001450843 000__ 04164cam\a2200517\i\4500
001450843 001__ 1450843
001450843 003__ OCoLC
001450843 005__ 20230310004546.0
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001450843 008__ 221101s2022\\\\sz\a\\\\ob\\\\001\0\eng\d
001450843 019__ $$a1349309944
001450843 020__ $$a9783031149375$$q(electronic bk.)
001450843 020__ $$a3031149378$$q(electronic bk.)
001450843 020__ $$z9783031149368
001450843 020__ $$z303114936X
001450843 0247_ $$a10.1007/978-3-031-14937-5$$2doi
001450843 035__ $$aSP(OCoLC)1349495078
001450843 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dYDX$$dEBLCP$$dOCLCF$$dUKAHL$$dOCLCQ
001450843 049__ $$aISEA
001450843 050_4 $$aS600.7.E93
001450843 08204 $$a631.587$$223/eng/20221101
001450843 1001_ $$aNiu, Haoyu,$$eauthor.
001450843 24510 $$aTowards tree-level evapotranspiration estimation with small UAVs in precision agriculture /$$cHaoyu Niu, YangQuan Chen.
001450843 264_1 $$aCham, Switzerland :$$bSpringer,$$c2022.
001450843 300__ $$a1 online resource (xxiv, 156 pages) :$$billustrations (some color)
001450843 336__ $$atext$$btxt$$2rdacontent
001450843 337__ $$acomputer$$bc$$2rdamedia
001450843 338__ $$aonline resource$$bcr$$2rdacarrier
001450843 504__ $$aIncludes bibliographical references and index.
001450843 5050_ $$aChapter 1: Introduction -- Chapter 2: ET Estimation Methods with UAVs: A Comprehensive Review -- Chapter 3: Existing ET Estimation Methods with UAVs: Results and Discussions -- Chapter 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 Imagery -- Chapter 6: Tree-level Water Status Inference Using UAV Thermal Imagery and Machine Learning -- Chapter 7: Conclusion and Future Research.
001450843 506__ $$aAccess limited to authorized users.
001450843 520__ $$aEstimating 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.
001450843 588__ $$aDescription based on print version record.
001450843 650_0 $$aEvapotranspiration$$xMeasurement.
001450843 650_0 $$aPrecision farming.
001450843 650_0 $$aDrone aircraft in remote sensing.
001450843 655_0 $$aElectronic books.
001450843 7001_ $$aChen, YangQuan,$$d1966-$$eauthor.$$1https://orcid.org/0000-0002-7422-5988
001450843 77608 $$iPrint version:$$aNiu, Haoyu, author.$$tTowards tree-level evapotranspiration estimation with small UAVs in precision agriculture$$z9783031149368$$w(OCoLC)1346321267
001450843 852__ $$bebk
001450843 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-14937-5$$zOnline Access$$91397441.1
001450843 909CO $$ooai:library.usi.edu:1450843$$pGLOBAL_SET
001450843 980__ $$aBIB
001450843 980__ $$aEBOOK
001450843 982__ $$aEbook
001450843 983__ $$aOnline
001450843 994__ $$a92$$bISE