Research Papers

Assessment of factors affecting shrub volume estimations using airborne discrete-return LiDAR data in Mediterranean areas

[+] Author Affiliations
Javier Estornell

Universitat Politècnica de València, Geo-Environmental Cartography and Remote Sensing Group, Department of Cartographic Engineering, Geodesy and Photogrammetry, Camino de Vera s/n 46022 Valencia, Spain

Luis A. Ruiz

Universitat Politècnica de València, Geo-Environmental Cartography and Remote Sensing Group, Department of Cartographic Engineering, Geodesy and Photogrammetry, Camino de Vera s/n 46022 Valencia, Spain

Borja Velázquez-Martí

Universitat Politècnica de València, Departamento de Ingeniería Rural y Agroalimentaria, Camino de Vera s/n 46022 Valencia, Spain

Txomin Hermosilla

Universitat Politècnica de València, Geo-Environmental Cartography and Remote Sensing Group, Department of Cartographic Engineering, Geodesy and Photogrammetry, Camino de Vera s/n 46022 Valencia, Spain

J. Appl. Remote Sens. 6(1), 063544 (Jun 21, 2012). doi:10.1117/1.JRS.6.063544
History: Received December 12, 2011; Revised April 26, 2012; Accepted May 2, 2012
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Abstract.  Shrub vegetation is a key element of Mediterranean forest areas and it is necessary to develop tools that allow a precise knowledge of this vegetation. This study aims to predict shrub volume and analyze the factors affecting the accuracy of these estimations in small stands using airborne discrete-return LiDAR data. The study was performed over 83 circular stands with 0.5 m radius located in Chiva (Spain) mainly occupied by Quercus coccifera. The vegetation inside each area was clear cut, and the height and the diameter of each plant was measured to compute the volume of shrub vegetation per stand. Volume values were related with maximum height values derived from LiDAR data reaching a coefficient of determination value R2=0.26. Afterwards, factors affecting the quality of volume estimations were analyzed, i.e., vegetation type, LiDAR density, and accuracy of the digital terrain model (DTM). Significant accuracy improvements (R2=0.71) were detected for stands with 0.5 m, LiDAR data density greater than 8points/m2, vegetation Q. coccifera, and error associated to the DTM less than 0.20 m. These results show the feasibility of using LiDAR data to predict shrub volume under certain conditions, which can contribute to improved forest management and characterization.

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© 2012 Society of Photo-Optical Instrumentation Engineers

Topics

LIDAR

Citation

Javier Estornell ; Luis A. Ruiz ; Borja Velázquez-Martí and Txomin Hermosilla
"Assessment of factors affecting shrub volume estimations using airborne discrete-return LiDAR data in Mediterranean areas", J. Appl. Remote Sens. 6(1), 063544 (Jun 21, 2012). ; http://dx.doi.org/10.1117/1.JRS.6.063544


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