000			01498nam a2200121Ia 4500
008			220615s9999||||xx |||||||||||||| ||und||
245		0	_aForestry Applications of Unmanned Aerial Vehicles (UAVs) 2019
546			_aEnglish[eng]
650			_aunmanned aerial vehicles||seedling detection||forest regeneration||reforestation||establishment survey||machine learning||multispectral classification||UAV photogrammetry||forest modeling||ancient trees measurement||tree age prediction||Mauritia flexuosa||semantic segmentation||end-to-end learning||convolutional neural network||forest inventory||Unmanned Aerial Systems (UAS)||structure from motion (SfM)||Unmanned Aerial Vehicles (UAV)||Photogrammetry||Thematic Mapping||Accuracy Assessment||Reference Data||Forest Sampling||Remote Sensing||Robinia pseudoacacia L.||reproduction||spreading||short rotation coppice||unmanned aerial system (UAS)||object-based image analysis (OBIA)||convolutional neural network (CNN)||juniper woodlands||ecohydrology||remote sensing||unmanned aerial systems||central Oregon||rangelands||seedling stand inventorying||photogrammetric point clouds||hyperspectral imagery||leaf-off||leaf-on||UAV||multispectral image||forest fire||burn severity||classification||precision agriculture||biomass evaluation||image processing||Castanea sativa||unmanned aerial vehicles (UAV)||precision forestry||forestry applications||RGB imagery
700			_aMatese, Alessandro
856			_uhttps://mdpi.com/books/pdfview/book/3123
942			_cEB
999			_c8392 _d8392