scholarly journals Estimation of Voxel-Based Above-Ground Biomass Using Airborne LiDAR Data in an Intact Tropical Rain Forest, Brunei

Forests ◽  
2016 ◽  
Vol 7 (12) ◽  
pp. 259 ◽  
Author(s):  
Eunji Kim ◽  
Woo-Kyun Lee ◽  
Mihae Yoon ◽  
Jong-Yeol Lee ◽  
Yowhan Son ◽  
...  
Keyword(s):  
Rain Forest ◽  
Tropical Rain Forest ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Above Ground Biomass ◽  
Ground Biomass ◽  
Airborne Lidar Data

scholarly journals Estimation of Stand-level Above Ground Biomass in Intact Tropical Rain Forests of Brunei using Airborne LiDAR data

2015 ◽  
Vol 31 (2) ◽  
pp. 127-136 ◽  
Author(s):  
Mihae Yoon ◽  
Eunji Kim ◽  
Doo-Ahn Kwak ◽  
Woo-Kyun Lee ◽  
Jong-Yeol Lee ◽  
...  
Keyword(s):  
Airborne Lidar ◽  
Lidar Data ◽  
Above Ground Biomass ◽  
Tropical Rain Forests ◽  
Rain Forests ◽  
Ground Biomass ◽  
Airborne Lidar Data

scholarly journals Estimation of Above Ground Biomass in a Tropical Mountain Forest in Southern Ecuador Using Airborne LiDAR Data

2018 ◽  
Vol 10 (5) ◽  
pp. 660 ◽  
Author(s):  
Víctor González-Jaramillo ◽  
Andreas Fries ◽  
Jörg Zeilinger ◽  
Jürgen Homeier ◽  
Jhoana Paladines-Benitez ◽  
...  
Keyword(s):  
Airborne Lidar ◽  
Mountain Forest ◽  
Lidar Data ◽  
Above Ground Biomass ◽  
Ground Biomass ◽  
Tropical Mountain ◽  
Southern Ecuador ◽  
Airborne Lidar Data

scholarly journals Synergistic use of Landsat 8 OLI image and airborne LiDAR data for above-ground biomass estimation in tropical lowland rainforests

2017 ◽  
Vol 406 ◽  
pp. 163-171 ◽  
Author(s):  
Mui-How Phua ◽  
Shazrul Azwan Johari ◽  
Ong Cieh Wong ◽  
Keiko Ioki ◽  
Maznah Mahali ◽  
...  
Keyword(s):  
Airborne Lidar ◽  
Biomass Estimation ◽  
Lidar Data ◽  
Landsat 8 ◽  
Above Ground Biomass ◽  
Landsat 8 Oli ◽  
Tropical Lowland ◽  
Ground Biomass ◽  
Airborne Lidar Data

scholarly journals Regional Scale Rain-Forest Height Mapping Using Regression-Kriging of Spaceborne and Airborne LiDAR Data: Application on French Guiana

2016 ◽  
Vol 8 (3) ◽  
pp. 240 ◽  
Author(s):  
Ibrahim Fayad ◽  
Nicolas Baghdadi ◽  
Jean-Stéphane Bailly ◽  
Nicolas Barbier ◽  
Valéry Gond ◽  
...  
Keyword(s):  
Rain Forest ◽  
French Guiana ◽  
Regional Scale ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Regression Kriging ◽  
Forest Height ◽  
Data Application ◽  
Airborne Lidar Data

scholarly journals Cloth simulation-based construction of pit-free canopy height models from airborne LiDAR data

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Wuming Zhang ◽  
Shangshu Cai ◽  
Xinlian Liang ◽  
Jie Shao ◽  
Ronghai Hu ◽  
...  
Keyword(s):  
Tree Height ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Canopy Height ◽  
Lidar Data ◽  
Cloth Simulation ◽  
Simulation Based ◽  
Maximum Tree Height ◽  
Airborne Lidar Data ◽  
Better Than

Abstract Background The universal occurrence of randomly distributed dark holes (i.e., data pits appearing within the tree crown) in LiDAR-derived canopy height models (CHMs) negatively affects the accuracy of extracted forest inventory parameters. Methods We develop an algorithm based on cloth simulation for constructing a pit-free CHM. Results The proposed algorithm effectively fills data pits of various sizes whilst preserving canopy details. Our pit-free CHMs derived from point clouds at different proportions of data pits are remarkably better than those constructed using other algorithms, as evidenced by the lowest average root mean square error (0.4981 m) between the reference CHMs and the constructed pit-free CHMs. Moreover, our pit-free CHMs show the best performance overall in terms of maximum tree height estimation (average bias = 0.9674 m). Conclusion The proposed algorithm can be adopted when working with different quality LiDAR data and shows high potential in forestry applications.

The use of Otsu algorithm and multi-temporal airborne LiDAR data to detect building changes in urban space

2021 ◽  
Author(s):  
Renato César dos Santos ◽  
Mauricio Galo ◽  
André Caceres Carrilho ◽  
Guilherme Gomes Pessoa
Keyword(s):  
Urban Space ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Multi Temporal ◽  
Airborne Lidar Data
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