04594nam 2201069z- 450 991055711210332120210501(CKB)5400000000040925(oapen)https://directory.doabooks.org/handle/20.500.12854/69331(oapen)doab69331(EXLCZ)99540000000004092520202105d2020 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierForestry Applications of Unmanned Aerial Vehicles (UAVs) 2019Basel, SwitzerlandMDPI - Multidisciplinary Digital Publishing Institute20201 online resource (184 p.)3-03936-754-4 3-03936-755-2 Unmanned 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.Forestry Applications of Unmanned Aerial Vehicles Biology, life sciencesbicsscForestry & related industriesbicsscResearch & information: generalbicsscAccuracy Assessmentancient trees measurementbiomass evaluationburn severityCastanea sativacentral Oregonclassificationconvolutional neural networkconvolutional neural network (CNN)ecohydrologyend-to-end learningestablishment surveyforest fireforest inventoryforest modelingforest regenerationForest Samplingforestry applicationshyperspectral imageryimage processingjuniper woodlandsleaf-offleaf-onmachine learningMauritia flexuosamultispectral classificationmultispectral imageobject-based image analysis (OBIA)photogrammetric point cloudsPhotogrammetryprecision agricultureprecision forestryrangelandsReference Datareforestationremote sensingRemote SensingreproductionRGB imageryRobinia pseudoacacia L.seedling detectionseedling stand inventoryingsemantic segmentationshort rotation coppicespreadingstructure from motion (SfM)Thematic Mappingtree age predictionUAVUAV photogrammetryunmanned aerial system (UAS)unmanned aerial systemsUnmanned Aerial Systems (UAS)unmanned aerial vehiclesunmanned aerial vehicles (UAV)Unmanned Aerial Vehicles (UAV)Biology, life sciencesForestry & related industriesResearch & information: generalMatese Alessandroedt1293412Matese AlessandroothBOOK9910557112103321Forestry Applications of Unmanned Aerial Vehicles (UAVs) 20193022594UNINA