Slope Vulnerability and Risk Assessment Using High-Resolution Airborne Laser Scanning Data

2017 ◽  
pp. 235-251 ◽  
Author(s):  
Biswajeet Pradhan ◽  
Norbazlan Mohd Yusof
Keyword(s):  
Risk Assessment ◽  
High Resolution ◽  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Airborne Laser

scholarly journals Airborne laser scanning for high-resolution mapping of Antarctica

Eos ◽  
2005 ◽  
Vol 86 (25) ◽  
pp. 237 ◽  
Author(s):  
Bea Csatho ◽  
Toni Schenk ◽  
William Krabill ◽  
Terry Wilson ◽  
William Lyons ◽  
...  
Keyword(s):  
High Resolution ◽  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
High Resolution Mapping ◽  
Airborne Laser ◽  
Resolution Mapping

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.

scholarly journals Quantification of Lichen Cover and Biomass Using Field Data, Airborne Laser Scanning and High Spatial Resolution Optical Data—A Case Study from a Canadian Boreal Pine Forest

Forests ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 682
Author(s):  
Ashley C. Hillman ◽  
Scott E. Nielsen
Keyword(s):  
High Resolution ◽  
Spectral Data ◽  
Laser Scanning ◽  
Canopy Cover ◽  
Jack Pine ◽  
Pine Forest ◽  
Airborne Laser Scanning ◽  
Woodland Caribou ◽  
Airborne Laser ◽  
Pine Stands

Ground-dwelling macrolichens dominate the forest floor of mature upland pine stands in the boreal forest. Understanding patterns of lichen abundance, as well as environmental characteristics associated with lichen growth, is key to managing lichens as a forage resource for threatened woodland caribou (Rangifer tarandus caribou). The spectral signature of light-coloured lichen distinguishes it from green vegetation, potentially allowing for mapping of lichen abundance using multi-spectral imagery, while canopy structure measured from airborne laser scanning (ALS) of forest openings can indirectly map lichen habitat. Here, we test the use of high-resolution KOMPSAT (Korea Multi-Purpose Satellite-3) imagery (280 cm resolution) and forest structural characteristics derived from ALS to predict lichen biomass in an upland jack pine forest in Northeastern Alberta, Canada. We quantified in the field lichen abundance (cover and biomass) in mature jack pine stands across low, moderate, and high canopy cover. We then used generalized linear models to relate lichen abundance to spectral data from KOMPSAT and structural metrics from ALS. Model selection suggested that lichen abundance was best predicted by canopy cover (ALS points > 1.37 m) and to a lesser extent blue spectral data from KOMPSAT. Lichen biomass was low at plots with high canopy cover (98.96 g/m2), while almost doubling for plots with low canopy cover (186.30 g/m2). Overall the model fit predicting lichen biomass was good (R2 c = 0.35), with maps predicting lichen biomass from spectral and structural data illustrating strong spatial variations. High-resolution mapping of ground lichen can provide information on lichen abundance that can be of value for management of forage resources for woodland caribou. We suggest that this approach could be used to map lichen biomass for other regions.

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