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      Quantifying pruning impacts on olive tree architecture and annual canopy growth by using UAV-based 3D modelling

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          Tree pruning is a costly practice with important implications for crop harvest and nutrition, pest and disease control, soil protection and irrigation strategies. Investigations on tree pruning usually involve tedious on-ground measurements of the primary tree crown dimensions, which also might generate inconsistent results due to the irregular geometry of the trees. As an alternative to intensive field-work, this study shows a innovative procedure based on combining unmanned aerial vehicle (UAV) technology and advanced object-based image analysis (OBIA) methodology for multi-temporal three-dimensional (3D) monitoring of hundreds of olive trees that were pruned with three different strategies (traditional, adapted and mechanical pruning). The UAV images were collected before pruning, after pruning and a year after pruning, and the impacts of each pruning treatment on the projected canopy area, tree height and crown volume of every tree were quantified and analyzed over time.


          The full procedure described here automatically identified every olive tree on the orchard and computed their primary 3D dimensions on the three study dates with high accuracy in the most cases. Adapted pruning was generally the most aggressive treatment in terms of the area and volume (the trees decreased by 38.95 and 42.05% on average, respectively), followed by trees under traditional pruning (33.02 and 35.72% on average, respectively). Regarding the tree heights, mechanical pruning produced a greater decrease (12.15%), and these values were minimal for the other two treatments. The tree growth over one year was affected by the pruning severity and by the type of pruning treatment, i.e., the adapted-pruning trees experienced higher growth than the trees from the other two treatments when pruning intensity was low (<10%), similar to the traditionally pruned trees at moderate intensity (10–30%), and lower than the other trees when the pruning intensity was higher than 30% of the crown volume.


          Combining UAV-based images and an OBIA procedure allowed measuring tree dimensions and quantifying the impacts of three different pruning treatments on hundreds of trees with minimal field work. Tree foliage losses and annual canopy growth showed different trends as affected by the type and severity of the pruning treatments. Additionally, this technology offers valuable geo-spatial information for designing site-specific crop management strategies in the context of precision agriculture, with the consequent economic and environmental benefits.

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          Most cited references 41

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          The application of small unmanned aerial systems for precision agriculture: a review

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            Geographic Object-Based Image Analysis – Towards a new paradigm

            The amount of scientific literature on (Geographic) Object-based Image Analysis – GEOBIA has been and still is sharply increasing. These approaches to analysing imagery have antecedents in earlier research on image segmentation and use GIS-like spatial analysis within classification and feature extraction approaches. This article investigates these development and its implications and asks whether or not this is a new paradigm in remote sensing and Geographic Information Science (GIScience). We first discuss several limitations of prevailing per-pixel methods when applied to high resolution images. Then we explore the paradigm concept developed by Kuhn (1962) and discuss whether GEOBIA can be regarded as a paradigm according to this definition. We crystallize core concepts of GEOBIA, including the role of objects, of ontologies and the multiplicity of scales and we discuss how these conceptual developments support important methods in remote sensing such as change detection and accuracy assessment. The ramifications of the different theoretical foundations between the ‘per-pixel paradigm’ and GEOBIA are analysed, as are some of the challenges along this path from pixels, to objects, to geo-intelligence. Based on several paradigm indications as defined by Kuhn and based on an analysis of peer-reviewed scientific literature we conclude that GEOBIA is a new and evolving paradigm.
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              UAV for 3D mapping applications: a review


                Author and article information

                +34 917452500 , jose.pena@fulbrightmail.org , jmpena@ica.csic.es , mediciona@gmail.com
                Plant Methods
                Plant Methods
                Plant Methods
                BioMed Central (London )
                6 July 2017
                6 July 2017
                : 13
                [1 ]ISNI 0000 0001 2183 4846, GRID grid.4711.3, Institute for Sustainable Agriculture, , CSIC, ; 14004 Córdoba, Spain
                [2 ]ISNI 0000 0001 2195 4653, GRID grid.425162.6, , Institute of Agricultural Research and Training (IFAPA), ; 14004 Córdoba, Spain
                [3 ]ISNI 0000 0001 2183 4846, GRID grid.4711.3, Institute of Agricultural Sciences, , CSIC, ; 28006 Madrid, Spain
                © The Author(s) 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                Funded by: Unit of Information Resources for Research (URICI)
                Funded by: The Spanish Ministry of Economy, Industry and Competitiveness, MINECO
                Award ID: AGL2014-52465-C4-4R project
                Funded by: CSIC - Intramural projects
                Award ID: 201640E034
                Funded by: Spanish MINECO
                Award ID: Juan de la Cierva
                Award ID: FPI
                Award ID: Ramón y Cajal
                Award Recipient :
                Methodology Article
                Custom metadata
                © The Author(s) 2017


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