Ting Yun
Orcid: 0000-0003-4294-8337
According to our database1,
Ting Yun
authored at least 18 papers
between 2014 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
On csauthors.net:
Bibliography
2024
Synergizing a Deep Learning and Enhanced Graph-Partitioning Algorithm for Accurate Individual Rubber Tree-Crown Segmentation from Unmanned Aerial Vehicle Light-Detection and Ranging Data.
Remote. Sens., August, 2024
Status, advancements and prospects of deep learning methods applied in forest studies.
Int. J. Appl. Earth Obs. Geoinformation, 2024
Early identification of immature rubber plantations using Landsat and Sentinel satellite images.
Int. J. Appl. Earth Obs. Geoinformation, 2024
Improving the accuracy of canopy height mapping in rubber plantations based on stand age, multi-source satellite images, and random forest algorithm.
Int. J. Appl. Earth Obs. Geoinformation, 2024
2023
Comparison of Different Important Predictors and Models for Estimating Large-Scale Biomass of Rubber Plantations in Hainan Island, China.
Remote. Sens., July, 2023
2022
Integrating Real Tree Skeleton Reconstruction Based on Partial Computational Virtual Measurement (CVM) with Actual Forest Scenario Rendering: A Solid Step Forward for the Realization of the Digital Twins of Trees and Forests.
Remote. Sens., December, 2022
Correction: Chen et al. High-Precision Stand Age Data Facilitate the Estimation of Rubber Plantation Biomass: A Case Study of Hainan Island, China. Remote Sens. 2020, 12, 3853.
Remote. Sens., 2022
2021
Separation of Wood and Foliage for Trees From Ground Point Clouds Using a Novel Least-Cost Path Model.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021
2020
Retrieval of Aerodynamic Parameters in Rubber Tree Forests Based on the Computer Simulation Technique and Terrestrial Laser Scanning Data.
Remote. Sens., 2020
2019
IEEE Trans. Geosci. Remote. Sens., 2019
Rubber Tree Crown Segmentation and Property Retrieval Using Ground-Based Mobile LiDAR after Natural Disturbances.
Remote. Sens., 2019
Extraction of Leaf Biophysical Attributes Based on a Computer Graphic-based Algorithm Using Terrestrial Laser Scanning Data.
Remote. Sens., 2019
Estimating Tree Volume Distributions in Subtropical Forests Using Airborne LiDAR Data.
Remote. Sens., 2019
A Flexible Architecture for Extracting Metro Tunnel Cross Sections from Terrestrial Laser Scanning Point Clouds.
Remote. Sens., 2019
2016
Remote. Sens., 2016
Aboveground Biomass Estimation of Individual Trees in a Coastal Planted Forest Using Full-Waveform Airborne Laser Scanning Data.
Remote. Sens., 2016
2014
Super-resolution scatterometer image reconstruction using total variation regularization method.
Proceedings of the 2014 IEEE Geoscience and Remote Sensing Symposium, 2014