Qin Ma

Orcid: 0000-0002-6995-6663

Affiliations:
  • Mississippi State University, Department of Forestry, Starkville, MS, USA
  • University of California at Merced, School of Engineering, Sierra Nevada Research Institute, CA, USA


According to our database1, Qin Ma authored at least 11 papers between 2015 and 2021.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

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

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

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

2018
Canopy Effects on Snow Accumulation: Observations from Lidar, Canonical-View Photos, and Continuous Ground Measurements from Sensor Networks.
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

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

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

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


  Loading...