A LiDAR-Based System to Assess Poplar Biomass
Fernandez Quintanilla, C.
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This study evaluated the capabilities of a LiDAR-based system to characterize poplar trees for biomass production. The precision of the system was assessed by analyzing the relationship between the distance records and biophysical parameters. The terrestrial laser scanner (TLS) system consisted of a
2D time-of-flight LiDAR sensor, a gimbal to dynamically stabilize the sensor and a RTK-GPS to georeference its location and, subsequently, the sensor data. The sensor and its stabilizer were fixed facing downwards, on a metal frame designed for this purpose. Then, it was mounted on an all-terrain vehicle to perform 2D scans in planes perpendicular to the travel direction. Distances between the sensor and the surrounding objects had a high spatial resolution, providing high density 3D point clouds. Results on the reliability of the LiDAR system to estimate plant height showed a significant relationship between the sensor readings and actual poplar height and biomass data. In addition, tree biomass and tree volume were properly estimated in the point cloud. Regression analysis showed significant estimates of 0.79 and 0.89 for biomass and volume, respectively. These results reveal the potential of the LiDAR sensor to estimate both, plant height and plant biomass. This sensor's capability, added to its relative low cost, fast reaction, and the high number of readings per second consolidate the ideal system for estimating the productivity of biomass in energy crops. http://link.springer.com/article/10.1007%2Fs10343-016-0369-1
Is part ofGesunde Pflanzen, 2016, vol. 68, p. 155-162
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Andújar, Dionisio; Rueda-Ayala, Victor; Moreno, Hugo; Rosell Polo, Joan Ramon; Escolà i Agustí, Alexandre; Valero, Constantino; Gerhards, Roland; Fernández-Quintanilla, César; Dorado, José; Griepentrog, Hans-Werner (Molecular Diversity Preservation International (MDPI), 2013)In this study, the evaluation of the accuracy and performance of a light detection and ranging (LIDAR) sensor for vegetation using distance and reflection measurements aiming to detect and discriminate maize plants and ...
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