World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
31
Citations
4353
World Ranking
13621
National Ranking
5437

Overview

Guangxing Wang is affiliated with Southern Illinois University Carbondale in the United States. Their research primarily spans the field of Environmental Science, with a focus on several specialized subfields including Environmental Engineering, Ecology, Global and Planetary Change, Nature and Landscape Conservation, and Atmospheric Science.

The scientist's work covers multiple research topics that reflect both their broad and specific interests. These topics include:

  • Remote Sensing and LiDAR Applications
  • Remote Sensing in Agriculture
  • Forest ecology and management
  • Land Use and Ecosystem Services
  • Physical Activity and Health
  • Hydrology and Sediment Transport Processes
  • Hydrology and Watershed Management Studies

Guangxing Wang frequently publishes in several scientific journals. The main publication venues are:

  • Remote Sensing
  • Sensors
  • International Journal of Remote Sensing
  • Forests
  • SSRN Electronic Journal

The scientist has been involved in multiple research papers with varied themes. Some recent publications include:

  • "Deep Learning Segmentation and Classification for Urban Village Using a Worldview Satellite Image Based on U-Net," 2020, Remote Sensing
  • "Associations of Daily Steps and Step Intensity With Incident Diabetes in a Prospective Cohort Study of Older Women: The OPACH Study," 2022, Diabetes Care
  • "Estimating the Growing Stem Volume of Coniferous Plantations Based on Random Forest Using an Optimized Variable Selection Method," 2020, Sensors
  • "Feasibility of a behavioral intervention using mobile health applications to reduce cardiovascular risk factors in cancer survivors: a pilot randomized controlled trial," 2020, Journal of Cancer Survivorship
  • "Identification of the critical accident causative factors in the urban rail transit system by complex network theory," 2022, Physica A Statistical Mechanics and its Applications

Collaborations form a significant part of Guangxing Wang's research output. Frequent co-authors include:

  • Chongzhi Di
  • Kelly R. Evenson
  • Ruopu Li
  • Andrea Z. LaCroix
  • John Bellettiere

Best Publications

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

    Dengsheng Lu;Qi Chen;Guangxing Wang;Lijuan Liu

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

    Dengsheng Lu;Qi Chen;Guangxing Wang;Emilio Moran

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

    Panpan Zhao;Dengsheng Lu;Guangxing Wang;Chuping Wu

  • Mapping Multiple Variables for Predicting Soil Loss by Geostatistical Methods with TM Images and a Slope Map

    Guangxing Wang;George Gertner;Shoufan Fang;Alan B. Anderson

  • Deep Learning Segmentation and Classification for Urban Village Using a Worldview Satellite Image Based on U-Net

    Zhuokun Pan;Jiashu Xu;Yubin Guo;Yueming Hu

  • Improvement in mapping vegetation cover factor for the universal soil loss equation by geostatistical methods with Landsat Thematic Mapper images

    G. Wang;S. Wente;G. Z. Gertner;A. Anderson

  • Comparative Analysis of Modeling Algorithms for Forest Aboveground Biomass Estimation in a Subtropical Region

    Yukun Gao;Dengsheng Lu;Guiying Li;Guangxing Wang

  • Mapping Paddy Rice Using a Convolutional Neural Network (CNN) with Landsat 8 Datasets in the Dongting Lake Area, China

    Meng Zhang;Hui Lin;Guangxing Wang;Hua Sun

  • Multipath analysis of code measurements for BeiDou geostationary satellites

    Guangxing Wang;Kees Jong;Qile Zhao;Zhigang Hu

  • Forest aboveground biomass estimation in Zhejiang Province using the integration of Landsat TM and ALOS PALSAR data

    Panpan Zhao;Dengsheng Lu;Guangxing Wang;Lijuan Liu

  • Phenology-based classification of vegetation cover types in Northeast China using MODIS NDVI and EVI time series

    Enping Yan;Guangxing Wang;Hui Lin;Chaozong Xia

  • Mapping and spatial uncertainty analysis of forest vegetation carbon by combining national forest inventory data and satellite images

    Guangxing Wang;Tonny Oyana;Maozhen Zhang;Samuel Adu-Prah

  • The geography of ecosystem service value: The case of the Des Plaines and Cache River wetlands, Illinois

    Justin Kozak;Christopher L. Lant;Sabina Shaikh;Guangxing Wang

  • The calibration of digitized aerial photographs for forest stratification

    Markus Holopainen;Guangxing Wang

  • Remote sensing of natural resources

    Guangxing Wang;Qihao Weng

  • Estimation of Soil Heavy Metal Content Using Hyperspectral Data

    Zhenhua Liu;Ying Lu;Yiping Peng;Li Zhao

  • Estimation Methods for Soil Mercury Content Using Hyperspectral Remote Sensing

    Li Zhao;Yue-Ming Hu;Wu Zhou;Zhen-Hua Liu

  • Diagnosis and Prediction of Traffic Congestion on Urban Road Networks Using Bayesian Networks

    Unknown

  • Mapping and uncertainty of predictions based on multiple primary variables from joint co-simulation with Landsat TM image and polynomial regression

    George Gertner;Guangxing Wang;Shoufan Fang;Alan B. Anderson

  • A Methodology for Spatial Uncertainty Analysis Of Remote Sensing and GIS Products

    Guangxing Wang;George Z. Gertner;Shoufan Fang;Alan B. Anderson

  • Effect and uncertainty of digital elevation model spatial resolutions on predicting the topographical factor for soil loss estimation

    George Gertner;Guangxing Wang;Shoufan Fang;Alan B. Anderson

  • Integrating a Hybrid Back Propagation Neural Network and Particle Swarm Optimization for Estimating Soil Heavy Metal Contents Using Hyperspectral Data

    Piao Liu;Zhenhua Liu;Yueming Hu;Zhou Shi

  • Mapping Forest Ecosystem Biomass Density for Xiangjiang River Basin by Combining Plot and Remote Sensing Data and Comparing Spatial Extrapolation Methods

    Jia Zhu;Zhihong Huang;Hua Sun;Guangxing Wang

  • Improving Aboveground Biomass Estimation of Pinus densata Forests in Yunnan Using Landsat 8 Imagery by Incorporating Age Dummy Variable and Method Comparison

    Guanglong Ou;Chao Li;Yanyu Lv;Anchao Wei

  • Determination of earthquake magnitude using GPS displacement waveforms from real-time precise point positioning

    Rongxin Fang;Chuang Shi;Weiwei Song;Guangxing Wang

  • Estimating the Growing Stem Volume of Coniferous Plantations Based on Random Forest Using an Optimized Variable Selection Method.

    Fugen Jiang;Mykola Kutia;Arbi J Sarkissian;Hui Lin

  • Prediction of soil properties using a hyperspectral remote sensing method

    Huan Yu;Huan Yu;Bo Kong;Guangxing Wang;Rongxiang Du

Frequent Co-Authors

Hui Lin
Hui Lin Jiangxi Normal University
Qile Zhao
Qile Zhao Wuhan University
Dengsheng Lu
Dengsheng Lu Fujian Normal University
Zhou Shi
Zhou Shi Zhejiang University
Qi Chen
Qi Chen University of Hawaii at Manoa
Chuang Shi
Chuang Shi Wuhan University
Ronald E. McRoberts
Ronald E. McRoberts University of Minnesota
Qihao Weng
Qihao Weng Hong Kong Polytechnic University
Emilio F. Moran
Emilio F. Moran Michigan State University
Erkki Tomppo
Erkki Tomppo University of Helsinki

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