Precision Agriculture and Crop Monitoring Based on Remote Sensing Methods
This Special Issue, entitled “Precision Agriculture and Crop Monitoring Based on Remote Sensing Methods”, brings together twelve peer-reviewed papers that advance remote sensing for crop management. The contributions span satellite and UAV platforms, multispectral and hyperspectral spectroscopy, rad...
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| Формат: | Online |
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| Мова: | Англійська |
| Опубліковано: |
MDPI - Multidisciplinary Digital Publishing Institute
2026
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| Предмети: | |
| Онлайн доступ: | ONIX_20260416T142754_9783725866106_10 |
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| _version_ | 1869524696206147584 |
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| collection | Directory of Open Access Books |
| description | This Special Issue, entitled “Precision Agriculture and Crop Monitoring Based on Remote Sensing Methods”, brings together twelve peer-reviewed papers that advance remote sensing for crop management. The contributions span satellite and UAV platforms, multispectral and hyperspectral spectroscopy, radar, and LiDAR, with workflows that combine physics-based modelling, machine learning, and deep learning. Across cotton, wheat, rice, maize, soybean, and vineyards, the studies demonstrate the robust retrieval of canopy structure, leaf area, biomass, nitrogen uptake, water status, and grain quality, alongside field and crop mapping and early stress and disease characterisation. Methodological innovations include optimised UAV LiDAR acquisition and processing, time series feature selection and matching for crop mapping, uncertainty quantification for biophysical retrieval, and plant-level detection and panoptic recognition in RGB imagery and 3D point clouds. Together, this Reprint illustrates how scalable sensing and analytics support timely, data-driven decisions for more efficient and sustainable agriculture. |
| format | Online |
| id | doab-20.500.12854ir-175355 |
| 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-1753552026-04-16T20:25:59Z Precision Agriculture and Crop Monitoring Based on Remote Sensing Methods Falcioni, Renan Furlanetto, Renato Herrig Crusiol, Luis Agricultural remote sensing Crop mapping Crop phenotyping Deep learning Hyperspectral imaging LiDAR Machine learning Precision agriculture UAV remote sensing thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general This Special Issue, entitled “Precision Agriculture and Crop Monitoring Based on Remote Sensing Methods”, brings together twelve peer-reviewed papers that advance remote sensing for crop management. The contributions span satellite and UAV platforms, multispectral and hyperspectral spectroscopy, radar, and LiDAR, with workflows that combine physics-based modelling, machine learning, and deep learning. Across cotton, wheat, rice, maize, soybean, and vineyards, the studies demonstrate the robust retrieval of canopy structure, leaf area, biomass, nitrogen uptake, water status, and grain quality, alongside field and crop mapping and early stress and disease characterisation. Methodological innovations include optimised UAV LiDAR acquisition and processing, time series feature selection and matching for crop mapping, uncertainty quantification for biophysical retrieval, and plant-level detection and panoptic recognition in RGB imagery and 3D point clouds. Together, this Reprint illustrates how scalable sensing and analytics support timely, data-driven decisions for more efficient and sustainable agriculture. 2026-04-16T20:25:45Z 2026-04-16T20:25:45Z 2026 book ONIX_20260416T142754_9783725866106_10 9783725866106 9783725866113 https://directory.doabooks.org/handle/20.500.12854/175355 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/ https://mdpi.com/books/pdfview/book/12270 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-6611-3 10.3390/books978-3-7258-6611-3 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725866106 9783725866113 304 CH open access |
| spellingShingle | Agricultural remote sensing Crop mapping Crop phenotyping Deep learning Hyperspectral imaging LiDAR Machine learning Precision agriculture UAV remote sensing thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general Precision Agriculture and Crop Monitoring Based on Remote Sensing Methods |
| title | Precision Agriculture and Crop Monitoring Based on Remote Sensing Methods |
| title_full | Precision Agriculture and Crop Monitoring Based on Remote Sensing Methods |
| title_fullStr | Precision Agriculture and Crop Monitoring Based on Remote Sensing Methods |
| title_full_unstemmed | Precision Agriculture and Crop Monitoring Based on Remote Sensing Methods |
| title_short | Precision Agriculture and Crop Monitoring Based on Remote Sensing Methods |
| title_sort | precision agriculture and crop monitoring based on remote sensing methods |
| topic | Agricultural remote sensing Crop mapping Crop phenotyping Deep learning Hyperspectral imaging LiDAR Machine learning Precision agriculture UAV remote sensing thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general |
| topic_facet | Agricultural remote sensing Crop mapping Crop phenotyping Deep learning Hyperspectral imaging LiDAR Machine learning Precision agriculture UAV remote sensing thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general |
| url | ONIX_20260416T142754_9783725866106_10 |