Fusion of full-waveform lidar and imaging spectroscopy remote sensing data for the characterization of forest stands-Reference-Cited by-同舟云学术

Fusion of full-waveform lidar and imaging spectroscopy remote sensing data for the characterization of forest stands

Published:2013-04-02 Issue:13 Volume:34 Page:4511-4524
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Buddenbaum Henning¹,Seeling Stephan¹,Hill Joachim¹

Affiliation:

1. Environmental Remote Sensing and Geoinformatics, University of Trier, 54286, Trier, Germany

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2013.776721

Reference52 articles.

1. Integrating waveform lidar with hyperspectral imagery for inventory of a northern temperate forest

2. Classification of coniferous tree species and age classes using hyperspectral data and geostatistical methods

3. Forest canopy height from the Multiangle Imaging SpectroRadiometer (MISR) assessed with high resolution discrete return lidar

4. Cocks, T., R. Jenssen, A. Stewart, I. Wilson, and T. Shields. 1998. “The HyMap Airborne Hyperspectral Sensor: The System, Calibration and Performance.” In 1st EARSEL Workshop on Imaging Spectroscopy, Zurich, Switzerland, October 6–8.

5. Radiometric correction in laser scanning

Cited by 41 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Hybrid model for estimating forest canopy heights using fused multimodal spaceborne LiDAR data and optical imagery;International Journal of Applied Earth Observation and Geoinformation;2023-08

2. Tree Species Classification in a Complex Brazilian Tropical Forest Using Hyperspectral and LiDAR Data;Forests;2023-05-04

3. Forestry Big Data: A Review and Bibliometric Analysis;Forests;2022-09-22

4. UAV-Based Multi-Sensor Data Fusion for Urban Land Cover Mapping Using a Deep Convolutional Neural Network;Remote Sensing;2022-08-31

5. Classification of Laser Footprint Based on Random Forest in Mountainous Area Using GLAS Full-Waveform Features;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2022