Guangxing Wang
Orcid: 0000-0002-5419-4547Affiliations:
- Southern Illinois University Carbondale, Carbondale, IL, USA
According to our database1,
Guangxing Wang authored at least 39 papers
between 2013 and 2021.
Collaborative distances:
Collaborative distances:
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Bibliography
2021
Assessing the impacts of anthropogenic drainage structures on hydrologic connectivity using high-resolution digital elevation models.
Trans. GIS, 2021
Editorial Summary, Remote Sensing Special Issue "Advances in Remote Sensing for Global Forest Monitoring".
Remote. Sens., 2021
2020
Improving Estimation of Forest Canopy Cover by Introducing Loss Ratio of Laser Pulses Using Airborne LiDAR.
IEEE Trans. Geosci. Remote. Sens., 2020
Design of an Integrated Remote and Ground Sensing Monitor System for Assessing Farmland Quality.
Sensors, 2020
Estimating the Growing Stem Volume of the Planted Forest Using the General Linear Model and Time Series Quad-Polarimetric SAR Images.
Sensors, 2020
Estimating the Growing Stem Volume of Coniferous Plantations Based on Random Forest Using an Optimized Variable Selection Method.
Sensors, 2020
Prediction of Individual Tree Diameter and Height to Crown Base Using Nonlinear Simultaneous Regression and Airborne LiDAR Data.
Remote. Sens., 2020
Deep Learning Segmentation and Classification for Urban Village Using a Worldview Satellite Image Based on U-Net.
Remote. Sens., 2020
Improving Estimation of Soil Moisture Content Using a Modified Soil Thermal Inertia Model.
Remote. Sens., 2020
Analysis of the Spatial Differences in Canopy Height Models from UAV LiDAR and Photogrammetry.
Remote. Sens., 2020
Estimating the Growing Stem Volume of Chinese Pine and Larch Plantations based on Fused Optical Data Using an Improved Variable Screening Method and Stacking Algorithm.
Remote. Sens., 2020
A Modified KNN Method for Mapping the Leaf Area Index in Arid and Semi-Arid Areas of China.
Remote. Sens., 2020
Prediction of Individual Tree Diameter Using a Nonlinear Mixed-Effects Modeling Approach and Airborne LiDAR Data.
Remote. Sens., 2020
2019
The Optimal Image Date Selection for Evaluating Cultivated Land Quality Based on Gaofen-1 Images.
Sensors, 2019
The GA-BPNN-Based Evaluation of Cultivated Land Quality in the PSR Framework Using Gaofen-1 Satellite Data.
Sensors, 2019
Correction: Zhang, M., et al. Estimation of Vegetation Productivity Using a Landsat 8 Time Series in a Heavily Urbanized Area, Central China. <i>Remote Sens.</i> 2019, <i>11</i>, 133.
Remote. Sens., 2019
Improving the Estimation of Forest Carbon Density in Mountainous Regions Using Topographic Correction and Landsat 8 Images.
Remote. Sens., 2019
Airborne LIDAR-Derived Aboveground Biomass Estimates Using a Hierarchical Bayesian Approach.
Remote. Sens., 2019
Improving Forest Aboveground Biomass Estimation of Pinus densata Forest in Yunnan of Southwest China by Spatial Regression using Landsat 8 Images.
Remote. Sens., 2019
Improving Aboveground Biomass Estimation of <i>Pinus densata</i> Forests in Yunnan Using Landsat 8 Imagery by Incorporating Age Dummy Variable and Method Comparison.
Remote. Sens., 2019
Mapping Growing Stem Volume of Chinese Fir Plantation Using a Saturation-based Multivariate Method and Quad-polarimetric SAR Images.
Remote. Sens., 2019
A Probability-Based Spectral Unmixing Analysis for Mapping Percentage Vegetation Cover of Arid and Semi-Arid Areas.
Remote. Sens., 2019
Prediction of Soil Nutrient Contents Using Visible and Near-Infrared Reflectance Spectroscopy.
ISPRS Int. J. Geo Inf., 2019
2018
Mapping Paddy Rice Using a Convolutional Neural Network (CNN) with Landsat 8 Datasets in the Dongting Lake Area, China.
Remote. Sens., 2018
Optimizing kNN for Mapping Vegetation Cover of Arid and Semi-Arid Areas Using Landsat Images.
Remote. Sens., 2018
Improving Selection of Spectral Variables for Vegetation Classification of East Dongting Lake, China, Using a Gaofen-1 Image.
Remote. Sens., 2018
Comparative Analysis of Modeling Algorithms for Forest Aboveground Biomass Estimation in a Subtropical Region.
Remote. Sens., 2018
Development of a System of Compatible Individual Tree Diameter and Aboveground Biomass Prediction Models Using Error-In-Variable Regression and Airborne LiDAR Data.
Remote. Sens., 2018
Detection of charcoal rot (<i>Macrophomina phaseolina</i>) toxin effects in soybean (<i>Glycine</i> max) seedlings using hyperspectral spectroscopy.
Comput. Electron. Agric., 2018
2017
Mapping Forest Ecosystem Biomass Density for Xiangjiang River Basin by Combining Plot and Remote Sensing Data and Comparing Spatial Extrapolation Methods.
Remote. Sens., 2017
2016
Examining Spectral Reflectance Saturation in Landsat Imagery and Corresponding Solutions to Improve Forest Aboveground Biomass Estimation.
Remote. Sens., 2016
Multi-Resolution Mapping and Accuracy Assessment of Forest Carbon Density by Combining Image and Plot Data from a Nested and Clustering Sampling Design.
Remote. Sens., 2016
A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems.
Int. J. Digit. Earth, 2016
Forest aboveground biomass estimation in Zhejiang Province using the integration of Landsat TM and ALOS PALSAR data.
Int. J. Appl. Earth Obs. Geoinformation, 2016
2015
Increasing the Accuracy of Mapping Urban Forest Carbon Density by Combining Spatial Modeling and Spectral Unmixing Analysis.
Remote. Sens., 2015
Improvement of Forest Carbon Estimation by Integration of Regression Modeling and Spectral Unmixing of Landsat Data.
IEEE Geosci. Remote. Sens. Lett., 2015
Retrieval and Accuracy Assessment of Tree and Stand Parameters for Chinese Fir Plantation Using Terrestrial Laser Scanning.
IEEE Geosci. Remote. Sens. Lett., 2015
2013
Impacts of Plot Location Errors on Accuracy of Mapping and Scaling Up Aboveground Forest Carbon Using Sample Plot and Landsat TM Data.
IEEE Geosci. Remote. Sens. Lett., 2013