Identifying the genus or species of individual trees using a three-wavelength airborne lidar system
BC Budei, B St-Onge, C Hopkinson, FA Audet - Remote Sensing of …, 2018 - Elsevier
The identification of individual tree species is crucial for forest inventory, carbon stocks
assessment as well as for habitat and ecosystem change studies. Previous studies have …
assessment as well as for habitat and ecosystem change studies. Previous studies have …
[HTML][HTML] Multispectral light detection and ranging technology and applications: a review
N Takhtkeshha, G Mandlburger, F Remondino… - Sensors, 2024 - mdpi.com
Light Detection and Ranging (LiDAR) is a well-established active technology for the direct
acquisition of 3D data. In recent years, the geometric information collected by LiDAR …
acquisition of 3D data. In recent years, the geometric information collected by LiDAR …
[HTML][HTML] Object-based analysis of multispectral airborne laser scanner data for land cover classification and map updating
L Matikainen, K Karila, J Hyyppä, P Litkey… - ISPRS Journal of …, 2017 - Elsevier
During the last 20 years, airborne laser scanning (ALS), often combined with passive
multispectral information from aerial images, has shown its high feasibility for automated …
multispectral information from aerial images, has shown its high feasibility for automated …
[HTML][HTML] AGFP-Net: Attentive geometric feature pyramid network for land cover classification using airborne multispectral LiDAR data
Accurate land cover (LC) classification plays an important role in ecosystem protection,
climate changes, and urban planning. The airborne multispectral LiDAR data are …
climate changes, and urban planning. The airborne multispectral LiDAR data are …
[HTML][HTML] Three dimensional change detection using point clouds: A review
A Kharroubi, F Poux, Z Ballouch, R Hajji, R Billen - Geomatics, 2022 - mdpi.com
Change detection is an important step for the characterization of object dynamics at the
earth's surface. In multi-temporal point clouds, the main challenge is to detect true changes …
earth's surface. In multi-temporal point clouds, the main challenge is to detect true changes …
[HTML][HTML] Introducing improved transformer to land cover classification using multispectral LiDAR point clouds
Z Zhang, T Li, X Tang, X Lei, Y Peng - Remote Sensing, 2022 - mdpi.com
The use of Transformer-based networks has been proposed for the processing of general
point clouds. However, there has been little research related to multispectral LiDAR point …
point clouds. However, there has been little research related to multispectral LiDAR point …
Integrated change detection and classification in urban areas based on airborne laser scanning point clouds
THG Tran, C Ressl, N Pfeifer - Sensors, 2018 - mdpi.com
This paper suggests a new approach for change detection (CD) in 3D point clouds. It
combines classification and CD in one step using machine learning. The point cloud data of …
combines classification and CD in one step using machine learning. The point cloud data of …
[HTML][HTML] Exploring multispectral ALS data for tree species classification
A Axelsson, E Lindberg, H Olsson - Remote Sensing, 2018 - mdpi.com
Multispectral Airborne Laser Scanning (ALS) is a new technology and its output data have
not been fully explored for tree species classification purposes. The objective of this study …
not been fully explored for tree species classification purposes. The objective of this study …
A comparative land-cover classification feature study of learning algorithms: DBM, PCA, and RF using multispectral LiDAR data
Multispectral LiDAR, characterization of completeness, and consistency of spectrum and
spatial geometric data provide a new data source for land cover classification. However …
spatial geometric data provide a new data source for land cover classification. However …
Supervised spatial classification of multispectral LiDAR data in urban areas
LZ Huo, CA Silva, C Klauberg, M Mohan, LJ Zhao… - PloS one, 2018 - journals.plos.org
Multispectral LiDAR (light detection and ranging) data have been initially used for land cover
classification. However, there are still high classification uncertainties, especially in urban …
classification. However, there are still high classification uncertainties, especially in urban …