Estimation of wetland vegetation height and leaf area index using airborne laser scanning data

2015 ◽  
Vol 48 ◽  
pp. 550-559 ◽  
Author(s):  
Shezhou Luo ◽  
Cheng Wang ◽  
Feifei Pan ◽  
Xiaohuan Xi ◽  
Guicai Li ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Laser Scanning ◽  
Wetland Vegetation ◽  
Airborne Laser Scanning ◽  
Area Index ◽  
Vegetation Height ◽  
Airborne Laser

Derivation, Validation, and Sensitivity Analysis of Terrestrial Laser Scanning-Based Leaf Area Index

2016 ◽  
Vol 42 (6) ◽  
pp. 719-729 ◽  
Author(s):  
Yumei Li ◽  
Qinghua Guo ◽  
Shengli Tao ◽  
Guang Zheng ◽  
Kaiguang Zhao ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Area Index

scholarly journals Categorizing Wetland Vegetation by Airborne Laser Scanning on Lake Balaton and Kis-Balaton, Hungary

2012 ◽  
Vol 4 (6) ◽  
pp. 1617-1650 ◽  
Author(s):  
András Zlinszky ◽  
Werner Mücke ◽  
Hubert Lehner ◽  
Christian Briese ◽  
Norbert Pfeifer
Keyword(s):  
Laser Scanning ◽  
Wetland Vegetation ◽  
Airborne Laser Scanning ◽  
Lake Balaton ◽  
Airborne Laser

scholarly journals Determining leaf area index and leafy tree roughness using terrestrial laser scanning

2010 ◽  
Vol 46 (6) ◽  
Author(s):  
A. S. Antonarakis ◽  
K. S. Richards ◽  
J. Brasington ◽  
E. Muller
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Area Index

scholarly journals EcoDes-DK15: High-resolution ecological descriptors of vegetation and terrain derived from Denmark's national airborne laser scanning data set

2021 ◽  
Author(s):  
Jakob J. Assmann ◽  
Jesper E. Moeslund ◽  
Urs A. Treier ◽  
Signe Normand
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Airborne Laser Scanning ◽  
Data Sets ◽  
Ecosystem Structure ◽  
Data Set ◽  
Vegetation Height ◽  
Airborne Laser

Abstract. Biodiversity studies could strongly benefit from three-dimensional data on ecosystem structure derived from contemporary remote sensing technologies, such as Light Detection and Ranging (LiDAR). Despite the increasing availability of such data at regional and national scales, the average ecologist has been limited in accessing them due to high requirements on computing power and remote-sensing knowledge. We processed Denmark's publicly available national Airborne Laser Scanning (ALS) data set acquired in 2014/15 together with the accompanying elevation model to compute 70 rasterized descriptors of interest for ecological studies. With a grain size of 10 m, these data products provide a snapshot of high-resolution measures including vegetation height, structure and density, as well as topographic descriptors including elevation, aspect, slope and wetness across more than forty thousand square kilometres covering almost all of Denmark's terrestrial surface. The resulting data set is comparatively small (~ 87 GB, compressed 16.4 GB) and the raster data can be readily integrated into analytical workflows in software familiar to many ecologists (GIS software, R, Python). Source code and documentation for the processing workflow are openly available via a code repository, allowing for transfer to other ALS data sets, as well as modification or re-calculation of future instances of Denmark’s national ALS data set. We hope that our high-resolution ecological vegetation and terrain descriptors (EcoDes-DK15) will serve as an inspiration for the publication of further such data sets covering other countries and regions and that our rasterized data set will provide a baseline of the ecosystem structure for current and future studies of biodiversity, within Denmark and beyond.

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