Application of airborne LiDA R data in viewshed analysis

Revista oficial de la Asociación Española de Teledetección[EN] The environmental impact assessment and landscape analysis of any work or activity over the territory requires a study of the visual impact what can be done from the application of viewshed analysis. The accuracy of these results depends largely on the parameters for calculating them, accuracy and spatial resolution of initial elevation data and digital models derived. In this study viewshed analysis in 4 areas of the town of Gandia with different characteristics (urban, forest, beach, mixed) were analyzed from 4 types of geographic information: a) Digital Elevation Model (DEM) and b) Digital Surface Model (DSM) derived from LiDAR data with density of 1 point/m2; c) DTM from a photogrammetric flight with a pixel size of 5×5 m; d) Overlay cadastral cartography with the previous DTM. For the validation of the results, 120 checking points were used to calculate the overall accuracy and kappa index. The results showed a high overall accuracy for the viewsheds calculated from the DSM derived from LiDAR data being the overall accuracy and index kappa 90% and 0.80, respectively. The conclusions drawn from this study indicated that the use of this source of information showed a good performance for the generation of viewshed analysis.[ES] Los estudios de impacto ambiental o paisajismo de cualquier obra o actuación en el territorio requieren de un estudio del impacto visual de las mismas a partir de la generación de cuencas visuales. La exactitud de estos resultados depende en gran medida del tipo datos de elevaciones iniciales, de los modelos digitales que se deriven y de los parámetros del cálculo de las cuencas visuales. En este estudio se analizaron cuencas visuales generadas en cuatro zonas del municipio de Gandia con características diferenciadas (urbana, forestal, playa, mixta) a partir de cuatro tipos de información cartográfica: a) Modelo Digital del Terreno (MDT) y b) Modelo Digital de Superficie (MDS) calculados a partir de datos LiDAR con una densidad media de 1 punto/m2; c) MDT derivado de un vuelo fotogramétrico a escala 1/5000; d) Superposición cartografía catastral con elevaciones de edificios y el MDT anterior. Para la validación de las mismas se utilizaron 120 puntos de muestreo (60 visibles y 60 no visibles) con los que se calculó la fiabilidad global e índice kappa. Los resultados obtenidos muestran una fiabilidad global muy alta en las cuencas visuales calculadas a partir del MDS derivado de los datos LiDAR siendo la fiabilidad global e índice kappa del 90% y 0,80, respectivamente. La conclusión que se desprenden de este estudio indica que la utilización del MDS derivado de los datos LiDAR de baja densidad genera resultados satisfactorios en la generación de cuencas visuales para los estudios de paisajismo o impacto ambiental.Pellicer, I.; Estornell Cremades, J.; Martí, J. (2014). Aplicación de datos LiDAR aéreo para el cálculo de cuencas visuales. Revista de Teledetección. (41):9-18. doi:10.4995/raet.2014.2293SWORD9184

Estimation of wood volume and height of olive tree plantations using airborne discrete-return LiDAR data

The aim of this study is to analyze methodologies based on airborne LiDAR (light detection and ranging) technology of low pulse density points (0.5m(-2)) for height and volume quantification of olive trees in Viver (Spain). A total of 29 circular plots, each with a radius of 20m, were sampled and their volumes and heights were obtained by dendrometric methods. For these estimations, several statistics derived from LiDAR data were calculated in each plot. Regression models were used to predict volume and height. The results showed good performance for estimating volume (R-2=0.70) and total height (R-2=0.67).The authors appreciate the financial support provided by the Spanish Ministerio de Ciencia e Innovacion (Ministry for Science & Innovation) within the framework of the project AGL2010-15334 and by the Vice-Rectorate for Research of the Universitat Politecnica de Valencia [Grant PAID-06-12-3297; SP20120534].Estornell Cremades, J.; Velázquez Martí, B.; López Cortés, I.; Salazar Hernández, DM.; Fernández-Sarría, A. (2014). Estimation of wood volume and height of olive tree plantations using airborne discrete-return LiDAR data. GIScience and Remote Sensing. 51(1):17-29. https://doi.org/10.1080/15481603.2014.883209S1729511Estornell, J., Ruiz, L. A., Velázquez-Martí, B., & Fernández-Sarría, A. (2011). Estimation of shrub biomass by airborne LiDAR data in small forest stands. Forest Ecology and Management, 262(9), 1697-1703. doi:10.1016/j.foreco.2011.07.026García, M., Riaño, D., Chuvieco, E., & Danson, F. M. (2010). Estimating biomass carbon stocks for a Mediterranean forest in central Spain using LiDAR height and intensity data. Remote Sensing of Environment, 114(4), 816-830. doi:10.1016/j.rse.2009.11.021Hyyppa, J., Kelle, O., Lehikoinen, M., & Inkinen, M. (2001). A segmentation-based method to retrieve stem volume estimates from 3-D tree height models produced by laser scanners. IEEE Transactions on Geoscience and Remote Sensing, 39(5), 969-975. doi:10.1109/36.921414Kim, Y., Yang, Z., Cohen, W. B., Pflugmacher, D., Lauver, C. L., & Vankat, J. L. (2009). Distinguishing between live and dead standing tree biomass on the North Rim of Grand Canyon National Park, USA using small-footprint lidar data. Remote Sensing of Environment, 113(11), 2499-2510. doi:10.1016/j.rse.2009.07.010Moorthy, I., Miller, J. R., Berni, J. A. J., 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. doi:10.1016/j.agrformet.2010.10.005Næsset, E. (2004). Accuracy of forest inventory using airborne laser scanning: evaluating the first nordic full-scale operational project. Scandinavian Journal of Forest Research, 19(6), 554-557. doi:10.1080/02827580410019544Popescu, S. C. (2007). Estimating biomass of individual pine trees using airborne lidar. Biomass and Bioenergy, 31(9), 646-655. doi:10.1016/j.biombioe.2007.06.022Popescu, S. C., Wynne, R. H., & Nelson, R. F. (2002). Estimating plot-level tree heights with lidar: local filtering with a canopy-height based variable window size. Computers and Electronics in Agriculture, 37(1-3), 71-95. doi:10.1016/s0168-1699(02)00121-7Velázquez-Martí, B., Estornell, J., López-Cortés, I., & Martí-Gavilá, J. (2012). Calculation of biomass volume of citrus trees from an adapted dendrometry. Biosystems Engineering, 112(4), 285-292. doi:10.1016/j.biosystemseng.2012.04.011Velázquez-Martí, B., Fernández-González, E., Estornell, J., & Ruiz, L. A. (2010). Dendrometric and dasometric analysis of the bushy biomass in Mediterranean forests. Forest Ecology and Management, 259(5), 875-882. doi:10.1016/j.foreco.2009.11.027Velázquez-Martí, B., Fernández-González, E., López-Cortés, I., & Salazar-Hernández, D. M. (2011). Quantification of the residual biomass obtained from pruning of trees in Mediterranean olive groves. Biomass and Bioenergy, 35(7), 3208-3217. doi:10.1016/j.biombioe.2011.04.042Yu, X., Hyyppä, J., Kaartinen, H., & Maltamo, M. (2004). Automatic detection of harvested trees and determination of forest growth using airborne laser scanning. Remote Sensing of Environment, 90(4), 451-462. doi:10.1016/j.rse.2004.02.00

Classification of UAV-based photogrammetric point clouds of riverine species using machine learning algorithms: a case study in the Palancia river, Spain

[EN] The management of riverine areas is fundamental due to their great environmental importance. The fast changes that occur in these areas due to river mechanics and human pressure makes it necessary to obtain data with high temporal and spatial resolution. This study proposes a workflow to map riverine species using Unmanned Aerial Vehicle (UAV) imagery. Based on RGB point clouds, our work derived simple geometric and spectral metrics to classify an area of the public hydraulic domain of the river Palancia (Spain) in five different classes: Tamarix gallica L. (French tamarisk), Pinus halepensis Miller (Aleppo pine), Arundo donax L. (giant reed), other riverine species and ground. A total of six Machine Learning (ML) methods were evaluated: Decision Trees, Extra Trees, Multilayer Perceptron, K-Nearest Neighbors, Random Forest and Ridge. The method chosen to carry out the classification was Random Forest, which obtained a mean score cross-validation close to 0.8. Subsequently, an object-based reclassification was done to improve this result, obtaining an overall accuracy of 83.6%, and individually a producer¿s accuracy of 73.8% for giant reed, 87.7% for Aleppo pine, 82.8% for French tamarisk, 93.5% for ground and 80.1% for other riverine species. Results were promising, proving the feasibility of using this cost-effective method for periodic monitoring of riverine species. In addition, the proposed workflow is easily transferable to other tasks beyond riverine species classification (e.g., green areas detection, land cover classification) opening new opportunities in the use of UAVs equipped with consumer cameras for environmental applications.Carbonell-Rivera, JP.; Estornell Cremades, J.; Ruiz Fernández, LÁ.; Torralba, J.; Crespo-Peremarch, P. (2020). Classification of UAV-based photogrammetric point clouds of riverine species using machine learning algorithms: a case study in the Palancia river, Spain. ISPRS. 659-666. https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-659-2020S65966

Calculation of biomass volume of citrus trees from an adapted dendrometry

A methodology and computational algorithms, to calculate volumes and the total biomass contained in citrus trees from an adapted dendrometry were developed. The methodology could be used as a tool to manage resources from the orchards, establishing adequate predictive models for assessing parameters such as income from raw materials for the cultivation, fruit production, CO2 sink, and waste materials (i.e. residual wood) used for energy or industry. Dendrometry has been traditionally applied to forest trees. However, little research has been conducted on fruit trees due to their heterogeneous structure. To develop the process of biomass quantification it was necessary to perform systems of measurement, enabling to determine volumes of the analysed trees. Firstly, form factors and volume functions for the branches were calculated. These volume functions gave 0.97 coefficient of determination from base diameter and length. The relationships between apparent crown volume and actual volume in the crown (i.e. no hollows) of the trees were established, with 0.80 coefficient of determination. Occupation factor and the distribution of biomass in the crown strata were evaluated. These results could be correlated with production and quality of the fruit, with the amount of residual biomass coming from pruning, and with LIDAR data what may produce a simple, quick and accurate way to predict biomass.This research were developed by the project AGL2010-15334 funded by the Ministry of Science and Innovation of Spain funds.Velázquez Martí, B.; Estornell Cremades, J.; López Cortés, I.; Marti Gavila, J. (2012). Calculation of biomass volume of citrus trees from an adapted dendrometry. Biosystems Engineering. 112(4):285-292. https://doi.org/10.1016/j.biosystemseng.2012.04.011S285292112

Estimation of shrub biomass by airborne LiDAR data in small forest stands

The presence of shrub vegetation is very significant in Mediterranean ecosystems. However, the difficulty involved in shrub management and the lack of information about behavior of this vegetation means that these areas are often left out of spatial planning projects. Airborne LiDAR (Light Detection And Ranging) has been used successfully in forestry to estimate dendrometric and dasometric variables that allow to characterize forest structure. In contrast, little research has focused on shrub vegetation. The objective of this study was to estimate dry biomass of shrub vegetation in 83 stands of radius 0.5 m using variables derived from LiDAR data. Dominant species was Quercus coccifera, one of the most characteristic species of the Mediterranean forests. Density of LiDAR data in the analyzed stands varied from 2 points/m(2) to 16 points/m(2), being the average 8 points/m(2) and the standard deviation 4.5 points/m(2). Under these conditions, predictions of biomass were performed calculating the mean height, the maximum height and the percentile values 80th, 90th, and 95th derived from LiDAR in concentric areas whose radius varied from 0.50 m to 3.5 m from the center of the stand. The maximum R(2) and the minimum RMSE for dry biomass estimations were obtained when the percentile 95th of LiDAR data was calculated in an area of radius 1.5 m, being 0.48 and 1.45 kg, respectively. For this radius, it was found that for the stands (n = 39) where the DTM is calculated with high accuracy (RMSE lower than 0.20 m) and with a high density of LiDAR data (more than 8 points/m(2)) the R(2) value was 0.73. These results show the possibility of estimating shrub biomass in small areas when the density of LiDAR data is high and errors associated to the DTM are low. These results would allow us to improve the knowledge about shrub behavior avoiding the cost of field measurements and clear cutting actions. (C) 2011 Elsevier B.V. All rights reserved.Estornell Cremades, J.; Ruiz Fernández, LÁ.; Velázquez Martí, B.; Fernández Sarriá, A. (2011). Estimation of shrub biomass by airborne LiDAR data in small forest stands. Forest Ecology and Management. 262(9):1697-1703. doi:10.1016/j.foreco.2011.07.026S16971703262

Estimación de parámetros de estructura de nogales utilizando láser escáner terrestre

[EN] 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).[ES] Juglans regiaL. (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 pa-rámetros 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.The authors appreciate the financial support provided by the regional government of Spain (Conselleria d'Educacio, Cultura i Esport Generalitat Valenciana) in the framework of the Project GV/2014/016.Estornell, J.; Velázquez-Martí, A.; Fernández-Sarría, A.; López-Cortés, I.; Martí-Gavilá, J.; Salazar, D. (2017). Estimation of structural attributes of walnut trees based on terrestrial laser scanning. Revista de Teledetección. (48):67-76. https://doi.org/10.4995/raet.2017.7429SWORD677648Belsley. D.A. 1991. Conditioning Diagnostics: Collinearity and Weak Data in Regression. John Wiley & Sons.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. doi:10.1016/j.ufug.2015.04.001Corona, P., Agrimi, M., Baffetta, F., Barbati, A., Chiriacò, M. V., Fattorini, L., … Mattioli, W. (2011). Extending large-scale forest inventories to assess urban forests. Environmental Monitoring and Assessment, 184(3), 1409-1422. doi:10.1007/s10661-011-2050-6Fernández-Sarría, A., Martínez, L., Velázquez-Martí, B., Sajdak, M., Estornell, J., & Recio, J. A. (2013). Different methodologies for calculating crown volumes of Platanus hispanica trees using terrestrial laser scanner and a comparison with classical dendrometric measurements. Computers and Electronics in Agriculture, 90, 176-185. doi:10.1016/j.compag.2012.09.017Gil, 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. doi:10.3390/s130100516Greaves, 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. doi:10.1016/j.rse.2015.02.023Keightley, K. E., & Bawden, G. W. (2010). 3D volumetric modeling of grapevine biomass using Tripod LiDAR. Computers and Electronics in Agriculture, 74(2), 305-312. doi:10.1016/j.compag.2010.09.005Manes, 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. doi:10.1890/11-0561.1MAAM. 2015. Encuesta sobre superficies y rendimientos cultivos (ASYRCE). Encuesta de marco de áreas de Espa-a. Ministerio de Agricultura, Alimentación y Medio Ambiente de Espa-a, 44 pp.Rosell, J. R., Llorens, J., Sanz, R., Arnó, J., Ribes-Dasi, M., Masip, J., … Palacín, J. (2009). Obtaining the three-dimensional structure of tree orchards from remote 2D terrestrial LIDAR scanning. Agricultural and Forest Meteorology, 149(9), 1505-1515. doi:10.1016/j.agrformet.2009.04.008Rosell Polo, J. R., Sanz, R., Llorens, J., Arnó, J., Escolà, A., Ribes-Dasi, M., … Palacín, J. (2009). 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. doi:10.1016/j.biosystemseng.2008.10.009Rosell, 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. doi:10.1016/j.compag.2011.09.00

Change detection of isolated housing using a new hybrid approach based on object classification with optical and TerraSAR-X data

Optical and microwave high spatial resolution images are now available for a wide range of applications. In this work, they have been applied for the semi-automatic change detection of isolated housing in agricultural areas. This article presents a new hybrid methodology based on segmentation of high-resolution images and image differencing. This new approach mixes the main techniques used in change detection methods and it also adds a final segmentation process in order to classify the change detection product. First, isolated building classification is carried out using only optical data. Then, synthetic aperture radar (SAR) information is added to the classification process, obtaining excellent results with lower complexity cost. Since the first classification step is improved, the total change detection scheme is also enhanced when the radar data are used for classification. Finally, a comparison between the different methods is presented and some conclusions are extracted from the study. © 2011 Taylor & Francis.Vidal Pantaleoni, A.; Moreno Cambroreno, MDR. (2011). Change detection of isolated housing using a new hybrid approach based on object classification with optical and TerraSAR-X data. International Journal of Remote Sensing. 32(24):9621-9635. doi:10.1080/01431161.2011.571297S962196353224BLAES, X., VANHALLE, L., & DEFOURNY, P. (2005). Efficiency of crop identification based on optical and SAR image time series. Remote Sensing of Environment, 96(3-4), 352-365. doi:10.1016/j.rse.2005.03.010Chen, Y., Shi, P., Fung, T., Wang, J., & Li, X. (2007). Object‐oriented classification for urban land cover mapping with ASTER imagery. International Journal of Remote Sensing, 28(20), 4645-4651. doi:10.1080/01431160500444731Dalla Mura, M., Benediktsson, J. A., Bovolo, F., & Bruzzone, L. (2008). An Unsupervised Technique Based on Morphological Filters for Change Detection in Very High Resolution Images. IEEE Geoscience and Remote Sensing Letters, 5(3), 433-437. doi:10.1109/lgrs.2008.917726Dell’Acqua, F., & Gamba, P. (2006). Discriminating urban environments using multiscale texture and multiple SAR images. International Journal of Remote Sensing, 27(18), 3797-3812. doi:10.1080/01431160600557572Haralick, R. M., Shanmugam, K., & Dinstein, I. (1973). Textural Features for Image Classification. IEEE Transactions on Systems, Man, and Cybernetics, SMC-3(6), 610-621. doi:10.1109/tsmc.1973.4309314Im, J., Jensen, J. R., & Tullis, J. A. (2008). Object‐based change detection using correlation image analysis and image segmentation. International Journal of Remote Sensing, 29(2), 399-423. doi:10.1080/01431160601075582Lhomme, S., He, D., Weber, C., & Morin, D. (2009). A new approach to building identification from very‐high‐spatial‐resolution images. International Journal of Remote Sensing, 30(5), 1341-1354. doi:10.1080/01431160802509017LOBO, A., CHIC, O., & CASTERAD, A. (1996). Classification of Mediterranean crops with multisensor data: per-pixel versus per-object statistics and image segmentation. International Journal of Remote Sensing, 17(12), 2385-2400. doi:10.1080/01431169608948779Lu, D., Mausel, P., Brondízio, E., & Moran, E. (2004). Change detection techniques. International Journal of Remote Sensing, 25(12), 2365-2401. doi:10.1080/0143116031000139863Shimabukuro, Y. E., Almeida‐Filho, R., Kuplich, T. M., & de Freitas, R. M. (2007). Quantifying optical and SAR image relationships for tropical landscape features in the Amazônia. International Journal of Remote Sensing, 28(17), 3831-3840. doi:10.1080/01431160701236829Stramondo, S., Bignami, C., Chini, M., Pierdicca, N., & Tertulliani, A. (2006). Satellite radar and optical remote sensing for earthquake damage detection: results from different case studies. International Journal of Remote Sensing, 27(20), 4433-4447. doi:10.1080/01431160600675895Yuan, D., & Elvidge, C. D. (1996). Comparison of relative radiometric normalization techniques. ISPRS Journal of Photogrammetry and Remote Sensing, 51(3), 117-126. doi:10.1016/0924-2716(96)00018-

Estimating residual biomass of olive tree crops using terrestrial laser scanning

[EN] Agricultural residues have gained increasing interest as a source of renewable energy. The development of methods and techniques that allow to inventory residual biomass needs to be explored further. In this study, the residual biomass of olive trees was estimated based on parameters derived from using a Terrestrial Laser Scanning System (TLS). To this end, 32 olive trees in 2 orchards in the municipality of Viver, Central Eastern Spain, were selected and measured using a TLS system. The residual biomass of these trees was pruned and weighed. Several algorithms were applied to the TLS data to compute the main parameters of the trees: total height, crown height, crown diameter and crown volume. Regarding the last parameter, 4 methods were tested: the global convex hull volume, the convex hull by slice volume, the section volume, and the volume measured by voxels. In addition, several statistics were computed from the crown points for each tree. Regression models were calculated to predict residual biomass using 3 sets of potential explicative variables: firstly, the height statistics retrieved from 3D cloud data for each crown tree, secondly, the parameters of the trees derived from TLS data and finally, the combination of both sets of variables. Strong relationships between residual biomass and TLS parameters (crown volume parameters) were found (R2 = 0.86, RMSE = 2.78 kg). The pruning biomass pre- diction fraction was improved by 6%, in terms of R2, when the variance of the crown-point elevations was selected (R2 = 0.92, RMSE = 2.01 kg). The study offers some important insights into the quantification of residual biomass, which is essential information for the production of biofuel.Fernández-Sarría, A.; López- Cortés, I.; Estornell Cremades, J.; Velázquez Martí, B.; Salazar Hernández, DM. (2019). Estimating residual biomass of olive tree crops using terrestrial laser scanning. International Journal of Applied Earth Observation and Geoinformation. 75:163-170. https://doi.org/https://doi.org/10.1016/j.jag.2018.10.019S1631707

Circundatin H, a new inhibitor of mitochondrial NADH oxidase from Aspergillus ochraceus

[EN] Circumdatin H (1), a new alkaloid from the culture broth of Aspergillus ochraceus, has been isolated, together with a known circumdatin, circumdatin E (2) and other known compounds: flavacol (3) and stephacidin A (4). The structure of 1 was established on the basis of chemical and spectral evidence. All of these alkaloids showed biological activity as inhibitors of the mammalian mitochondrial respiratory chain.López-Gresa, MP.; Gonzalez Más, MC.; Primo, J.; Moya, P.; Romero, V.; Estornell, E. (2005). Circundatin H, a new inhibitor of mitochondrial NADH oxidase from Aspergillus ochraceus. The Journal of Antibiotics. 58:416-419. http://hdl.handle.net/10251/134335S4164195

Different methodologies for calculating crown volume of Platanus hispanica trees by terrestial laser scanner and comparison with classical dendrometric measurements

Terrestrial laser scanners (TLSs) are used in forestry and fruit culture applications to perform a threedimensional geometrical characterization of trees and so make it easier to develop management systems based on that information. In addition, this data can improve the accuracy of dendrometric variable estimations, such as crown volume, obtained by standard methods. The main objective of this paper is to compare classical methods for crown volume estimation with the volumes obtained from the processing of point clouds obtained using a terrestrial laser scanner (TLS) on urban Platanus hispanica trees. This will allow faster quantification of residual biomass from pruning and therefore an improved management in future. The methods applied using TLS data were also evaluated in terms of processing speed. A set of 30 specimens were selected and their main dendrometric parameters (such as diameter breast height, crown diameter, total height, and distance from the crown base to the soil) were manually measured using classical methods. From these dendrometric parameters, the apparent crown volumes were calculated using three geometric models: cone, hemisphere, and paraboloid. Simultaneously, these trees were scanned with a Leica ScanStation2. A laser point cloud was registered for each tree and processed to obtain the crown volumes. Four processing methods were analyzed: (a) convex hull (an irregular polyhedral surface formed by triangles that surround the crown) applied to the whole point cloud that forms the crown; (b) convex hull using slices of 10 cm in height from the top to the base of the crown; (c) XY triangulation in horizontal sections; and (d) voxel discretization. All the obtained volumes (derived from classical methods and TLS) were assessed and compared. The regression equations that compare the volumes obtained by dendrometry and those derived from TLS data showed coefficients of determination (R2) greater than 0.78. The highest R2 (0.89) was obtained in the comparison between the volume calculated using a paraboloid and flat sections, which was also the fastest method. These results show the potential of TLS for predicting the crown volumes of urban trees, such as P. hispanica, to help improve their management, especially the quantification of residual biomass.The authors appreciate the financial support provided by the Spanish Ministry of Science and Innovation in the framework of the Project AGL2010-15334 and by the Generalitat Valenciana in the framework of the Project GV/2012/003.Fernández-Sarría, A.; Martínez, L.; Velázquez Martí, B.; Sajdak, M.; Estornell Cremades, J.; Recio Recio, JA. (2013). Different methodologies for calculating crown volume of Platanus hispanica trees by terrestial laser scanner and comparison with classical dendrometric measurements. Computers and Electronics in Agriculture. 90(1):176-185. https://doi.org/10.1016/j.compag.2012.09.017S17618590