A low-cost multi-sensoral mobile mapping system and its feasibility for tree measurements

By Anttoni Jaakkola, Juha Hyyppä, A. Kukko, Xiaowei Yu, Harri Kaartinen, M. Lehtomäki, Yi Lin. 2010

344 citations recorded by the source corpus.

Subfields: Environmental Engineering, Geology, Insect Science

View Paper: https://www.semanticscholar.org/paper/f93858dae98308e777e04b23b71407844e08acfd

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Environmental Engineering

1. Darren Turner
2. Arko Lucieer
3. Luke Wallace
4. Lianjun Zhang
5. Zhen Zhen
6. Lin Cao
7. Katarzyna Dziób
8. Honghua Ruan

In Geology

1. Darren Turner
2. Arko Lucieer
3. Luke Wallace
4. Z. Malenovsky
5. Petr Vopenka
6. Lin Cao
7. Katarzyna Dziób
8. M. Nowak

In Insect Science

1. Lin Cao
2. Honghua Ruan
3. Paula Litkey
4. Zhen Zhen
5. Hao Liu
6. Lianjun Zhang
7. Zhengnan Zhang
8. Eija Honkavaara

Citations in the corpus

• Comparison of UAV LiDAR and Digital Aerial Photogrammetry Point Clouds for Estimating Forest Structural Attributes in Subtropical Planted Forests (2019, background): “Jaakkola et al. (2010) [38] reported the first application of UAV-LiDAR in forestry.”
• A LIDAR-based crop height measurement system for Miscanthus giganteus (2012, methodology): “The method is similar to that used by Jaakkola et al. (2010), who applied a LIDAR to develop a mapping system for tree measurement as well as the method used by Van der Zande et al. (2006), who reconstructed the tree structure using a LIDAR as well.”
• Unmanned Aerial Vehicles (UAVs) in environmental biology: a review (2019, background): “One of the first examples showing the potential of UAV-borne LiDAR for use in the forestry research was provided by Jaakkola et al. (2010).”
• Development of a UAV-LiDAR System with Application to Forest Inventory (2012, methodology): “This is consistent with the results from [14] who reported a similar variation with a Ibeo LUX sensor.”
• Comparison and Combination of Mobile and Terrestrial Laser Scanning for Natural Forest Inventories (2018, methodology): “[16] perform a tree segmentation by clustering of vertical line segments and the analysis of their spatial extent.”
• Processing and Assessment of Spectrometric, Stereoscopic Imagery Collected Using a Lightweight UAV Spectral Camera for Precision Agriculture (2013, methodology): “The recent sensor developments tailored for operation from UAVs offer enhanced possibilities for remote sensing applications in terms of better image quality, multi-spectral, hyper-spectral and thermal imaging [4–10] and laser scanning [11–13].”
• Assessment of Forest Structure Using Two UAV Techniques: A Comparison of Airborne Laser Scanning and Structure from Motion (SfM) Point Clouds (2016, methodology): “Point clouds generated with both LiDAR and SfM technologies have been demonstrated to provide information representative of forest attributes including height, canopy dimensions, and biomass at both the area and tree levels [14,15,20,21].”
• Trends in Automatic Individual Tree Crown Detection and Delineation - Evolution of LiDAR Data (2016, methodology): “[101] performed tree measurement using a low-cost laser scanning system consisting of GPS/IMU positioning system, two laser scanners, a CCD camera, a spectrometer and a thermal camera.”
• Forestry applications of UAVs in Europe: a review (2017, methodology): “Jaakkola (2015), Lin, Hyyppä, and Jaakkola (2011), and Jaakkola et al. (2010) developed a low-cost multisensoral UAV system for detailed mapping and modelling of trees in Finland by means of laser scanner data.”