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Towards Tree-level Evapotranspiration Estimation With Small Uavs in Precision Agriculture - Couverture rigide
Synopsis
Chapter 1: Introduction
Chapter 2: ET Estimation Methods with UAVs: A Comprehensive Review
Chapter 3: Existing ET Estimation Methods with UAVs: Results and DiscussionsChapter 4: Estimating Actual Crop Evapotranspiration Using Deep Stochastic Configuration Networks Model and UAV-based Crop Coefficients in A Pomegranate Orchard
Chapter 5: Reliable Tree-level Evapotranspiration Estimation of Pomegranate Trees Using Lysimeter and UAV Multispectral ImageryChapter 6: Tree-level Water Status Inference Using UAV Thermal Imagery and Machine Learning
Chapter 7: Conclusion and Future ResearchLes informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l'auteur
YangQuan Chen received his PhD degree in advanced control and instrumentation from the Nanyang Technological University in Singapore. Currently, he is a full professor at the University of California Merced. His Mechatronics, Embedded Systems and Automation (MESA) Lab at UC Merced is emerging as a widely known "drone lab" with the vision to build an "agriculture drone valley" in California's Central Valley. The lab's work on low-cost, reliably airworthy, multispectral UAV-based remote sensing systems helps create a new type of information services valuable not only for farming and growing, but also for environmental monitoring and assessment. Prof Chen has published over 300 peer-reviewed paper and more than 20 books/book chapters.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Towards Tree-Level Evapotranspiration Estimation With Small Uavs in Precision Agriculture [Hardcover] [Oct 28, 2022] Niu, Haoyu and Chen, Yangquan
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Towards Tree-level Evapotranspiration Estimation with Small UAVs in Precision Agriculture (eng)
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Towards Tree-level Evapotranspiration Estimation with Small UAVs in Precision Agriculture
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ISBN 13 : 9783031149368
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Estimating evapotranspiration (ET) has been one of the most critical research areas in agriculture because of water scarcity, the growing population, and climate change. The accurate estimation and mapping of ET are necessary for crop water management. Traditionally, researchers use water balance, soil moisture, weighing lysimeters, or an energy balance approach, such as Bowen ratio or eddy covariance towers to estimate ET. However, these ET methods are point-specific or area-weighted measurements and cannot be extended to a large scale. On the other hand, while remote sensing is able to provide spatially distributed measurements, the spatial resolution of multispectral satellite images is often not enough for crops with clumped canopy structures, such as trees and vines. Unmanned aerial vehicles (UAVs) can mitigate these spatial and temporal limitations. Lightweight cameras and sensors can be mounted on the UAVs and take high-resolution images. Unlike satellite imagery, the spatial resolution of the UAV images can be at the centimeter-level. UAVs can also fly on-demand, which provides high temporal imagery.This book examines the different UAV-based approaches of ET estimation. Models and algorithms, such as mapping evapotranspiration at high resolution with internalized calibration (METRIC), the two-source energy balance (TSEB) model, and machine learning (ML) are discussed. It also covers the challenges and opportunities for UAVs in ET estimation, with the final chapters devoted to new ET estimation methods and their potential applications for future research. 180 pp. Englisch. N° de réf. du vendeur 9783031149368
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Evapotranspiration Estimation with Small UAVs in Precision Agriculture
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Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. A review of the ET estimation with small UAVNew field methods for ET estimationApplication of uncooled thermal cameraYangQuan Chen received his PhD degree in advanced control and instrumentation from the Nanyang Techno. N° de réf. du vendeur 668447935
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Towards Tree-level Evapotranspiration Estimation with Small UAVs in Precision Agriculture
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ISBN 10 : 303114936X
ISBN 13 : 9783031149368
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Etat : Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Estimating evapotranspiration (ET) has been one of the most critical research areas in agriculture because of water scarcity, the growing population, and climate change. The accurate estimation and mapping of ET are necessary for crop water management. Traditionally, researchers use water balance, soil moisture, weighing lysimeters, or an energy balance approach, such as Bowen ratio or eddy covariance towers to estimate ET. However, these ET methods are point-specific or area-weighted measurements and cannot be extended to a large scale. On the other hand, while remote sensing is able to provide spatially distributed measurements, the spatial resolution of multispectral satellite images is often not enough for crops with clumped canopy structures, such as trees and vines. Unmanned aerial vehicles (UAVs) can mitigate these spatial and temporal limitations. Lightweight cameras and sensors can be mounted on the UAVs and take high-resolution images. Unlike satellite imagery, the spatial resolution of the UAV images can be at the centimeter-level. UAVs can also fly on-demand, which provides high temporal imagery. This book examines the different UAV-based approaches of ET estimation. Models and algorithms, such as mapping evapotranspiration at high resolution with internalized calibration (METRIC), the two-source energy balance (TSEB) model, and machine learning (ML) are discussed. It also covers the challenges and opportunities for UAVs in ET estimation, with the final chapters devoted to new ET estimation methods and their potential applications for future research. N° de réf. du vendeur 40749645/1
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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Estimating evapotranspiration (ET) has been one of the most critical research areas in agriculture because of water scarcity, the growing population, and climate change. The accurate estimation and mapping of ET are necessary for crop water management. Traditionally, researchers use water balance, soil moisture, weighing lysimeters, or an energy balance approach, such as Bowen ratio or eddy covariance towers to estimate ET. However, these ET methods are point-specific or area-weighted measurements and cannot be extended to a large scale. On the other hand, while remote sensing is able to provide spatially distributed measurements, the spatial resolution of multispectral satellite images is often not enough for crops with clumped canopy structures, such as trees and vines. Unmanned aerial vehicles (UAVs) can mitigate these spatial and temporal limitations. Lightweight cameras and sensors can be mounted on the UAVs and take high-resolution images. Unlike satellite imagery, the spatial resolution of the UAV images can be at the centimeter-level. UAVs can also fly on-demand, which provides high temporal imagery.This book examines the different UAV-based approaches of ET estimation. Models and algorithms, such as mapping evapotranspiration at high resolution with internalized calibration (METRIC), the two-source energy balance (TSEB) model, and machine learning (ML) are discussed. It also covers the challenges and opportunities for UAVs in ET estimation, with the final chapters devoted to new ET estimation methods and their potential applications for future research. N° de réf. du vendeur 9783031149368
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