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Applications of Machine Learning and Remote Sensing in Crop and Vegetation Monitoring - Couverture rigide
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Applications of Machine Learning and Remote Sensing in Crop and Vegetation Monitoring
Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
HRD. Etat : New. New Book. Shipped from UK. Established seller since 2000. N° de réf. du vendeur L2-9783725882694
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EUR 83,33
Expédition à EUR 6,89
Expédition depuis Royaume-Uni vers Etats-Unis
Expédition depuis Royaume-Uni vers Etats-Unis
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Applications of Machine Learning and Remote Sensing in Crop and Vegetation Monitoring
Vendeur : PBShop.store US, Wood Dale, IL, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
HRD. Etat : New. New Book. Shipped from UK. Established seller since 2000. N° de réf. du vendeur L2-9783725882694
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EUR 91,77
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Expédition nationale : Etats-Unis
Expédition nationale : Etats-Unis
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Applications of Machine Learning and Remote Sensing in Crop and Vegetation Monitoring (Hardcover)
impression à la demandeVendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Hardcover. Etat : new. Hardcover. This Reprint presents a collection of cutting-edge research on the integration of machine learning and remote sensing technologies for precision agriculture. Vegetation plays a critical role in the Earth's system, influencing global change, climate, hydrological cycles, and biochemical processes. The combination of high-resolution remote sensing data with advanced machine learning algorithms offers new solutions for monitoring vegetation status. The articles within this Reprint explore a wide range of applications, including the estimation of crop biophysical parameters such as leaf area index and chlorophyll content, the prediction of yield, the detection of diseases and pests in fruits and vegetables, and the monitoring of agricultural droughts. The research covers diverse techniques, from using object detection models for fruit quality assessment to synergizing multispectral and radar data, and from applying discrete wavelet transforms to RGB images for chlorophyll estimation to reconstructing solar-induced chlorophyll fluorescence for drought monitoring. Collectively, this Reprint demonstrates how intelligent data analysis can enhance crop monitoring, support sustainable vegetation restoration strategies, and improve water resource management. It serves as a valuable resource for researchers, agronomists, and practitioners seeking to apply state-of-the-art computational methods to tackle current challenges in agriculture and vegetation science. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9783725882694
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EUR 93,40
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Expédition nationale : Etats-Unis
Expédition nationale : Etats-Unis
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Applications of Machine Learning and Remote Sensing in Crop and Vegetation Monitoring
Vendeur : California Books, Miami, FL, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. N° de réf. du vendeur I-9783725882694
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EUR 97,98
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Expédition nationale : Etats-Unis
Expédition nationale : Etats-Unis
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Applications of Machine Learning and Remote Sensing in Crop and Vegetation Monitoring (Hardcover)
impression à la demandeVendeur : CitiRetail, Stevenage, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Hardcover. Etat : new. Hardcover. This Reprint presents a collection of cutting-edge research on the integration of machine learning and remote sensing technologies for precision agriculture. Vegetation plays a critical role in the Earth's system, influencing global change, climate, hydrological cycles, and biochemical processes. The combination of high-resolution remote sensing data with advanced machine learning algorithms offers new solutions for monitoring vegetation status. The articles within this Reprint explore a wide range of applications, including the estimation of crop biophysical parameters such as leaf area index and chlorophyll content, the prediction of yield, the detection of diseases and pests in fruits and vegetables, and the monitoring of agricultural droughts. The research covers diverse techniques, from using object detection models for fruit quality assessment to synergizing multispectral and radar data, and from applying discrete wavelet transforms to RGB images for chlorophyll estimation to reconstructing solar-induced chlorophyll fluorescence for drought monitoring. Collectively, this Reprint demonstrates how intelligent data analysis can enhance crop monitoring, support sustainable vegetation restoration strategies, and improve water resource management. It serves as a valuable resource for researchers, agronomists, and practitioners seeking to apply state-of-the-art computational methods to tackle current challenges in agriculture and vegetation science. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9783725882694
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EUR 94,25
Expédition à EUR 43,41
Expédition depuis Royaume-Uni vers Etats-Unis
Expédition depuis Royaume-Uni vers Etats-Unis
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Applications of Machine Learning and Remote Sensing in Crop and Vegetation Monitoring (Hardcover)
impression à la demandeVendeur : AussieBookSeller, Truganina, VIC, Australie
Évaluation du vendeur 5 sur 5 étoiles
Hardcover. Etat : new. Hardcover. This Reprint presents a collection of cutting-edge research on the integration of machine learning and remote sensing technologies for precision agriculture. Vegetation plays a critical role in the Earth's system, influencing global change, climate, hydrological cycles, and biochemical processes. The combination of high-resolution remote sensing data with advanced machine learning algorithms offers new solutions for monitoring vegetation status. The articles within this Reprint explore a wide range of applications, including the estimation of crop biophysical parameters such as leaf area index and chlorophyll content, the prediction of yield, the detection of diseases and pests in fruits and vegetables, and the monitoring of agricultural droughts. The research covers diverse techniques, from using object detection models for fruit quality assessment to synergizing multispectral and radar data, and from applying discrete wavelet transforms to RGB images for chlorophyll estimation to reconstructing solar-induced chlorophyll fluorescence for drought monitoring. Collectively, this Reprint demonstrates how intelligent data analysis can enhance crop monitoring, support sustainable vegetation restoration strategies, and improve water resource management. It serves as a valuable resource for researchers, agronomists, and practitioners seeking to apply state-of-the-art computational methods to tackle current challenges in agriculture and vegetation science. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N° de réf. du vendeur 9783725882694
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EUR 112,91
Expédition à EUR 32,89
Expédition depuis Australie vers Etats-Unis
Expédition depuis Australie vers Etats-Unis
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Applications of Machine Learning and Remote Sensing in Crop and Vegetation Monitoring
impression à la demandeVendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This Reprint presents a collection of cutting-edge research on the integration of machine learning and remote sensing technologies for precision agriculture. Vegetation plays a critical role in the Earth's system, influencing global change, climate, hydrological cycles, and biochemical processes. The combination of high-resolution remote sensing data with advanced machine learning algorithms offers new solutions for monitoring vegetation status. The articles within this Reprint explore a wide range of applications, including the estimation of crop biophysical parameters such as leaf area index and chlorophyll content, the prediction of yield, the detection of diseases and pests in fruits and vegetables, and the monitoring of agricultural droughts. The research covers diverse techniques, from using object detection models for fruit quality assessment to synergizing multispectral and radar data, and from applying discrete wavelet transforms to RGB images for chlorophyll estimation to reconstructing solar-induced chlorophyll fluorescence for drought monitoring. Collectively, this Reprint demonstrates how intelligent data analysis can enhance crop monitoring, support sustainable vegetation restoration strategies, and improve water resource management. It serves as a valuable resource for researchers, agronomists, and practitioners seeking to apply state-of-the-art computational methods to tackle current challenges in agriculture and vegetation science. N° de réf. du vendeur 9783725882694
Acheter neuf
EUR 114,96
Expédition à EUR 35
Expédition depuis Allemagne vers Etats-Unis
Expédition depuis Allemagne vers Etats-Unis
Quantité disponible : 2 disponible(s)