Mobile LiDAR Point-Clouds

    Yongtao Yu;Jonathan Li;Haiyan Guan;Cheng Wang

  • Automated Road Information Extraction From Mobile Laser Scanning Data

    Haiyan Guan;Jonathan Li;Yongtao Yu;Michael Chapman

  • Learning Hierarchical Features for Automated Extraction of Road Markings From 3-D Mobile LiDAR Point Clouds

    Yongtao Yu;Jonathan Li;Haiyan Guan;Fukai Jia

  • Toward better boundary preserved supervoxel segmentation for 3D point clouds

    Yangbin Lin;Cheng Wang;Dawei Zhai;Wei Li

  • NormalNet: A voxel-based CNN for 3D object classification and retrieval

    Cheng Wang;Ming Cheng;Ferdous Sohel;Mohammed Bennamoun

  • PBNet: Part-based convolutional neural network for complex composite object detection in remote sensing imagery

    Xian Sun;Peijin Wang;Cheng Wang;Yingfei Liu

  • A deep learning framework for road marking extraction, classification and completion from mobile laser scanning point clouds

    Chenglu Wen;Xiaotian Sun;Jonathan Li;Jonathan Li;Cheng Wang

  • 3D Multi-Object Tracking in Point Clouds Based on Prediction Confidence-Guided Data Association

    Hai Wu;Wenkai Han;Chenglu Wen;Xin Li

  • Line segment extraction for large scale unorganized point clouds

    Yangbin Lin;Cheng Wang;Jun Cheng;Bili Chen

  • CasA: A Cascade Attention Network for 3-D Object Detection From LiDAR Point Clouds

    Unknown

  • Vehicle Detection in High-Resolution Aerial Images via Sparse Representation and Superpixels

    Ziyi Chen;Cheng Wang;Chenglu Wen;Xiuhua Teng

  • LiDAR-Video Driving Dataset: Learning Driving Policies Effectively

    Yiping Chen;Jingkang Wang;Jonathan Li;Cewu Lu

  • Review of research progress on the electrical properties and modification of mineral insulating oils used in power transformers

    Unknown

Frequent Co-Authors

Jonathan Li
Jonathan Li University of Waterloo
Yongtao Yu
Yongtao Yu Huaiyin Institute of Technology
See Leang Chin
See Leang Chin Université Laval
xin li
xin li Louisiana State University
Ying Wu
Ying Wu Northwestern University
Yulan Guo
Yulan Guo Sun Yat-sen University
Naser El-Sheimy
Naser El-Sheimy University of Calgary
Guangxiao Yang
Guangxiao Yang Huazhong University of Science and Technology
Guangyuan He
Guangyuan He Huazhong University of Science and Technology
Jiaqi Liu
Jiaqi Liu Chinese Academy of Sciences

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

Exploring online degrees opens exciting pathways beyond traditional computer science programs. Many students consider earning a computer science degree online, which allows for flexible scheduling, accelerated completion, and access to innovative coursework—all without the need to relocate.

Online education also supports interdisciplinary studies. For example, combining computer science with environmental fields can broaden your career options. If you’re interested in jobs that bridge education and sustainability, it’s worth looking into jobs with elementary education and environmental science degree backgrounds, which can range from teaching to environmental advocacy.

Engineering degrees are also widely available online. Those curious about building sustainable infrastructure may consider enrolling at environmental engineering schools online, which focus on solving global environmental challenges.

If you’re comparing costs, the mechanical engineering cost of education is another important factor to examine. Affordability and flexibility make online mechanical engineering programs popular for working professionals seeking advancement.

Best Scientists Citing Cheng Wang

Trending Scientists

Recently Published Articles