[HTML][HTML] lidR: An R package for analysis of Airborne Laser Scanning (ALS) data
Airborne laser scanning (ALS) is a remote sensing technology known for its applicability in
natural resources management. By quantifying the three-dimensional structure of vegetation …
natural resources management. By quantifying the three-dimensional structure of vegetation …
Review of studies on tree species classification from remotely sensed data
Spatially explicit information on tree species composition of managed and natural forests,
plantations and urban vegetation provides valuable information for nature conservationists …
plantations and urban vegetation provides valuable information for nature conservationists …
Individual tree segmentation and tree species classification in subtropical broadleaf forests using UAV-based LiDAR, hyperspectral, and ultrahigh-resolution RGB data
Accurate classification of individual tree species is essential for inventorying, managing, and
protecting forest resources. Individual tree species classification in subtropical forests …
protecting forest resources. Individual tree species classification in subtropical forests …
Lidar sheds new light on plant phenomics for plant breeding and management: Recent advances and future prospects
Plant phenomics is a new avenue for linking plant genomics and environmental studies,
thereby improving plant breeding and management. Remote sensing techniques have …
thereby improving plant breeding and management. Remote sensing techniques have …
Allometric equations for integrating remote sensing imagery into forest monitoring programmes
Remote sensing is revolutionizing the way we study forests, and recent technological
advances mean we are now able–for the first time–to identify and measure the crown …
advances mean we are now able–for the first time–to identify and measure the crown …
Registration of laser scanning point clouds: A review
The integration of multi-platform, multi-angle, and multi-temporal LiDAR data has become
important for geospatial data applications. This paper presents a comprehensive review of …
important for geospatial data applications. This paper presents a comprehensive review of …
Urban tree species mapping using hyperspectral and lidar data fusion
In this study we fused high-spatial resolution (3.7 m) hyperspectral imagery with 22 pulse/m
2 lidar data at the individual crown object scale to map 29 common tree species in Santa …
2 lidar data at the individual crown object scale to map 29 common tree species in Santa …
A review of tree species classification based on airborne LiDAR data and applied classifiers
M Michałowska, J Rapiński - Remote Sensing, 2021 - mdpi.com
Remote sensing techniques, developed over the past four decades, have enabled large-
scale forest inventory. Light Detection and Ranging (LiDAR), as an active remote sensing …
scale forest inventory. Light Detection and Ranging (LiDAR), as an active remote sensing …
Tree species classification of drone hyperspectral and RGB imagery with deep learning convolutional neural networks
Interest in drone solutions in forestry applications is growing. Using drones, datasets can be
captured flexibly and at high spatial and temporal resolutions when needed. In forestry …
captured flexibly and at high spatial and temporal resolutions when needed. In forestry …
Tree‐centric mapping of forest carbon density from airborne laser scanning and hyperspectral data
M Dalponte, DA Coomes - Methods in ecology and evolution, 2016 - Wiley Online Library
Forests are a major component of the global carbon cycle, and accurate estimation of forest
carbon stocks and fluxes is important in the context of anthropogenic global change …
carbon stocks and fluxes is important in the context of anthropogenic global change …