國立虎尾科技大學 |

Towards Tree-level Evapotranspiration Estimation with Small UAVs in Precision Agriculture

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Towards Tree-level Evapotranspiration Estimation with Small UAVs in Precision Agriculture/ by Haoyu Niu, YangQuan Chen.
作者:	Niu, Haoyu.
其他作者:	Chen, YangQuan.
面頁冊數:	XXIV, 156 p. 60 illus., 56 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Soil and Water Protection. -
電子資源:	https://doi.org/10.1007/978-3-031-14937-5
ISBN:	9783031149375

Towards Tree-level Evapotranspiration Estimation with Small UAVs in Precision Agriculture
Niu, Haoyu.

Towards Tree-level Evapotranspiration Estimation with Small UAVs in Precision Agriculture[electronic resource] /by Haoyu Niu, YangQuan Chen. - 1st ed. 2022. - XXIV, 156 p. 60 illus., 56 illus. in color.online resource.

Chapter 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.

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.

ISBN: 9783031149375

Standard No.: 10.1007/978-3-031-14937-5doiSubjects--Topical Terms:

1389198
Soil and Water Protection.

LC Class. No.: S1-972

Dewey Class. No.: 630

Towards Tree-level Evapotranspiration Estimation with Small UAVs in Precision Agriculture
LDR:03604nam a22003975i 4500 001 1084789
003 DE-He213
005 20221027102354.0
007 cr nn 008mamaa
008 221228s2022 sz | s |||| 0|eng d
020 $a 9783031149375 $9 978-3-031-14937-5
024 7 $a 10.1007/978-3-031-14937-5 $2 doi
035 $a 978-3-031-14937-5
050 4 $a S1-972
072 7 $a TVB $2 bicssc
072 7 $a TEC003000 $2 bisacsh
072 7 $a TVB $2 thema
082 0 4 $a 630 $2 23
100 1 $a Niu, Haoyu. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1391171
245 1 0 $a Towards Tree-level Evapotranspiration Estimation with Small UAVs in Precision Agriculture $h [electronic resource] / $c by Haoyu Niu, YangQuan Chen.
250 $a 1st ed. 2022.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2022.
300 $a XXIV, 156 p. 60 illus., 56 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
505 0 $a Chapter 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.
520 $a 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.
650 2 4 $a Soil and Water Protection. $3 1389198
650 2 4 $a Plant Science. $3 1366032
650 2 4 $a Engineering Mechanics. $3 1366277
650 0 $a Civil engineering. $3 561339
650 0 $a Environmental protection. $3 556606
650 0 $a Botany. $3 599558
650 0 $a Mechanics, Applied. $3 596630
650 0 $a Agriculture. $3 660421
700 1 $a Chen, YangQuan. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 888187
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783031149368
776 0 8 $i Printed edition: $z 9783031149382
776 0 8 $i Printed edition: $z 9783031149399
856 4 0 $u https://doi.org/10.1007/978-3-031-14937-5
912 $a ZDB-2-SBL
912 $a ZDB-2-SXB
950 $a Biomedical and Life Sciences (SpringerNature-11642)
950 $a Biomedical and Life Sciences (R0) (SpringerNature-43708)