Qinghua Guo

Orcid: 0000-0002-1065-0838

Affiliations:
  • Chinese Academy of Sciences, State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Beijing, China
  • University of California Merced, Sierra Nevada Research Institute, School of Engineering, CA, USA


According to our database1, Qinghua Guo authored at least 50 papers between 2003 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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Online presence:

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Bibliography

2024
TTSR: A Transformer-Based Topography Neural Network for Digital Elevation Model Super-Resolution.
IEEE Trans. Geosci. Remote. Sens., 2024

Segmenting Individual Trees From Terrestrial LiDAR Data Using Tree Branch Directivity.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024

2022
Loess Landslide Detection Using Object Detection Algorithms in Northwest China.
Remote. Sens., 2022

LiDAR Reveals the Process of Vision-Mediated Predator-Prey Relationships.
Remote. Sens., 2022

2021
One-Class Remote Sensing Classification From Positive and Unlabeled Background Data.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021

Development and Performance Evaluation of a Very Low-Cost UAV-Lidar System for Forestry Applications.
Remote. Sens., 2021

The Development and Evaluation of a Backpack LiDAR System for Accurate and Efficient Forest Inventory.
IEEE Geosci. Remote. Sens. Lett., 2021

2020
Separating the Structural Components of Maize for Field Phenotyping Using Terrestrial LiDAR Data and Deep Convolutional Neural Networks.
IEEE Trans. Geosci. Remote. Sens., 2020

A Novel Framework to Automatically Fuse Multiplatform LiDAR Data in Forest Environments Based on Tree Locations.
IEEE Trans. Geosci. Remote. Sens., 2020

A Framework for Land Use Scenes Classification Based on Landscape Photos.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2020

A Point-Based Fully Convolutional Neural Network for Airborne LiDAR Ground Point Filtering in Forested Environments.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2020

An Impartial Semi-Supervised Learning Strategy for Imbalanced Classification on VHR Images.
Sensors, 2020

Mapping the Global Mangrove Forest Aboveground Biomass Using Multisource Remote Sensing Data.
Remote. Sens., 2020

Estimating aboveground biomass of the mangrove forests on northeast Hainan Island in China using an upscaling method from field plots, UAV-LiDAR data and Sentinel-2 imagery.
Int. J. Appl. Earth Obs. Geoinformation, 2020

ADMorph: A 3D Digital Microfossil Morphology Dataset for Deep Learning.
IEEE Access, 2020

2019
Stem-Leaf Segmentation and Phenotypic Trait Extraction of Individual Maize Using Terrestrial LiDAR Data.
IEEE Trans. Geosci. Remote. Sens., 2019

The Influence of Vegetation Characteristics on Individual Tree Segmentation Methods with Airborne LiDAR Data.
Remote. Sens., 2019

An Object-Based Strategy for Improving the Accuracy of Spatiotemporal Satellite Imagery Fusion for Vegetation-Mapping Applications.
Remote. Sens., 2019

Efficiency of Extreme Gradient Boosting for Imbalanced Land Cover Classification Using an Extended Margin and Disagreement Performance.
ISPRS Int. J. Geo Inf., 2019

A simple and integrated approach for fire severity assessment using bi-temporal airborne LiDAR data.
Int. J. Appl. Earth Obs. Geoinformation, 2019

2018
Retrieving 2-D Leaf Angle Distributions for Deciduous Trees From Terrestrial Laser Scanner Data.
IEEE Trans. Geosci. Remote. Sens., 2018

An Ensemble of Classifiers Based on Positive and Unlabeled Data in One-Class Remote Sensing Classification.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2018

Evaluating the Performance of Sentinel-2, Landsat 8 and Pléiades-1 in Mapping Mangrove Extent and Species.
Remote. Sens., 2018

Artificial Mangrove Species Mapping Using Pléiades-1: An Evaluation of Pixel-Based and Object-Based Classifications with Selected Machine Learning Algorithms.
Remote. Sens., 2018

Impact of Error in Lidar-Derived Canopy Height and Canopy Base Height on Modeled Wildfire Behavior in the Sierra Nevada, California, USA.
Remote. Sens., 2018

The Transferability of Random Forest in Canopy Height Estimation from Multi-Source Remote Sensing Data.
Remote. Sens., 2018

Quantifying individual tree growth and tree competition using bi-temporal airborne laser scanning data: a case study in the Sierra Nevada Mountains, California.
Int. J. Digit. Earth, 2018

The Integration of Uavand Backpack Lidar Systems for Forest Inventory.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

Retrieving the Leaf area Index of Individual Trees and Stands using Single-Scan Data From a Terrestrial Laser Scanner.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

Individual Tree Level Forest Fire Assessment Using Bi-temporal LiDAR Data.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

2017
Comparison of Canopy Cover Estimations From Airborne LiDAR, Aerial Imagery, and Satellite Imagery.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2017

Mapping Regional Urban Extent Using NPP-VIIRS DNB and MODIS NDVI Data.
Remote. Sens., 2017

One-Class Classification of Airborne LiDAR Data in Urban Areas Using a Presence and Background Learning Algorithm.
Remote. Sens., 2017

Fine-resolution forest tree height estimation across the Sierra Nevada through the integration of spaceborne LiDAR, airborne LiDAR, and optical imagery.
Int. J. Digit. Earth, 2017

2016
Mapping Global Forest Aboveground Biomass with Spaceborne LiDAR, Optical Imagery, and Forest Inventory Data.
Remote. Sens., 2016

2015
Mapping US Urban Extents from MODIS Data Using One-Class Classification Method.
Remote. Sens., 2015

SRTM DEM Correction in Vegetated Mountain Areas through the Integration of Spaceborne LiDAR, Airborne LiDAR, and Optical Imagery.
Remote. Sens., 2015

2014
Restoration of Information Obscured by Mountainous Shadows Through Landsat TM/ETM+ Images Without the Use of DEM Data: A New Method.
IEEE Trans. Geosci. Remote. Sens., 2014

A New Accuracy Assessment Method for One-Class Remote Sensing Classification.
IEEE Trans. Geosci. Remote. Sens., 2014

Space-time analyses for forecasting future incident occurrence: a case study from Yosemite National Park using the presence and background learning algorithm.
Int. J. Geogr. Inf. Sci., 2014

2013
Delineating Individual Trees from Lidar Data: A Comparison of Vector- and Raster-based Segmentation Approaches.
Remote. Sens., 2013

2012
A software framework for classification models of geographical data.
Comput. Geosci., 2012

2011
A Positive and Unlabeled Learning Algorithm for One-Class Classification of Remote-Sensing Data.
IEEE Trans. Geosci. Remote. Sens., 2011

Georeferencing Incidents from Locality Descriptions and its Applications: a Case Study from Yosemite National Park Search and Rescue.
Trans. GIS, 2011

Predicting potential distributions of geographic events using one-class data: concepts and methods.
Int. J. Geogr. Inf. Sci., 2011

2008
Towards a General Field model and its order in GIS.
Int. J. Geogr. Inf. Sci., 2008

Georeferencing locality descriptions and computing associated uncertainty using a probabilistic approach.
Int. J. Geogr. Inf. Sci., 2008

2007
Modeling the risk for a new invasive forest disease in the United States: An evaluation of five environmental niche models.
Comput. Environ. Urban Syst., 2007

2004
The point-radius method for georeferencing locality descriptions and calculating associated uncertainty.
Int. J. Geogr. Inf. Sci., 2004

2003
Predicting distribution of a new forest disease using one-class SVMs.
Proceedings of the 3rd IEEE International Conference on Data Mining (ICDM 2003), 2003


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