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dc.contributor.editorMatese, Alessandro
dc.date.accessioned2021-05-01T15:46:53Z
dc.date.available2021-05-01T15:46:53Z
dc.date.issued2020
dc.identifierONIX_20210501_9783039367542_1077
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/69331
dc.description.abstractUnmanned aerial vehicles (UAVs) are new platforms that have been increasingly used in the last few years for forestry applications that benefit from the added value of flexibility, low cost, reliability, autonomy, and capability of timely provision of high-resolution data. The main adopted image-based technologies are RGB, multispectral, and thermal infrared. LiDAR sensors are becoming commonly used to improve the estimation of relevant plant traits. In comparison with other permanent ecosystems, forests are particularly affected by climatic changes due to the longevity of the trees, and the primary objective is the conservation and protection of forests. Nevertheless, forestry and agriculture involve the cultivation of renewable raw materials, with the difference that forestry is less tied to economic aspects and this is reflected by the delay in using new monitoring technologies. The main forestry applications are aimed toward inventory of resources, map diseases, species classification, fire monitoring, and spatial gap estimation. This Special Issue focuses on new technologies (UAV and sensors) and innovative data elaboration methodologies (object recognition and machine vision) for applications in forestry.
dc.languageEnglish
dc.subject.classificationthema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: generalen_US
dc.subject.classificationthema EDItEUR::P Mathematics and Science::PS Biology, life sciencesen_US
dc.subject.classificationthema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNA Agribusiness and primary industries::KNAL Forestry industryen_US
dc.subject.otherunmanned aerial vehicles
dc.subject.otherseedling detection
dc.subject.otherforest regeneration
dc.subject.otherreforestation
dc.subject.otherestablishment survey
dc.subject.othermachine learning
dc.subject.othermultispectral classification
dc.subject.otherUAV photogrammetry
dc.subject.otherforest modeling
dc.subject.otherancient trees measurement
dc.subject.othertree age prediction
dc.subject.otherMauritia flexuosa
dc.subject.othersemantic segmentation
dc.subject.otherend-to-end learning
dc.subject.otherconvolutional neural network
dc.subject.otherforest inventory
dc.subject.otherUnmanned Aerial Systems (UAS)
dc.subject.otherstructure from motion (SfM)
dc.subject.otherUnmanned Aerial Vehicles (UAV)
dc.subject.otherPhotogrammetry
dc.subject.otherThematic Mapping
dc.subject.otherAccuracy Assessment
dc.subject.otherReference Data
dc.subject.otherForest Sampling
dc.subject.otherRemote Sensing
dc.subject.otherRobinia pseudoacacia L.
dc.subject.otherreproduction
dc.subject.otherspreading
dc.subject.othershort rotation coppice
dc.subject.otherunmanned aerial system (UAS)
dc.subject.otherobject-based image analysis (OBIA)
dc.subject.otherconvolutional neural network (CNN)
dc.subject.otherjuniper woodlands
dc.subject.otherecohydrology
dc.subject.otherremote sensing
dc.subject.otherunmanned aerial systems
dc.subject.othercentral Oregon
dc.subject.otherrangelands
dc.subject.otherseedling stand inventorying
dc.subject.otherphotogrammetric point clouds
dc.subject.otherhyperspectral imagery
dc.subject.otherleaf-off
dc.subject.otherleaf-on
dc.subject.otherUAV
dc.subject.othermultispectral image
dc.subject.otherforest fire
dc.subject.otherburn severity
dc.subject.otherclassification
dc.subject.otherprecision agriculture
dc.subject.otherbiomass evaluation
dc.subject.otherimage processing
dc.subject.otherCastanea sativa
dc.subject.otherunmanned aerial vehicles (UAV)
dc.subject.otherprecision forestry
dc.subject.otherforestry applications
dc.subject.otherRGB imagery
dc.titleForestry Applications of Unmanned Aerial Vehicles (UAVs) 2019
dc.typebook
oapen.identifier.doi10.3390/books978-3-03936-755-9
oapen.relation.isPublishedBy46cabcaa-dd94-4bfe-87b4-55023c1b36d0
oapen.relation.isbn9783039367542
oapen.relation.isbn9783039367559
oapen.pages184
oapen.place.publicationBasel, Switzerland


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