Crops and Vegetation Monitoring with Remote/Proximal Sensing
Remote sensing is a powerful technique for characterizing and monitoring crop or vegetation properties at reasonable temporal and spatial resolutions. Remote sensing uses airborne and spaceborne platforms to collect various imageries and is widely applied for the vegetation monitoring of local- or l...
Wedi'i Gadw mewn:
| Fformat: | Online |
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| Iaith: | Saesneg |
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MDPI - Multidisciplinary Digital Publishing Institute
2023
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| Pynciau: | |
| Mynediad Ar-lein: | ONIX_20231130_9783036594460_295 |
| Tagiau: |
Dim Tagiau, Byddwch y cyntaf i dagio'r cofnod hwn!
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| _version_ | 1869522388931051520 |
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| collection | Directory of Open Access Books |
| description | Remote sensing is a powerful technique for characterizing and monitoring crop or vegetation properties at reasonable temporal and spatial resolutions. Remote sensing uses airborne and spaceborne platforms to collect various imageries and is widely applied for the vegetation monitoring of local- or large-scale interest concerning the effect of geophysical and climate parameters. The Special Issue highlights vegetation monitoring using remote sensing data acquired from satellite or unmanned aerial vehicle platforms. In addition to the optical data, thermal data is utilized to estimate crop yield or production, orchard water status, chlorophyll content, forest diversity mapping, or vegetation phenology. |
| format | Online |
| id | doab-20.500.12854ir-128843 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1288432024-03-28T03:31:35Z Crops and Vegetation Monitoring with Remote/Proximal Sensing Omasa, Kenji Lu, Shan Wang, Jie rice and wheat nitrogen remote sensing quantitative retrieval research prospect vegetation phenology snow cover vegetation index SOS Tibetan Plateau remote sensing forest diversity GEDI LiDAR Sentinel-2 machine Learning yield forecasting logistic model normalization method crop canopy temperature maize broadband vegetation indices chlorophyll content leaf angle distribution WorldView-2 RapidEye GaoFen-6 random forest land evaluation soil biomass Hungary gross primary productivity soil health soil quality coastal marsh continuum removal hyperspectral spectral signatures unmanned aerial vehicle (UAV) vegetation species discrimination second derivative transformation canopy temperature crop water status index accuracy assessment peach orchard stem water potential backscatter gradient boosting machine learning NDVI precision agriculture forest stock volume NDVIRE Helan mountains convolutional neural networks (CNNs) unmanned aerial vehicles (UAVs) semi-natural grasslands plant communities time series reconstruction algorithm smoothing optical remote sensing cropping intensity temporal mixture analysis endmember unmixing time series images thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography Remote sensing is a powerful technique for characterizing and monitoring crop or vegetation properties at reasonable temporal and spatial resolutions. Remote sensing uses airborne and spaceborne platforms to collect various imageries and is widely applied for the vegetation monitoring of local- or large-scale interest concerning the effect of geophysical and climate parameters. The Special Issue highlights vegetation monitoring using remote sensing data acquired from satellite or unmanned aerial vehicle platforms. In addition to the optical data, thermal data is utilized to estimate crop yield or production, orchard water status, chlorophyll content, forest diversity mapping, or vegetation phenology. 2023-11-30T20:57:43Z 2023-11-30T20:57:43Z 2023 book ONIX_20231130_9783036594460_295 9783036594460 9783036594477 https://directory.doabooks.org/handle/20.500.12854/128843 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/8313 https://mdpi.com/books/pdfview/book/8313 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-9447-7 10.3390/books978-3-0365-9447-7 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036594460 9783036594477 290 Basel open access |
| spellingShingle | rice and wheat nitrogen remote sensing quantitative retrieval research prospect vegetation phenology snow cover vegetation index SOS Tibetan Plateau remote sensing forest diversity GEDI LiDAR Sentinel-2 machine Learning yield forecasting logistic model normalization method crop canopy temperature maize broadband vegetation indices chlorophyll content leaf angle distribution WorldView-2 RapidEye GaoFen-6 random forest land evaluation soil biomass Hungary gross primary productivity soil health soil quality coastal marsh continuum removal hyperspectral spectral signatures unmanned aerial vehicle (UAV) vegetation species discrimination second derivative transformation canopy temperature crop water status index accuracy assessment peach orchard stem water potential backscatter gradient boosting machine learning NDVI precision agriculture forest stock volume NDVIRE Helan mountains convolutional neural networks (CNNs) unmanned aerial vehicles (UAVs) semi-natural grasslands plant communities time series reconstruction algorithm smoothing optical remote sensing cropping intensity temporal mixture analysis endmember unmixing time series images thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography Crops and Vegetation Monitoring with Remote/Proximal Sensing |
| title | Crops and Vegetation Monitoring with Remote/Proximal Sensing |
| title_full | Crops and Vegetation Monitoring with Remote/Proximal Sensing |
| title_fullStr | Crops and Vegetation Monitoring with Remote/Proximal Sensing |
| title_full_unstemmed | Crops and Vegetation Monitoring with Remote/Proximal Sensing |
| title_short | Crops and Vegetation Monitoring with Remote/Proximal Sensing |
| title_sort | crops and vegetation monitoring with remote proximal sensing |
| topic | rice and wheat nitrogen remote sensing quantitative retrieval research prospect vegetation phenology snow cover vegetation index SOS Tibetan Plateau remote sensing forest diversity GEDI LiDAR Sentinel-2 machine Learning yield forecasting logistic model normalization method crop canopy temperature maize broadband vegetation indices chlorophyll content leaf angle distribution WorldView-2 RapidEye GaoFen-6 random forest land evaluation soil biomass Hungary gross primary productivity soil health soil quality coastal marsh continuum removal hyperspectral spectral signatures unmanned aerial vehicle (UAV) vegetation species discrimination second derivative transformation canopy temperature crop water status index accuracy assessment peach orchard stem water potential backscatter gradient boosting machine learning NDVI precision agriculture forest stock volume NDVIRE Helan mountains convolutional neural networks (CNNs) unmanned aerial vehicles (UAVs) semi-natural grasslands plant communities time series reconstruction algorithm smoothing optical remote sensing cropping intensity temporal mixture analysis endmember unmixing time series images thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography |
| topic_facet | rice and wheat nitrogen remote sensing quantitative retrieval research prospect vegetation phenology snow cover vegetation index SOS Tibetan Plateau remote sensing forest diversity GEDI LiDAR Sentinel-2 machine Learning yield forecasting logistic model normalization method crop canopy temperature maize broadband vegetation indices chlorophyll content leaf angle distribution WorldView-2 RapidEye GaoFen-6 random forest land evaluation soil biomass Hungary gross primary productivity soil health soil quality coastal marsh continuum removal hyperspectral spectral signatures unmanned aerial vehicle (UAV) vegetation species discrimination second derivative transformation canopy temperature crop water status index accuracy assessment peach orchard stem water potential backscatter gradient boosting machine learning NDVI precision agriculture forest stock volume NDVIRE Helan mountains convolutional neural networks (CNNs) unmanned aerial vehicles (UAVs) semi-natural grasslands plant communities time series reconstruction algorithm smoothing optical remote sensing cropping intensity temporal mixture analysis endmember unmixing time series images thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography |
| url | ONIX_20231130_9783036594460_295 |