Comer por aburrimiento: relación entre tendencia al aburrimiento y estilos de ingesta en población general.

Antecedentes: Por comer emocional se entiende la tendencia a comer con el objetivo de regular emociones negativas, entre ellas el aburrimiento sin atender a las necesidades de hambre. El objetivo del presente estudio es examinar las relaciones existentes entre la tendencia al aburrimiento y los estilos de ingesta y la regulación emocional. Método: La muestra consiste en 123 personas adultas. Las medidas utilizadas incluyen los estilos de ingesta medidos a través del Dutch Eating Behavior Questionnaire (debq), la tendencia al aburrimiento, a través del Boredom Proneness Scale (bps ), la regulación emocional mediante el Emotion Regulation Questionnaire (erq) y la alexitimia, a través del Toronto Alexthymia Scale (tas-20). Resultados: Los resultados analizados, muestran una correlación negativa significativa entre la falta de estimulación interna (mayor experiencia de aburrimiento) y el comer emocional, con una mayor incapacidad para identificar las emociones. Por otro lado, se observan correlaciones significativas positivas entre la falta de estimulación externa y la dificultad para regular emociones, además de problemas para identificar los sentimientos y la dificultad para verbalizarlos. Conclusiones: La tendencia a sentir aburrimiento por la falta de estimulación interna, parece que se relaciona con una mayor tendencia a comer para regular emociones y la dificultad de etiquetarlas. El estudio del comer emocional y su relación con el aburrimiento, puede ser de gran ayuda a la hora de plantear intervenciones que tengan como objetivo la pérdida de peso o el cambio de estilos de vida.Background: Emotional eating refers to the tendency to eat with the aim of regulating negative emotions like boredom without taking care of the hunger necessities. The objective of the present study is to examine the relations between boredom proneness, the eating styles and emotional regulation. Method: The sample consists of 123 adult people. The measures used include eating styles measured through Dutch Eating Behavior Questionnaire (debq), Boredom Proneness with Boredom Proneness Scale (BSP ), the emotional regulation by the Emotion Regulation Questionnaire and the Alexithymia though Toronto Alexthymia Scale (tas-20). Results: The results show significant negative correlation between the lack of internal stimulation (greater experience of boredom) and emotional eating, with a greater incapacity to identify emotions. On the other hand, it is observed significant positive correlations between the lack of external stimulation and the difficulties in emotion regulation, in addition to, problems to identify feelings and the difficulty to verbalize them. Conclusions: The tendency to feel boredom by the lack of internal stimulation is related to a greater tendency to eat for regulating emotions and the problems to label them. The research of emotional eating and its relation with boredom, can be helpful to design interventions that target the weight loss or change lifestyles

Tree extraction and estimation of walnut structure parameters using airborne LiDAR data

[EN] The development of new tools based on remote sensing data in agriculture contributes to cost reduction, increased production, and greater profitability. Airborne LiDAR (Light Detection and Ranging) data show a significant potential for geometrically characterizing tree plantations. This study aims to develop a methodology to extract walnut (Juglans regia L.) crowns under leafless conditions using airborne LiDAR data. An original approach based on the alpha-shape algorithm, identification of local maxima, and k-means algorithms is developed to extract the crowns of walnut trees in a plot located in Viver (Eastern Spain) with 192 trees. In addition, stem diameter and volume, crown diameter, total height, and crown height were estimated from cloud metrics and other 2D parameters such as crown area, and diameter derived from LiDAR data. A correct identification was made of 178 trees (92.7%). For structure parameters, the most accurate results were obtained for crown diameter, stem diameter, and stem volume with coefficient of determination values (R-2) equal to 0.95, 0.87 and 0.83; and RMSE values of 0.43 m (5.70%), 0.02 m (9.35%) and 0.016 m(3) (21.55%), respectively. The models that gave the lowest R-2 values were 0.69 for total height and 0.70 for crown height, with RMSE values of 0.84 m (12.4%) and 0.83 m (14.5%), respectively. A suitable definition of the central and lower parts of tree canopies was observed. Results of this study generate valuable information, which can be applied for improving the management of walnut plantations.Estornell Cremades, J.; Hadas, E.; Marti-Gavila, J.; López- Cortés, I. (2021). Tree extraction and estimation of walnut structure parameters using airborne LiDAR data. International Journal of Applied Earth Observation and Geoinformation. 96:1-9. https://doi.org/10.1016/j.jag.2020.102273S199

Service Prototyping Lab Report - 2016 (Y1)

The annual activity report of the Service Prototyping Lab at Zurich University of Applied Sciences. Research trends and initiatives, research projects, transfer to education and local industry, academic community involvement, qualification and scientific development over the period of one year are among the covered topics

Estimation of Walnut Structure Parameters Using Terrestrial Photogrammetry Based on Structure-from-Motion (SfM)

[EN] Remote sensing techniques are increasingly used for crop monitoring to improve the profitability of plantations. These studies are mainly based on spectral information recorded by satellites or unmanned aerial vehicles. However, the development of Earth Observation Systems capable of retrieving 3D point clouds at an affordable cost enables the possibility of exploring new approaches in agriculture. In this context, more research is required to analyze the capability of 3D data for inventory, management and prediction of inputs (water, fertilizers and pesticides) and outputs (production, biomass) of fruit plantations. To do this, the complete representation of each tree contribute to extract the main geometric parameters. The objective of this work is to obtain regression models to estimate total height (H-t), crown height (H-c), stem diameter (D-s), crown diameter (D-c), stem volume (V-s) and crown volume (V-c) from 45 walnut specimens. For this, 3D models were computed for these trees by applying ground-based Structure from Motion (SfM). A circular photogrammetric survey of each tree was carried out using a standard digital camera and three-dimensional point clouds were retrieved for each tree. From these data, the tree parameters were computed. Linear regression models were obtained to estimate H-t, H-c, D-s, D-c, V-s and V-c, with R-2 values between 0.89 and 0.99. The results showed accurate fits between field parameters and those derived from 3D point clouds retrieved from SfM technique, indicating the applicability of this cost-effective method to model walnut trees and to extract their accurate parameters without costly field campaigns.Fernández-Sarría, A.; López- Cortés, I.; Marti-Gavila, J.; Estornell Cremades, J. (2022). Estimation of Walnut Structure Parameters Using Terrestrial Photogrammetry Based on Structure-from-Motion (SfM). Journal of the Indian Society of Remote Sensing. 50(10):1931-1944. https://doi.org/10.1007/s12524-022-01576-x193119445010Arnó, J., Masip, J., & Rosell-Polo, J. R. (2015). Influence of the scanned side of the row in terrestrial laser sensor applications in vineyards: Practical consequences. Precision Agriculture, 16(2), 119–128. https://doi.org/10.1007/s11119-014-9364-7Arnó, J., Vallès, J. M., Llorens, J., Sanz, R., Masip, J., Palacín, J., & Rosell-Polo, J. R. (2013). Leaf area index estimation in vineyards using a ground-based LiDAR scanner. Precision Agriculture, 14(3), 290–306. https://doi.org/10.1007/s11119-012-9295-0Auat Cheein, F., Guivant, J., Sanz, R., Escolà, A., Yandún, F., Torres-Torriti, M., & Rosell-Polo, J. R. (2015). Real-time approaches for characterization of fully and partially scanned canopies in groves. COMPAG, 118, 361–371. https://doi.org/10.1016/j.compag.2015.09.017Bork, E. W., & Su, J. G. (2007). Integrating LiDAR data and multispectral imagery for enhanced classification of rangeland vegetation: A meta analysis. Remote Sensing of Environment, 111, 11–24. https://doi.org/10.1016/j.rse.2007.03.011Brede, B., Calders, K., Lau, A., Raumonen, P., Bartholomeus, H., Herold, M., & Kooistra, L. (2019). Non-destructivetree volume estimation through quantitative structure modelling: Comparing UAV laser scanning with terrestrial LIDAR. Remote Sensing of Environment, 233, 111355. https://doi.org/10.1016/j.rse.2019.111355Cadena, C., Carlone, L., Carrillo, H., Latif, Y., Scaramuzza, D., Neira, J., Reid, I., & Leonard, J. J. (2016). Past, present, and future of simultaneous localization and mapping: Toward the robust-perception age. IEEE Transactions on Robotics, 32, 1309–1332. https://doi.org/10.1109/tro.2016.2624754Calders, 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, 6, 198–208. https://doi.org/10.1111/2041-210X.12301Chang, A., Jung, J., Maeda, M. M., & Landivar, J. (2017). Crop height monitoring with digital imagery from unmanned aerial system (UAS). COMPAG, 141, 232–237. https://doi.org/10.1016/j.compag.2017.07.008Cunliffe, A. M., Brazier, R. E., & Anderson, K. (2016). Ultra-fine grain landscape-scale quantification of dryland vegetation structure with drone-acquired structure-from-motion photogrammetry. Remote Sensing of Environment, 183, 129–143. https://doi.org/10.1016/j.rse.2016.05.019Dalla, A., Rex, F., Almeida, D., Sanquetta, C., Silva, C., Moura, M., Wilkinson, B., et al. (2020). Measuring individual tree diameter and height using gatoreyehigh-density UAV-lidar in an integrated crop-livestock-forest system. Remote Sensing, 12, 863. https://doi.org/10.3390/rs12050863De Eugenio, A., Fernández-Landa, A., & Merino-de-Miguel, S. (2018). 3D models from terrestrial photogrammetry in the estimation of forest inventory variables. Revista de Teledetección, 51, 113–124. https://doi.org/10.4995/raet.2018.9174Díaz-Varela, R., de la Rosa, R., León, L., & Zarco-Tejada, P. (2015). High-Resolution airborne UAV imagery to assess olive tree crown parameters using 3D photo reconstruction: Application in breeding trials. Remote Sensing, 7(4), 4213–4232. https://doi.org/10.3390/rs70404213Dong, J., Burnham, J.G., Boots, B., Rains, G., Dellaert, F. (2017). 4D crop monitoring: Spatio-temporal reconstruction for agriculture. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Singapore, pp. 3878–3885. https://doi.org/10.1109/ICRA.2017.7989447.Ehlert, D., Heisig, M., & Adamek, R. (2010). Suitability of a laser rangefinder to characterize winter wheat. Precision Agriculture, 11, 650–663.Escolà, A., Martínez-Casasnovas, J. A., Rufat, J., Arnó, J., Arbonés, A., Sebé, F., Pascual, M., Gregorio, E., & Rosell-Polo, J. R. (2017). Mobile terrestrial laser scanner applications in precision fruticulture/horticulture and tools to extract information from canopy point clouds. Precision Agriculture, 18, 111–132. https://doi.org/10.1007/s11119-016-9474-5Estornell, 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.2015.07.015Estornell, 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, 0(48), 67–76. https://doi.org/10.4995/raet.2017.7429Estornell, J., Velázquez-Martí, B., Fernández-Sarría, A., & Martí, J. (2018). Lidar methods for measurement of trees in urban forests. Journal of Applied Remote Sensing, 12(4), 046009. https://doi.org/10.1117/1.JRS.12.046009Fernández-Sarría, A., López-Cortés, I., Estornell, J., Velázquez-Martí, B., & Salazar, D. (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/10.1016/j.jag.2018.10.019Fernández-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. COMPAG, 90, 176–185.Gené-Mola, J., Gregorio López, E., Auat Cheein, F. A., Guevara, J., Llorens Calveras, J., Sanz Cortiella, R., & Rosell Polo, J. R. (2020). Fruit detection, yield prediction and canopy geometric characterization using LiDAR with forced air flow. COMPAG, 168, 105121. https://doi.org/10.1016/j.compag.2019.105121Gil, E., Arnó, J., Llorens, J., Sanz, R., Llop, J., Rosell-Polo, J. R., Gallart, M., & Escolà, A. (2014). Advanced technologies for the improvement of spray application techniques in Spanish viticulture: An overview. Sensors, 14, 691–708. https://doi.org/10.3390/s140100691Goesele, M., Snavely, N., Seitz, S.M., Curless, B., Hoppe, H. (2007). Multi-view stereo for community photo collections. In Proceedings of the11th International Conference on Computer Vision, Rio de Janeiro, Brazil pp. 1–8. https://doi.org/10.1109/ICCV.2007.4408933.Gómez-Candón, D., De Castro, A. I., & López-Granados, F. (2014). Assessing the accuracy of mosaics from unmanned aerial vehicle (UAV) imagery for precision agriculture purposes in wheat. Precision Agriculture, 15(1), 44–56. https://doi.org/10.1007/s11119-013-9335-4Gonzalez de Tanago, J., Lau, A., Bartholomeus, H., Herold, M., Avitabile, V., Raumonen, P., Martius, C., Goodman, R., Disney, M., Manuri, S., et al. (2018). Estimation of above ground biomass of large tropical trees with terrestrial LiDAR. Methods in Ecology and Evolution, 9(2), 223–234. https://doi.org/10.1111/2041-210X.12904Guerra-Hernández, J., Cosenza, D. N., Estraviz Rodriguez, L. C., Silva, M., Tomé, M., Díaz-Varela, R. A., & González-Ferreiro, E. (2018). Comparison of ALS- and UAV(SfM)-derived high-density point clouds for individual tree detection in Eucalyptus plantations. International Journal of Remote Sensing, 39(15–16), 5211–5235. https://doi.org/10.1080/01431161.2018.1486519Hadas, E., Borkowski, A., Estornell, J., & Tymkow, P. (2017). Automatic estimation of olive tree dendrometric parameters based on airborne laser scanning data using alpha-shape and principal component analysis. GIScience & Remote Sensing, 54(6), 898–917. https://doi.org/10.1080/15481603.2017.1351148Hargreaves, G. H. (1994). Defining and using reference evapotranspiration. Journal of Irrigation and Drainage Engineering. https://doi.org/10.1061/(ASCE)0733-9437(1994)120:6(1132)Heinzel, J., & Huber, M. O. (2017). Tree stem diameter estimation from volumetric TLS image data. Remote Sensing, 9, 614. https://doi.org/10.3390/rs9060614Jay, S., Rabatel, G., Hadoux, X., Moura, D., & Gorretta, N. (2015). In-field crop row phenotyping from 3D modeling performed using Structure from motion. COMPAG, 110, 70–77.Jenkins, J., Chojnack, D., Heath, L., Birdsey, R. (2004). Comprehensive database of diameter-based biomass regressions for north american tree Species; United States Forest Service, Northeastern Research Station, p. 45.Jiménez-Brenes, F. M., López-Granados, F., Castro, A. I., Torres-Sánchez, J., Serrano, N., & Peña, J. M. (2017). Quantifying pruning impacts on olive tree architecture and annual canopy growth by using UAV-based 3D modelling. Plant Methods, 13, 1–15. https://doi.org/10.1186/s13007-017-0205-3Kankare, I., Räty, M., Yu, X., Holopainen, M., Vastaranta, M., Kantola, T., Hyyppä, J., Hyyppä, H., Alho, P., & Viitala, R. (2013). Single tree biomass modelling using airborne laser scanning. ISPRS Journal of Photogrammetry and Remote Sensing, 85, 66–73. https://doi.org/10.1016/j.isprsjprs.2013.08.008Lefsky, M. A., Cohen, W. B., Parker, G. G., & Harding, D. J. (2002). LiDAR remote sensing for ecosystem studies. BioScience, 52, 19–30.Liang, X., Kankare, V., Hyyppä, J., Wang, Y., Kukko, A., Haggrén, H., Yu, X., Kaartinen, H., Jaakola, A., Guan, F., Holopainen, M., & Vastaranta, M. (2016). Terrestrial laser scanning in forest inventories. ISPRS Journal of Photogrammetry and Remote Sensing, 115, 63–77.López-Cortés, I., Martí-Gavilá, J., Estornell, J., Fernández-Sarría, A. (2019). Comparación de parámetros de olivos a partir de UAV y datos LiDAR aéreos. In Proceedings of XVIII Congreso de la Asociación Española de Teledetección, Valladolid, pp. 24–27 September 2019; pp. 439–442.Lowe, D. (2004). Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60(2), 91–110. https://doi.org/10.1023/B:VISI.0000029664.99615.94Maltamo, M., Räty, J., Korhonen, L., Kotivuori, E., Kukkonen, M., Peltola, H., Kangas, J., & Packalen, P. (2020). Prediction of forest canopy fuel parameters in managed boreal forests using multispectral and unispectral airborne laser scanning data and aerial images. European Journal of Remote Sensing. https://doi.org/10.1080/22797254.2020.1816142Miao, Y., Mulla, D. J., Randall, G. W., Vetsch, J. A., & Vintila, R. (2009). Combining chlorophyll meter readings and high spatial resolution remote sensing images for in-season site-specific nitrogen management of corn. Precision Agriculture, 10, 45–62. https://doi.org/10.1007/s11119-008-9091-zMiller, J., Morgenroth, J., & Gomez, C. (2015). 3D modelling of individual trees using a handheld camera: Accuracy of height, diameter and volume estimates. Urban for Urban Green, 14(4), 932–940. https://doi.org/10.1016/j.ufug.2015.09.001Ministerio de Agricultura, Pesca y Alimentación (2019). Encuesta sobre superficies y rendimientos cultivos (ESYRCE). Encuesta de marco de áreas de España. p. 178. Retrieved 15 Sept 2021 from https://www.mapa.gob.es/es/estadistica/temas/estadisticas-agrarias/agricultura/esyrce/.Miranda-Fuentes, A., Llorens, J., Rodriguez-Lizana, A., Cuenca, A., Gil, E., Blanco-Roldán, G. L., & Gil-Ribes, J. A. (2016). Assessing the optimal liquid volume to be sprayed on isolated olive trees according to their canopy volumes. STOTEN, 568, 296–305. https://doi.org/10.1016/j.scitotenv.2016.06.013Moorthy, 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.2010.10.005Neuenschwander, A., & Pitts, K. (2019). The ATL08 land and vegetation product for the ICESat-2 Mission. Remote Sensing of Environment, 221, 247–259. https://doi.org/10.1016/j.rse.2018.11.005Palacín, J., Pallejà, T., Tresanchez, M., Sanz, R., Llorens, J., Ribes-Dasi, M., Masip, J., Arnó, J., Escolà, A., & Rosell, J. R. (2007). Real-time tree-foliage surface estimation using a ground laser scanner. IEEE Transactions on Instrumentation and Measurement, 56(4), 1377–1383. https://doi.org/10.1109/TIM.2007.900126Pierzchala, M., Giguère, P., & Astrup, R. (2018). Mapping forests using an unmanned ground vehicle with 3D LiDAR and graph-slam. COMPAG, 145, 217–225. https://doi.org/10.1016/j.compag.2017.12.034Pitkänen, T. P., Raumonen, P., & Kangas, A. (2019). Measuring stem diameters with TLS in boreal forests complementary fitting procedure. ISPRS Journal of Photogrammetry and Remote Sensing, 147, 294–306. https://doi.org/10.1016/j.isprsjprs.2018.11.027Popescu, S. C. (2007). Estimating biomass of individual pine trees using airborne LiDAR. Biomass and Bioenergy, 31(9), 646–655. https://doi.org/10.1016/j.biombioe.2007.06.022Sanz, R., Llorens, J., Escolà, A., Arnó, J., Planas, S., Román, C., & Rosell-Polo, J. R. (2018). LiDAR and non-LiDAR-based canopy parameters to estimate the leaf area in fruit trees and vineyard. Agricultural and Forest Meteorology, 260–261, 229–239. https://doi.org/10.1016/j.agrformet.2018.06.017Schlaegel, B. (1984). Green ash volume and weight tables. US Department of Agriculture, Forest Service, Southern Forest Experiment Station.Sheridan, R. D., Popescu, S. C., Gatziolis, D., Morgan, C. L. S., & Ku, N. W. (2015). Modeling forest aboveground biomass and volume using airborne LiDAR metrics and forest inventory and analysis data in the Pacific Northwest. Remote Sensing, 7, 229–255. https://doi.org/10.3390/rs70100229Snavely, N., Seitz, S. M., & Szeliski, R. (2008). Modeling the world from Internet photo collections. International Journal of Computer Vision, 80(2), 189–210. https://doi.org/10.1007/s11263-007-0107-3Stereńczak, K., Kraszewski, B., Mielcarek, M., Piasecka, N., Lisiewicz, M., & Heurich, M. (2020). Mapping individual trees with airborne laser scanning data in an European lowland forest using a selfcalibration algorithm. International Journal of Applied Earth Observation and Geoinformation, 93, 102191. https://doi.org/10.1016/j.jag.2020.102191Tagarakis, A. C., Koundouras, S., Fountas, S., & Gemtos, T. (2018). Evaluation of the use of LIDAR laser scanner to map pruning wood in vineyards and its potential for management zones delineation. Precision Agriculture, 19, 334–347. https://doi.org/10.1007/s11119-017-9519-4Torres-Sánchez, J., de Castro, A., Peña, J. M., Jiménez-Brenes, F. M., Arquero, O., Lovera, M., et al. (2018). Mapping the 3D structure of almond trees using UAV acquired photogrammetric point clouds and object-based image analysis. Biosystems Engineering, 176, 172–184. https://doi.org/10.1016/j.biosystemseng.2018.10.018Torres-Sánchez, J., López-Granados, F., Serrano, N., Arquero, O., & Peña, J. M. (2015). High-throughput 3-D monitoring of agricultural-tree plantations with unmanned aerial vehicle (UAV) technology. PLoS ONE, 10(6), e0130479. https://doi.org/10.1371/journal.pone.0130479Valbuena, M. A., Santamaría, J., & Sanz, F. (2016). Estimation of diameter and height of individual trees for Pinus sylvestris L. based on the individualising of crowns using airborne LiDAR and the national forest inventory data. Forest Systems, 25(1), e046. https://doi.org/10.5424/fs/2016251-05790Van der Zande, V., Hoet, W., Jonckheere, I., van Aardt, J., & Coppin, P. (2006). Influence of measurement set-up of ground-based LiDAR for derivation of tree structure. Agricultural and Forest Meteorology, 141(2–4), 147–160. https://doi.org/10.1016/j.agrformet.2006.09.007Velázquez-Martí, B., Fernández-González, E., López-Cortes, I., & Salazar-Hernández, D. M. (2011). Quantification of the residual biomass obtained from pruning of trees in Mediterranean olive groves. Biomass and Bioenergy, 35(2), 3208–3217. https://doi.org/10.1016/j.biombioe.2011.04.042Velázquez-Martí, B., López-Cortés, I., & Salazar, D. M. (2014). Dendrometric analysis of olive trees for wood biomass quantification in Mediterranean orchards. Agroforestry Systems, 88(5), 755–765. https://doi.org/10.1007/s10457-014-9718-1Walklate, P. J., Cross, J. V., Richardson, G. M., Murray, R. A., & Baker, D. E. (2002). Comparison of different spray volume deposition models using LIDAR measurements of apple orchards. Biosystems Engineering, 82(3), 253–267.Wallace, L., Lucieer, A., Malenovský, Z., Turner, D., & Vopenka, P. (2016). Assessment of forest structure using two UAV Techniques: a comparison of airborne laser scanning and structure from motion (SfM) point clouds. Forests, 7, 62. https://doi.org/10.3390/f7030062Wang, X., Cheng, X., Gong, P., Huang, H., Li, Z., & Li, X. (2011). Earth science applications of ICESat/GLAS: A review. International Journal of Remote Sensing, 32(23), 8837–8864.Wieser, M., Mandlburger, G., Hollaus, M., Otepka, J., Glira, P., & Pfeifer, N. (2017). A case study of UAS borne laser scanning for measurement of tree stem diameter. Remote Sensing, 9, 1154. https://doi.org/10.3390/rs9111154Xie, Q., Dash, J., Huete, A., Jiang, A., Yin, G., Ding, Y., Peng, D., Hall, C. C., Brown, L., Shi, Y., et al. (2019). Retrieval of crop biophysical parameters from Sentinel-2 remote sensing imagery. International Journal of Applied Earth Observation and Geoinformation, 80, 187–195. https://doi.org/10.1016/j.jag.2019.04.019Xing, D., Bergeron, J. C., Solarik, K. A., Tomm, B., Macdonald, S. E., Spence, J. R., & He, F. (2019). Challenges in estimating forest biomass: Use of allometric equations for three boreal tree species. Canadian Journal of Forest Research, 49(12), 1613–1622.Zarco-Tejada, P. J., Diaz-Varela, R., Angileri, V., & Loudjani, P. (2014). Tree height quantification using very high resolution imagery acquired from an unmanned aerial vehicle (UAV) and automatic 3D photo-reconstruction methods. European Journal of Agronomy, 255, 89–99.Zhang, Z., Cao, L., & She, G. (2017). Estimating forest structural parameters using canopy metrics derived from airborne LiDAR data in subtropical forests. Remote Sens, 9, 940. https://doi.org/10.3390/rs909094

Using one-dimensional modeling to analyse the influence of the use of biodiesels on the dynamic behavior of solenoid-operated injectors in common rail systems: Detailed injection system model

A combined experimental and computational investigation has been performed in order to evaluate the influence of physical properties of biodiesel on the injection process in a common-direct injection system with second generation solenoid injectors. For that purpose, after a complete characterization of the system, which involved mechanical and hydraulic characterization, a one-dimensional model has been obtained and extensively validated. Simulations have then been performed with a standard diesel and a 100% rape methyl ester (RME) biodiesel which allowed a comparison and analysis of the dynamic response of the injector to be done. Different injection strategies involving main injection and main plus post-injection have been used to explore the impact of the use of biodiesel on the performance and stability of solenoid injectors. As far as the dynamic response of the injector is concerned, the results obtained have clearly shown that the use of biodiesel affects the dynamic response of the needle, especially at low injection pressures. The behavior of the system under multi-injection strategies (main plus post-injection) has been also evaluated determining for different operating conditions (injection pressures and backpressures) the minimum dwell time between injections to assure a stable behavior in the injection process (mass flow rate). Important differences have been found between biodiesel and standard diesel in this critical parameter at low injection pressures, becoming less important at high injection pressure. Finally, a modification on the injector hardware has been proposed in order to compensate these differences.This research has been funded by "Ministerio de Ciencia e Innovacion" in the frame of the project "Estudio teorico experimental de la influencia del combustible sobre la cavitacion y el desarrollo del chorro evaporative (FlexiFuel)", Reference TRA2010-17564.Payri Marín, R.; Salvador Rubio, FJ.; Marti Aldaravi, P.; Martínez López, J. (2012). Using one-dimensional modeling to analyse the influence of the use of biodiesels on the dynamic behavior of solenoid-operated injectors in common rail systems: Detailed injection system model. Energy Conversion and Management. 54(1):90-99. https://doi.org/10.1016/j.enconman.2011.10.004S909954

Adaptation strategies to climate change in the tourist sector: The case of coastal tourism in Spain

Tourism activities, that are very important in the Spanish Mediterranean coast since 60s, have been described as highly vulnerable to climate change. Diversification of the tourism and tourist products are often presented as a possible strategy for adapting to the effects of climate change. The present study explores the initiatives in product diversification that are being put into practice in the Spanish Mediterranean coastal tourism sector. To this end, the study focuses on the analysis of the experiences of the rural tourism sector as an alternative to sun-and-sand tourism in the Alt Empordà (Costa Brava, North-eastern Spain). Methodology of this research is based in two aspects: a) desk research of relevant public documents aimed to promote the diversification of the tourist sector; b) regional survey of rural tourism establishments. The analysis reveals a process of diversification that is characterised by spontaneous developments that lack planning and shows an absence of product structuring in accordance with a segmentation of the market. Given these characteristics, the process of diversification that has taken place will not contribute to increasing adaptation\u27s capacity of tourism to climate change or, consequently, to reducing its level of vulnerability

Adaptation strategies to climate change in the tourist sector: The case of coastal tourism in Spain

Tourism activities, that are very important in the Spanish Mediterranean coast since 60s, have been described as highly vulnerable to climate change. Diversification of the tourism and tourist products are often presented as a possible strategy for adapting to the effects of climate change. The present study explores the initiatives in product diversification that are being put into practice in the Spanish Mediterranean coastal tourism sector. To this end, the study focuses on the analysis of the experiences of the rural tourism sector as an alternative to sun-and-sand tourism in the Alt Empordà (Costa Brava, North-eastern Spain). Methodology of this research is based in two aspects: a) desk research of relevant public documents aimed to promote the diversification of the tourist sector; b) regional survey of rural tourism establishments. The analysis reveals a process of diversification that is characterised by spontaneous developments that lack planning and shows an absence of product structuring in accordance with a segmentation of the market. Given these characteristics, the process of diversification that has taken place will not contribute to increasing adaptation\u27s capacity of tourism to climate change or, consequently, to reducing its level of vulnerability

Effect of turbulent model closure and type of inlet boundary condition on a Large Eddy Simulation of a non-reacting jet with co-flow stream

[EN] In this paper, the behavior and turbulence structure of a non-reacting jet with a co-flow stream is described by means of Large Eddy Simulations (LES) carried out with the computational tool OpenFoam. In order to study the influence of the sub-grid scale (SGS) model on the main flow statistics, Smagorinsky (SMAG) and One Equation Eddy (OEE) approaches are used to model the smallest scales involved in the turbulence of the jet. The impact of cell size and turbulent inlet boundary condition in resulting velocity profiles is analyzed as well. Four different tasks have been performed to accomplish these objectives. Firstly, the simulation of a turbulent pipe, which is necessary to generate and map coherent turbulence structure into the inlet of the non-reacting jet domain. Secondly, a structured mesh based on hexahedrons has been built for the jet and its co-flow. The third task consists on performing four different simulations. In those, mapping statistics from the turbulent pipe is compared with the use of fluctuating inlet boundary condition available in OpenFoam; OEE and SMAG approaches are contrasted; and the effect of changing cell size is investigated. Finally, as forth task, the obtained results are compared with experimental data. As main conclusions of this comparison, it has been proved that the fluctuating boundary condition requires much less computational cost, but some inaccuracies were found close to the nozzle. Also, both SGS models are capable to simulate this kind of jets with a co-flow stream with exactitude.This research was performed in the frame of the project "Estudio de la interaccion chorro-pared en condiciones realistas de motor" reference TRA2015-67679-c2-1-R from Ministerio de Economia y Competitividad (Spanish Ministry of Economy). The equipment used in this work has been partially supported by FEDER Project funds "Dotacion de infraestructuras cientifico tectinas para el Centro Integral de Mejora Energetica y Medioambiental de Sistemas de Transporte (CiMeT), (FEDER-ICTS-2012-06)", framed in the operation program of unique scientific and technical infrastructure of the Ministry of Science and Innovation of Spain. Jhoan S. Giraldo was supported by a research grant from Generalitat Valenciana (Programa Santiago Grisolia, GRISOLIA/2013/007).Payri Marín, R.; López Sánchez, JJ.; Marti-Aldaravi, P.; Giraldo Valderrama, JS. (2016). Effect of turbulent model closure and type of inlet boundary condition on a Large Eddy Simulation of a non-reacting jet with co-flow stream. International Journal of Heat and Fluid Flow. 61:545-552. https://doi.org/10.1016/j.ijheatfluidflow.2016.06.016S5455526

The Succession in Firm Top Management and the Successor Origin: Moderating Variables

El objetivo de nuestro estudio es, por un lado, avanzar en el conocimiento de las causas que pueden provocar un cambio en la alta dirección de la empresa, y, por otro, conocer los factores que pueden influir en el origen del sucesor, considerando algunas de las variables que habitualmente han sido omitidas por la literatura previa: sucesión forzada o no forzada y poder del alto directivo dentro del gobierno corporativo de la empresa. Los resultados obtenidos indican que la principal variable que influye en la sucesión forzada y en el origen del sucesor, es el rendimiento previo. Esta relación, sin embargo, se encuentra moderada por el efecto interactivo o moderador que ejercen otra serie de variables indicativas del poder que dicho directivo posee dentro la empresa, como es el caso de la composición del Consejo de Administración, la participación de alto directivo en la propiedad de la empresa, su antigüedad en el cargo como directivo, el tamaño de la empresa o la edad de la empresa.The objective of our study is, on the one hand, to gain further knowledge into the causes that can bring about a change in firm top management, and, on the other, to know the factors that may have some influence on successor origin, considering some of the variables that have habitually been ignored by the previous literature: torced succession or non-forced succession and the power of the top manager inside the firm's corporative governance. The results obtained indícate that the main variable influencing the scenario of torced succession and the successor origin, is prior performance. This relation, however, is conditioned by the interactive or moderating effect exercised by another series of variables that are indicative of the power this manager has inside the firm, as is the composition ofthe board of directors, the top manager's participation in firm ownership, the number of years he has held the post, the firm size, or the age firm

El análisis de la cohesión, vinculación e integración sociales en las encuestas EgoNet

Background of INCASI Project H2020-MSCA-RISE-2015 GA 691004. WP1: CompilationEl objetivo de este artículo consiste en mostrar algunas de las posibilidades de análisis que ofrecen las redes Ego-centradas en lo que se refiere a la Cohesión, Vinculación e Integración social. El artículo indaga en ellas haciendo una propuesta de operativización de dichos conceptos y de análisis a partir de un caso de aplicación. Los datos empleados en los ejemplos ilustrativos de los conceptos provienen de una encuesta de redes Ego-centradas realizada en Catalunya.The objective of these papers consists to showing some possibilities of analysis Ego-net about social Cohesion, Linking and Integration. A proposal is done in order to analyze these concepts. The data used in the illustrative examples of the concepts come from a survey of Ego-centered networks in Catalonia