Estimación de parámetros de estructura de nogales utilizando láser escáner terrestre

Juglans regia L. (nogal) es un árbol de importancia económica por el fruto que proporciona y por su madera utilizada en la industria del mueble. El objetivo de este trabajo fue calcular modelos de regresión para estimar los parámetros altura total, altura, diámetro y volumen de copa de nogales utili...

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Published in:Revista de Teledetección
Main Authors: Estornell, J., Velázquez-Martí, A., Fernández-Sarría, A., López-Cortés, I., Martí-Gavilá, J., Salazar, D.
Other Authors: Conselleria d'Educació, Cultura i Esport - Generalitat Valenciana) in the framework of the Project GV/2014/016
Format: Article in Journal/Newspaper
Language:English
Published: Universitat Politècnica de València 2017
Subjects:
Online Access:https://polipapers.upv.es/index.php/raet/article/view/7429
https://doi.org/10.4995/raet.2017.7429
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record_format openpolar
institution Open Polar
collection Universitat Politècnica de València: PoliPapers
op_collection_id ftunpvalenciaojs
language English
topic dendrometría
nogal
láser escáner
convex hull
agricultura de precisión
dendrometry
walnut tree
laser scanner
convex hull;precision agriculture
spellingShingle dendrometría
nogal
láser escáner
convex hull
agricultura de precisión
dendrometry
walnut tree
laser scanner
convex hull;precision agriculture
Estornell, J.
Velázquez-Martí, A.
Fernández-Sarría, A.
López-Cortés, I.
Martí-Gavilá, J.
Salazar, D.
Estimación de parámetros de estructura de nogales utilizando láser escáner terrestre
topic_facet dendrometría
nogal
láser escáner
convex hull
agricultura de precisión
dendrometry
walnut tree
laser scanner
convex hull;precision agriculture
description Juglans regia L. (nogal) es un árbol de importancia económica por el fruto que proporciona y por su madera utilizada en la industria del mueble. El objetivo de este trabajo fue calcular modelos de regresión para estimar los parámetros altura total, altura, diámetro y volumen de copa de nogales utilizando datos registrados mediante un escáner láser terrestre. Un conjunto de 30 árboles fueron escaneados y se aplicaron algoritmos para calcular los parámetros anteriores, que también se midieron en campo utilizando técnicas tradicionales. Se obtuvieron buenos resultados, con valores de R2 entre 0,90 y 0,98 para todos los parámetros. Además, para analizar la relación entre la densidad de puntos registrada y la precisión en la estimación de los parámetros de los nogales, las nubes de puntos de todos los árboles fueron sub-muestreadas utilizando diferentes distancias de separación entre puntos: 0,005 m, 0,01 m, 0,05 m, 0,1 m, 0,25 m, 0,5 m, 1 m y 2 m. Se calcularon nuevos modelos de regresión con los datos muestreados obteniéndose buenas estimaciones de los parámetros para todos los conjuntos de datos. Juglans regia L. (walnut) is a tree of significant economic importance, usually cultivated for its seed used in the food market, and for its wood used in the furniture industry. The aim of this work was to develop regression models to predict crown parameters for walnut trees using a terrestrial laser scanner. A set of 30 trees was selected and the total height, crown height and crown diameter were measured in the field. The trees were also measured by a laser scanner and algorithms were applied to compute the crown volume, crown diameter, total and crown height. Linear regression models were calculated to estimate walnut tree parameters from TLS data. Good results were obtained with values of R2 between 0.90 and 0.98. In addition, to analyze whether coarser point cloud densities might affect the results, the point clouds for all trees were subsampled using different point densities: points every 0.005 m, 0.01 m, 0.05 m, 0.1 m, 0.25 m, 0.5 m, 1 m, and 2 m. New regression models were calculated to estimate field parameters. For total height and crown volume good estimations were obtained from TLS parameters derived for all subsampled point cloud (0.005 m – 2 m).
author2 Conselleria d'Educació, Cultura i Esport - Generalitat Valenciana) in the framework of the Project GV/2014/016
format Article in Journal/Newspaper
author Estornell, J.
Velázquez-Martí, A.
Fernández-Sarría, A.
López-Cortés, I.
Martí-Gavilá, J.
Salazar, D.
author_facet Estornell, J.
Velázquez-Martí, A.
Fernández-Sarría, A.
López-Cortés, I.
Martí-Gavilá, J.
Salazar, D.
author_sort Estornell, J.
title Estimación de parámetros de estructura de nogales utilizando láser escáner terrestre
title_short Estimación de parámetros de estructura de nogales utilizando láser escáner terrestre
title_full Estimación de parámetros de estructura de nogales utilizando láser escáner terrestre
title_fullStr Estimación de parámetros de estructura de nogales utilizando láser escáner terrestre
title_full_unstemmed Estimación de parámetros de estructura de nogales utilizando láser escáner terrestre
title_sort estimación de parámetros de estructura de nogales utilizando láser escáner terrestre
publisher Universitat Politècnica de València
publishDate 2017
url https://polipapers.upv.es/index.php/raet/article/view/7429
https://doi.org/10.4995/raet.2017.7429
genre Arctic
genre_facet Arctic
op_source Revista de Teledetección; Núm. 48 (2017); 67-76
1988-8740
1133-0953
op_relation https://polipapers.upv.es/index.php/raet/article/view/7429/7922
Belsley. D.A. 1991. Conditioning Diagnostics: Collinearity and Weak Data in Regression. John Wiley & Sons.
Calders, K., Newnham, G., Burt, A., Murphy, S., Raumonen, P., Herold, M., Culvenor, D., Avitabile, V., Disney, M., Armston, J., Kaasalainen, M. 2015. Nondestructive estimates of above-ground biomass using terrestrial laser scanning. Methods in Ecology and Evolution Methods, 6(2), 198-208. https://doi. org/10.1111/2041-210x.12301
Chianucci, F., Puletti, N., Giacomello, E., Cutini, A., Corona, P. 2015. Estimation of leaf area index in isolated trees with digital photography and its application to urban forestry. Urban Forestry & Urban Greening, 14(2), 377-382. https://doi.org/10.1016/j.ufug.2015.04.001
Corona, P., Agrimi, M., Baffetta, F., Barbati, A., Chiriacò, M.V., Fattorini, L., Pompei, E., Valentini, R., Mattioli, W. 2012. Extending large-scale forest inventories to assess urban forests. Environmental Monitoring and Assessment, 184, 1409-1422. https://doi.org/10.1007/s10661-011-2050-6
Estornell, J., Ruiz, L.A., Velázquez-Martí, B., López- Cortés I., Salazar, D., Fernández-Sarría, A. 2015. Estimation of pruning biomass of olive trees using airborne discrete-return LiDAR data. Biomass and Bioenergy 81, 315-321. https://doi.org/10.1016/j. biombioe.2015.07.015
Fernández-Sarría, A., Velázquez-Martí, B., Sajdak, M., Martínez, L., Estornell, J. 2013a. Residual biomass calculation from individual tree architecture using terrestrial laser scanner and ground-level measurements. Computers and Electronics in Agriculture, 93, 90-97. https://doi.org/10.1016/j. compag.2013.01.012
Fernández-Sarría, A., Martínez, L., Velázquez-Martí, B., Sajdak, M., Estornell, J., Recio, J.A. 2013b. Different methodologies for calculating crown volume of Platanus hispanica trees by terrestrial laser scanner and comparison with classical dendrometric measurements. Computers and Electronics in Agriculture, 90, 176-185. https://doi. org/10.1016/j.compag.2012.09.017
Gil, E., Llorens, J., Llop, J., Fàbregas, X., Gallart, M. 2013. Use of a terrestrial LIDAR sensor for drift detection in vineyard spraying. Sensors, 13(1), 516- 534. https://doi.org/10.3390/s130100516
Greaves H.E., Vierling L.A., Eitel J.U.H., Boelman N.T., Magney T.S., Prager C.M., Griffin K. L. 2015. Estimating aboveground biomass and leaf area of low-stature Arctic shrubs with terrestrial LiDAR. Remote Sensing of Environment, 164, 26-35. https:// doi.org/10.1016/j.rse.2015.02.023
Höfle, B. 2014. Radiometric Correction of Terrestrial LiDAR Point Cloud Data for Individual Maize Plant Detection. Geoscience and Remote Sensing Letters, IEEE, 11(1), 94-98. https://doi.org/10.1109/ LGRS.2013.2247022
Hosoi, F., Omasa, K. 2009. Estimating vertical plant area density profile and growth parameters of a wheat canopy at different growth stages using three-dimensional portable LiDAR imaging. ISPRS Journal of Photogrammetry and Remote Sensing, 64(2), 151-158. https://doi.org/10.1016/j. isprsjprs.2008.09.003
Keightley, K.E., Bawden, G.W. 2010. 3D volumetric modeling of grapevine biomass using Tripod LiDAR. Computers and Electronics in Agriculture, 74(2), 305- 312. https://doi.org/10.1016/j.compag.2010.09.005
Manes, F., Incerti, G., Salvatori, E., Vitale, M., Ricotta, C., Costanza, R. 2012. Urban ecosystem services: tree diversity and stability of tropospheric ozone removal. Ecological Applications, 22(1), 349-360. https://doi.org/10.1890/11-0561.1
MAAM. 2015. Encuesta sobre superficies y rendimientos cultivos (ASYRCE). Encuesta de marco de áreas de España. Ministerio de Agricultura, Alimentación y Medio Ambiente de España, 44 pp.
Miranda-Fuentes, A., Llorens, J., Gamarra-Diezma, J.L., Gil-Ribes, J.A., Gil, E. 2015. Towards an optimized method of olive tree crown volume measurement. Sensors, 15(2), 3671-3687. https://doi.org/10.3390/ s150203671
Moorthy, I., Miller, J.R., Jimenez Berni, J.A., Zarco- Tejada, P., Hu, B., Chen, J. 2011. Field characterization of olive (Olea europaea L.) tree crown architecture using terrestrial laser scanning data. Agricultural and Forest Meteorology, 151(2), 204-214. https:// doi.org/10.1016/j.agrformet.2010.10.005
Rosell, J.R., Llorens, J., Sanz, R., Arnó, J., Ribes-Dasi, M., Masip, J., Escolà, A., Camp, F., Solanelles, F., Gràcia, F., Gil, E., Val, L., Planas, S., Palacín, J. 2009a. Obtaining the three-dimensional structure of tree orchards from remote 2D terrestrial LIDAR scanning. Agricultural and Forest Meteorology, 149(9), 1505-1515. https://doi.org/10.1016/j.agrformet.2009.04.008
Rosell, J.R., Sanz, R., Llorens, J., Arnó, J., Escolà, A., Ribes-Dasi, M., Masip, J., Camp, F., Gràcia, F., Solanelles, F., Pallejà, T., Val, L., Planas, S., Gil, E., Palacín, J. 2009b. A tractor-mounted scanning LIDAR for the non-destructive measurement of vegetative volume and surface area of tree-row plantations: A comparison with conventional destructive measurements. Biosystems Engineering, 102(2), 128-134. https://doi.org/10.1016/j.biosystemseng.2008.10.009
Rosell, J. R., Sanz, R. 2012. A review of methods and applications of the geometric characterization of tree crops in agricultural activities. Computers and Electronics in Agriculture, 81, 124-141. https://doi.org/10.1016/j.compag.2011.09.007
Tilly, N., Hoffmeister, D., Cao, Q., Huang, S., Lenz- Wiedemann, V., Miao, Y., Bareth, G. 2014. Multitemporal crop surface models: accurate plant height measurement and biomass estimation with terrestrial laser scanning in paddy rice. Journal of Applied Remote Sensing, 8(1), 83671. https://doi. org/10.1117/1.jrs.8.083671
https://polipapers.upv.es/index.php/raet/article/view/7429
doi:10.4995/raet.2017.7429
op_rights Copyright (c) 2017 Revista de Teledetección
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spelling ftunpvalenciaojs:oai:ojs.upv.es:article/7429 2023-05-15T14:28:24+02:00 Estimación de parámetros de estructura de nogales utilizando láser escáner terrestre Estimation of structural attributes of walnut trees based on terrestrial laser scanning Estornell, J. Velázquez-Martí, A. Fernández-Sarría, A. López-Cortés, I. Martí-Gavilá, J. Salazar, D. Conselleria d'Educació, Cultura i Esport - Generalitat Valenciana) in the framework of the Project GV/2014/016 2017-06-20 application/pdf https://polipapers.upv.es/index.php/raet/article/view/7429 https://doi.org/10.4995/raet.2017.7429 eng eng Universitat Politècnica de València https://polipapers.upv.es/index.php/raet/article/view/7429/7922 Belsley. D.A. 1991. Conditioning Diagnostics: Collinearity and Weak Data in Regression. John Wiley & Sons. Calders, K., Newnham, G., Burt, A., Murphy, S., Raumonen, P., Herold, M., Culvenor, D., Avitabile, V., Disney, M., Armston, J., Kaasalainen, M. 2015. Nondestructive estimates of above-ground biomass using terrestrial laser scanning. Methods in Ecology and Evolution Methods, 6(2), 198-208. https://doi. org/10.1111/2041-210x.12301 Chianucci, F., Puletti, N., Giacomello, E., Cutini, A., Corona, P. 2015. Estimation of leaf area index in isolated trees with digital photography and its application to urban forestry. Urban Forestry & Urban Greening, 14(2), 377-382. https://doi.org/10.1016/j.ufug.2015.04.001 Corona, P., Agrimi, M., Baffetta, F., Barbati, A., Chiriacò, M.V., Fattorini, L., Pompei, E., Valentini, R., Mattioli, W. 2012. Extending large-scale forest inventories to assess urban forests. Environmental Monitoring and Assessment, 184, 1409-1422. https://doi.org/10.1007/s10661-011-2050-6 Estornell, J., Ruiz, L.A., Velázquez-Martí, B., López- Cortés I., Salazar, D., Fernández-Sarría, A. 2015. Estimation of pruning biomass of olive trees using airborne discrete-return LiDAR data. Biomass and Bioenergy 81, 315-321. https://doi.org/10.1016/j. biombioe.2015.07.015 Fernández-Sarría, A., Velázquez-Martí, B., Sajdak, M., Martínez, L., Estornell, J. 2013a. Residual biomass calculation from individual tree architecture using terrestrial laser scanner and ground-level measurements. Computers and Electronics in Agriculture, 93, 90-97. https://doi.org/10.1016/j. compag.2013.01.012 Fernández-Sarría, A., Martínez, L., Velázquez-Martí, B., Sajdak, M., Estornell, J., Recio, J.A. 2013b. Different methodologies for calculating crown volume of Platanus hispanica trees by terrestrial laser scanner and comparison with classical dendrometric measurements. Computers and Electronics in Agriculture, 90, 176-185. https://doi. org/10.1016/j.compag.2012.09.017 Gil, E., Llorens, J., Llop, J., Fàbregas, X., Gallart, M. 2013. Use of a terrestrial LIDAR sensor for drift detection in vineyard spraying. Sensors, 13(1), 516- 534. https://doi.org/10.3390/s130100516 Greaves H.E., Vierling L.A., Eitel J.U.H., Boelman N.T., Magney T.S., Prager C.M., Griffin K. L. 2015. Estimating aboveground biomass and leaf area of low-stature Arctic shrubs with terrestrial LiDAR. Remote Sensing of Environment, 164, 26-35. https:// doi.org/10.1016/j.rse.2015.02.023 Höfle, B. 2014. Radiometric Correction of Terrestrial LiDAR Point Cloud Data for Individual Maize Plant Detection. Geoscience and Remote Sensing Letters, IEEE, 11(1), 94-98. https://doi.org/10.1109/ LGRS.2013.2247022 Hosoi, F., Omasa, K. 2009. Estimating vertical plant area density profile and growth parameters of a wheat canopy at different growth stages using three-dimensional portable LiDAR imaging. ISPRS Journal of Photogrammetry and Remote Sensing, 64(2), 151-158. https://doi.org/10.1016/j. isprsjprs.2008.09.003 Keightley, K.E., Bawden, G.W. 2010. 3D volumetric modeling of grapevine biomass using Tripod LiDAR. Computers and Electronics in Agriculture, 74(2), 305- 312. https://doi.org/10.1016/j.compag.2010.09.005 Manes, F., Incerti, G., Salvatori, E., Vitale, M., Ricotta, C., Costanza, R. 2012. Urban ecosystem services: tree diversity and stability of tropospheric ozone removal. Ecological Applications, 22(1), 349-360. https://doi.org/10.1890/11-0561.1 MAAM. 2015. Encuesta sobre superficies y rendimientos cultivos (ASYRCE). Encuesta de marco de áreas de España. Ministerio de Agricultura, Alimentación y Medio Ambiente de España, 44 pp. Miranda-Fuentes, A., Llorens, J., Gamarra-Diezma, J.L., Gil-Ribes, J.A., Gil, E. 2015. Towards an optimized method of olive tree crown volume measurement. Sensors, 15(2), 3671-3687. https://doi.org/10.3390/ s150203671 Moorthy, I., Miller, J.R., Jimenez Berni, J.A., Zarco- Tejada, P., Hu, B., Chen, J. 2011. Field characterization of olive (Olea europaea L.) tree crown architecture using terrestrial laser scanning data. Agricultural and Forest Meteorology, 151(2), 204-214. https:// doi.org/10.1016/j.agrformet.2010.10.005 Rosell, J.R., Llorens, J., Sanz, R., Arnó, J., Ribes-Dasi, M., Masip, J., Escolà, A., Camp, F., Solanelles, F., Gràcia, F., Gil, E., Val, L., Planas, S., Palacín, J. 2009a. Obtaining the three-dimensional structure of tree orchards from remote 2D terrestrial LIDAR scanning. Agricultural and Forest Meteorology, 149(9), 1505-1515. https://doi.org/10.1016/j.agrformet.2009.04.008 Rosell, J.R., Sanz, R., Llorens, J., Arnó, J., Escolà, A., Ribes-Dasi, M., Masip, J., Camp, F., Gràcia, F., Solanelles, F., Pallejà, T., Val, L., Planas, S., Gil, E., Palacín, J. 2009b. A tractor-mounted scanning LIDAR for the non-destructive measurement of vegetative volume and surface area of tree-row plantations: A comparison with conventional destructive measurements. Biosystems Engineering, 102(2), 128-134. https://doi.org/10.1016/j.biosystemseng.2008.10.009 Rosell, J. R., Sanz, R. 2012. A review of methods and applications of the geometric characterization of tree crops in agricultural activities. Computers and Electronics in Agriculture, 81, 124-141. https://doi.org/10.1016/j.compag.2011.09.007 Tilly, N., Hoffmeister, D., Cao, Q., Huang, S., Lenz- Wiedemann, V., Miao, Y., Bareth, G. 2014. Multitemporal crop surface models: accurate plant height measurement and biomass estimation with terrestrial laser scanning in paddy rice. Journal of Applied Remote Sensing, 8(1), 83671. https://doi. org/10.1117/1.jrs.8.083671 https://polipapers.upv.es/index.php/raet/article/view/7429 doi:10.4995/raet.2017.7429 Copyright (c) 2017 Revista de Teledetección http://creativecommons.org/licenses/by-nc-nd/4.0 CC-BY-NC-ND Revista de Teledetección; Núm. 48 (2017); 67-76 1988-8740 1133-0953 dendrometría nogal láser escáner convex hull agricultura de precisión dendrometry walnut tree laser scanner convex hull;precision agriculture info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article 2017 ftunpvalenciaojs https://doi.org/10.4995/raet.2017.7429 https://doi.org/10.1111/2041-210x.12301 https://doi.org/10.1007/s10661-011-2050-6 https://doi.org/10.1016/j https://doi.org/10.1016/j.compag.2012.09.017 https://doi.org/10.3390/s130100516 https://doi.org/ 2022-01-07T06:51:05Z Juglans regia L. (nogal) es un árbol de importancia económica por el fruto que proporciona y por su madera utilizada en la industria del mueble. El objetivo de este trabajo fue calcular modelos de regresión para estimar los parámetros altura total, altura, diámetro y volumen de copa de nogales utilizando datos registrados mediante un escáner láser terrestre. Un conjunto de 30 árboles fueron escaneados y se aplicaron algoritmos para calcular los parámetros anteriores, que también se midieron en campo utilizando técnicas tradicionales. Se obtuvieron buenos resultados, con valores de R2 entre 0,90 y 0,98 para todos los parámetros. Además, para analizar la relación entre la densidad de puntos registrada y la precisión en la estimación de los parámetros de los nogales, las nubes de puntos de todos los árboles fueron sub-muestreadas utilizando diferentes distancias de separación entre puntos: 0,005 m, 0,01 m, 0,05 m, 0,1 m, 0,25 m, 0,5 m, 1 m y 2 m. Se calcularon nuevos modelos de regresión con los datos muestreados obteniéndose buenas estimaciones de los parámetros para todos los conjuntos de datos. Juglans regia L. (walnut) is a tree of significant economic importance, usually cultivated for its seed used in the food market, and for its wood used in the furniture industry. The aim of this work was to develop regression models to predict crown parameters for walnut trees using a terrestrial laser scanner. A set of 30 trees was selected and the total height, crown height and crown diameter were measured in the field. The trees were also measured by a laser scanner and algorithms were applied to compute the crown volume, crown diameter, total and crown height. Linear regression models were calculated to estimate walnut tree parameters from TLS data. Good results were obtained with values of R2 between 0.90 and 0.98. In addition, to analyze whether coarser point cloud densities might affect the results, the point clouds for all trees were subsampled using different point densities: points every 0.005 m, 0.01 m, 0.05 m, 0.1 m, 0.25 m, 0.5 m, 1 m, and 2 m. New regression models were calculated to estimate field parameters. For total height and crown volume good estimations were obtained from TLS parameters derived for all subsampled point cloud (0.005 m – 2 m). Article in Journal/Newspaper Arctic Universitat Politècnica de València: PoliPapers Revista de Teledetección 48 67