Yanjun Su
Orcid: 0000-0001-7931-339X
According to our database1,
Yanjun Su
authored at least 31 papers
between 2015 and 2024.
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Bibliography
2024
Segmenting Individual Trees From Terrestrial LiDAR Data Using Tree Branch Directivity.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024
2023
Function of CD8<sup>+</sup>, conventional CD4<sup>+</sup>, and regulatory CD4<sup>+</sup> T cell identification in lung cancer.
Comput. Biol. Medicine, June, 2023
Extraction of Wheat Spike Phenotypes From Field-Collected Lidar Data and Exploration of Their Relationships With Wheat Yield.
IEEE Trans. Geosci. Remote. Sens., 2023
2022
Remote. Sens., 2022
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 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
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
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
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
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
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
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
Remote. Sens., 2015
SRTM DEM Correction in Vegetated Mountain Areas through the Integration of Spaceborne LiDAR, Airborne LiDAR, and Optical Imagery.
Remote. Sens., 2015