ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1702.06188
  4. Cited By
Forest understory trees can be segmented accurately within sufficiently
  dense airborne laser scanning point clouds

Forest understory trees can be segmented accurately within sufficiently dense airborne laser scanning point clouds

17 February 2017
Hamid Hamraz
M. Contreras
Jun Zhang
ArXivPDFHTML

Papers citing "Forest understory trees can be segmented accurately within sufficiently dense airborne laser scanning point clouds"

3 / 3 papers shown
Title
A robust approach for tree segmentation in deciduous forests using
  small-footprint airborne LiDAR data
A robust approach for tree segmentation in deciduous forests using small-footprint airborne LiDAR data
Hamid Hamraz
M. Contreras
Jun Zhang
17
80
0
01 Jan 2017
A scalable approach for tree segmentation within small-footprint
  airborne LiDAR data
A scalable approach for tree segmentation within small-footprint airborne LiDAR data
Hamid Hamraz
M. Contreras
Jun Zhang
20
16
0
01 Jan 2017
Vertical stratification of forest canopy for segmentation of under-story
  trees within small-footprint airborne LiDAR point clouds
Vertical stratification of forest canopy for segmentation of under-story trees within small-footprint airborne LiDAR point clouds
Hamid Hamraz
M. Contreras
Jun Zhang
3DPC
18
84
0
31 Dec 2016
1