Qi Chen
Orcid: 0000-0003-0110-7996Affiliations:
- University of Hawaii at Manoa, Department of Geography, Honolulu, HI, USA
According to our database1,
Qi Chen
authored at least 19 papers
between 2013 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
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Bibliography
2024
Assessment of the influence of UAV-borne LiDAR scan angle and flight altitude on the estimation of wheat structural metrics with different leaf angle distributions.
Comput. Electron. Agric., 2024
A fully convolutional neural network model combined with a Hough transform to extract crop breeding field plots from UAV images.
Int. J. Appl. Earth Obs. Geoinformation, 2024
2020
Estimating aboveground and organ biomass of plant canopies across the entire season of rice growth with terrestrial laser scanning.
Int. J. Appl. Earth Obs. Geoinformation, 2020
2019
Remote. Sens., 2019
A Hierarchical unsupervised method for power line classification from airborne LiDAR data.
Int. J. Digit. Earth, 2019
Detection of wheat height using optimized multi-scan mode of LiDAR during the entire growth stages.
Comput. Electron. Agric., 2019
2018
Determining the Mechanisms that Influence the Surface Temperature of Urban Forest Canopies by Combining Remote Sensing Methods, Ground Observations, and Spatial Statistical Models.
Remote. Sens., 2018
Individual and Interactive Influences of Anthropogenic and Ecological Factors on Forest PM<sub>2.5</sub> Concentrations at an Urban Scale.
Remote. Sens., 2018
Systematic Comparison of Power Line Classification Methods from ALS and MLS Point Cloud Data.
Remote. Sens., 2018
A Forest Attribute Mapping Framework: A Pilot Study in a Northern Boreal Forest, Northwest Territories, Canada.
Remote. Sens., 2018
Comparative Analysis of Modeling Algorithms for Forest Aboveground Biomass Estimation in a Subtropical Region.
Remote. Sens., 2018
2017
Estimation of Wheat LAI at Middle to High Levels Using Unmanned Aerial Vehicle Narrowband Multispectral Imagery.
Remote. Sens., 2017
Remote. Sens., 2017
Potential of ALOS2 and NDVI to Estimate Forest Above-Ground Biomass, and Comparison with Lidar-Derived Estimates.
Remote. Sens., 2017
Examining effective use of data sources and modeling algorithms for improving biomass estimation in a moist tropical forest of the Brazilian Amazon.
Int. J. Digit. Earth, 2017
2016
Modeling and Mapping Agroforestry Aboveground Biomass in the Brazilian Amazon Using Airborne Lidar Data.
Remote. Sens., 2016
A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems.
Int. J. Digit. Earth, 2016
Above ground biomass and tree species richness estimation with airborne lidar in tropical Ghana forests.
Int. J. Appl. Earth Obs. Geoinformation, 2016
2013
Optical and SAR sensor synergies for forest and land cover mapping in a tropical site in West Africa.
Int. J. Appl. Earth Obs. Geoinformation, 2013