Forestry Applications of Unmanned Aerial Vehicles (UAVs) 2019
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-bas...
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| Format: | Online |
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| Sprache: | Englisch |
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MDPI - Multidisciplinary Digital Publishing Institute
2021
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| Online-Zugang: | ONIX_20210501_9783039367542_1077 |
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| collection | Directory of Open Access Books |
| description | 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. |
| format | Online |
| id | doab-20.500.12854ir-69331 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-693312024-03-28T03:31:03Z Forestry Applications of Unmanned Aerial Vehicles (UAVs) 2019 Matese, Alessandro unmanned 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 thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PS Biology, life sciences thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNA Agribusiness and primary industries::KNAL Forestry industry 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. 2021-05-01T15:46:53Z 2021-05-01T15:46:53Z 2020 book ONIX_20210501_9783039367542_1077 9783039367542 9783039367559 https://directory.doabooks.org/handle/20.500.12854/69331 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/3123 https://mdpi.com/books/pdfview/book/3123 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-03936-755-9 10.3390/books978-3-03936-755-9 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783039367542 9783039367559 184 Basel, Switzerland open access |
| spellingShingle | unmanned 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 thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PS Biology, life sciences thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNA Agribusiness and primary industries::KNAL Forestry industry Forestry Applications of Unmanned Aerial Vehicles (UAVs) 2019 |
| title | Forestry Applications of Unmanned Aerial Vehicles (UAVs) 2019 |
| title_full | Forestry Applications of Unmanned Aerial Vehicles (UAVs) 2019 |
| title_fullStr | Forestry Applications of Unmanned Aerial Vehicles (UAVs) 2019 |
| title_full_unstemmed | Forestry Applications of Unmanned Aerial Vehicles (UAVs) 2019 |
| title_short | Forestry Applications of Unmanned Aerial Vehicles (UAVs) 2019 |
| title_sort | forestry applications of unmanned aerial vehicles uavs 2019 |
| topic | unmanned 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 thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PS Biology, life sciences thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNA Agribusiness and primary industries::KNAL Forestry industry |
| topic_facet | unmanned 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 thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PS Biology, life sciences thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNA Agribusiness and primary industries::KNAL Forestry industry |
| url | ONIX_20210501_9783039367542_1077 |