Remote Sensing and Visualization Methods
The aim of this reprint is to provide a comprehensive exploration of the latest advancements in forestry through the integration of emerging technologies. This publication delves into several key areas, including the application of remote sensing and visualization techniques, the use of digital twin...
محفوظ في:
| المؤلفون الرئيسيون: | , , , , , , , , , |
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| التنسيق: | Online |
| اللغة: | الإنجليزية |
| منشور في: |
MDPI - Multidisciplinary Digital Publishing Institute
2026
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://directory.doabooks.org/handle/20.500.12854/170593 |
| الوسوم: |
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| _version_ | 1869523637005975552 |
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| author | Zhang, Huaiqing Suárez-Minguez, Juan Chen, Qi Wang, Yunsheng Tharib, Safa Sun, Hua Jing, Weipeng Huang, Huaguo Yun, Ting Wang, Meili |
| author_browse | Chen, Qi Huang, Huaguo Jing, Weipeng Sun, Hua Suárez-Minguez, Juan Tharib, Safa Wang, Meili Wang, Yunsheng Yun, Ting Zhang, Huaiqing |
| author_facet | Zhang, Huaiqing Suárez-Minguez, Juan Chen, Qi Wang, Yunsheng Tharib, Safa Sun, Hua Jing, Weipeng Huang, Huaguo Yun, Ting Wang, Meili |
| author_sort | Zhang, Huaiqing |
| collection | Directory of Open Access Books |
| description | The aim of this reprint is to provide a comprehensive exploration of the latest advancements in forestry through the integration of emerging technologies. This publication delves into several key areas, including the application of remote sensing and visualization techniques, the use of digital twins and the metaverse, and the role of artificial intelligence in enhancing forest management. Each of these aspects plays a crucial role in shaping the future of smart forestry. First, remote sensing technologies have revolutionized our ability to create high-precision 3D models of forest ecosystems. These detailed models of terrain, trees, and entire environments provide unprecedented insights into forest structure and dynamics, which are essential for effective monitoring and management. Second, by leveraging the power of digital twin technology and the metaverse, this reprint explores how virtual and real-world environments can be seamlessly integrated. Third, artificial intelligence (AI) algorithms play a pivotal role in enhancing the efficiency and accessibility of forestry processes. AI-driven analytics can process vast amounts of data quickly, providing actionable insights that support decision-making in forest management. This reprint shows how AI is transforming forestry by improving the speed and accuracy of data analysis. |
| format | Online |
| id | doab-20.500.12854ir-170593 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2026 |
| publishDateRange | 2026 |
| publishDateSort | 2026 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1705932026-01-02T16:14:21Z Remote Sensing and Visualization Methods Zhang, Huaiqing Suárez-Minguez, Juan Chen, Qi Wang, Yunsheng Tharib, Safa Sun, Hua Jing, Weipeng Huang, Huaguo Yun, Ting Wang, Meili Forest Monitoring Visualization Remote Sensing The aim of this reprint is to provide a comprehensive exploration of the latest advancements in forestry through the integration of emerging technologies. This publication delves into several key areas, including the application of remote sensing and visualization techniques, the use of digital twins and the metaverse, and the role of artificial intelligence in enhancing forest management. Each of these aspects plays a crucial role in shaping the future of smart forestry. First, remote sensing technologies have revolutionized our ability to create high-precision 3D models of forest ecosystems. These detailed models of terrain, trees, and entire environments provide unprecedented insights into forest structure and dynamics, which are essential for effective monitoring and management. Second, by leveraging the power of digital twin technology and the metaverse, this reprint explores how virtual and real-world environments can be seamlessly integrated. Third, artificial intelligence (AI) algorithms play a pivotal role in enhancing the efficiency and accessibility of forestry processes. AI-driven analytics can process vast amounts of data quickly, providing actionable insights that support decision-making in forest management. This reprint shows how AI is transforming forestry by improving the speed and accuracy of data analysis. 2026-01-02T16:14:17Z 2026-01-02T16:14:17Z 2025 book 978-3-7258-4721-1 https://directory.doabooks.org/handle/20.500.12854/170593 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books https://mdpi.com/books/pdfview/topic/11319 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-4722-8 10.3390/books978-3-7258-4722-8 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 978-3-7258-4721-1 300 CH open access |
| spellingShingle | Forest Monitoring Visualization Remote Sensing Zhang, Huaiqing Suárez-Minguez, Juan Chen, Qi Wang, Yunsheng Tharib, Safa Sun, Hua Jing, Weipeng Huang, Huaguo Yun, Ting Wang, Meili Remote Sensing and Visualization Methods |
| title | Remote Sensing and Visualization Methods |
| title_full | Remote Sensing and Visualization Methods |
| title_fullStr | Remote Sensing and Visualization Methods |
| title_full_unstemmed | Remote Sensing and Visualization Methods |
| title_short | Remote Sensing and Visualization Methods |
| title_sort | remote sensing and visualization methods |
| topic | Forest Monitoring Visualization Remote Sensing |
| topic_facet | Forest Monitoring Visualization Remote Sensing |
| url | https://directory.doabooks.org/handle/20.500.12854/170593 |
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