BESS-STAIR: a framework to estimate daily, 30 m, and all-weather crop evapotranspiration using multi-source satellite data for the US Corn Belt

With increasing crop water demands and drought threats, mapping and monitoring of cropland evapotranspiration (ET) at high spatial and temporal resolutions become increasingly critical for water management and sustainability. However, estimating ET from satellites for precise water resource manageme...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Hydrology and earth system sciences Ročník 24; číslo 3; s. 1251 - 1273
Hlavní autoři: Jiang, Chongya, Guan, Kaiyu, Pan, Ming, Ryu, Youngryel, Peng, Bin, Wang, Sibo
Médium: Journal Article
Jazyk:angličtina
Vydáno: Katlenburg-Lindau Copernicus GmbH 20.03.2020
Copernicus Publications
Témata:
Agricultural land
Agricultural management
Agriculture
Albedo
Albedo (solar)
Algorithms
Analysis
Belts
Carbon
Carbon dioxide
Computer simulation
Corn
Corn belt
Crop evapotranspiration
Crop water
Daily
Data
Data integration
Decision making
Drought
Droughts
Energy
Evapotranspiration
Evapotranspiration estimates
Evapotranspiration models
Frameworks
Generic drugs
Humidity
Hydrologic cycle
Landsat
Landsat satellites
Leaf area
Leaf area index
Mapping
Precision agriculture
Reflectance
Remote sensing
Resolution
Resource management
Root-mean-square errors
Satellite data
Satellites
Seasonal variation
Simulators
Sustainability
Sustainable development
Time
Tower measurements
Vegetation
Water management
Water resource management
Water resources
Water resources management
Water shortages
Weather
United States > US
ISSN:1607-7938, 1027-5606, 1607-7938
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Abstract With increasing crop water demands and drought threats, mapping and monitoring of cropland evapotranspiration (ET) at high spatial and temporal resolutions become increasingly critical for water management and sustainability. However, estimating ET from satellites for precise water resource management is still challenging due to the limitations in both existing ET models and satellite input data. Specifically, the process of ET is complex and difficult to model, and existing satellite remote-sensing data could not fulfill high resolutions in both space and time. To address the above two issues, this study presents a new high spatiotemporal resolution ET mapping framework, i.e., BESS-STAIR, which integrates a satellite-driven water–carbon–energy coupled biophysical model, BESS (Breathing Earth System Simulator), with a generic and fully automated fusion algorithm, STAIR (SaTallite dAta IntegRation). In this framework, STAIR provides daily 30 m multispectral surface reflectance by fusing Landsat and MODIS satellite data to derive a fine-resolution leaf area index and visible/near-infrared albedo, all of which, along with coarse-resolution meteorological and CO2 data, are used to drive BESS to estimate gap-free 30 m resolution daily ET. We applied BESS-STAIR from 2000 through 2017 in six areas across the US Corn Belt and validated BESS-STAIR ET estimations using flux-tower measurements over 12 sites (85 site years). Results showed that BESS-STAIR daily ET achieved an overall R2=0.75, with root mean square error RMSE =0.93 mm d−1 and relative error RE =27.9 % when benchmarked with the flux measurements. In addition, BESS-STAIR ET estimations captured the spatial patterns, seasonal cycles, and interannual dynamics well in different sub-regions. The high performance of the BESS-STAIR framework primarily resulted from (1) the implementation of coupled constraints on water, carbon, and energy in BESS, (2) high-quality daily 30 m data from the STAIR fusion algorithm, and (3) BESS's applicability under all-sky conditions. BESS-STAIR is calibration-free and has great potentials to be a reliable tool for water resource management and precision agriculture applications for the US Corn Belt and even worldwide given the global coverage of its input data.
AbstractList With increasing crop water demands and drought threats, mapping and monitoring of cropland evapotranspiration (ET) at high spatial and temporal resolutions become increasingly critical for water management and sustainability. However, estimating ET from satellites for precise water resource management is still challenging due to the limitations in both existing ET models and satellite input data. Specifically, the process of ET is complex and difficult to model, and existing satellite remote-sensing data could not fulfill high resolutions in both space and time. To address the above two issues, this study presents a new high spatiotemporal resolution ET mapping framework, i.e., BESS-STAIR, which integrates a satellite-driven water-carbon-energy coupled biophysical model, BESS (Breathing Earth System Simulator), with a generic and fully automated fusion algorithm, STAIR (SaTallite dAta IntegRation). In this framework, STAIR provides daily 30 m multispectral surface reflectance by fusing Landsat and MODIS satellite data to derive a fine-resolution leaf area index and visible/near-infrared albedo, all of which, along with coarse-resolution meteorological and CO.sub.2 data, are used to drive BESS to estimate gap-free 30 m resolution daily ET. We applied BESS-STAIR from 2000 through 2017 in six areas across the US Corn Belt and validated BESS-STAIR ET estimations using flux-tower measurements over 12 sites (85 site years). Results showed that BESS-STAIR daily ET achieved an overall R.sup.2 =0.75, with root mean square error RMSE =0.93 mm d.sup.-1 and relative error RE =27.9 % when benchmarked with the flux measurements. In addition, BESS-STAIR ET estimations captured the spatial patterns, seasonal cycles, and interannual dynamics well in different sub-regions. The high performance of the BESS-STAIR framework primarily resulted from (1) the implementation of coupled constraints on water, carbon, and energy in BESS, (2) high-quality daily 30 m data from the STAIR fusion algorithm, and (3) BESS's applicability under all-sky conditions. BESS-STAIR is calibration-free and has great potentials to be a reliable tool for water resource management and precision agriculture applications for the US Corn Belt and even worldwide given the global coverage of its input data.
With increasing crop water demands and drought threats, mapping and monitoring of cropland evapotranspiration (ET) at high spatial and temporal resolutions become increasingly critical for water management and sustainability. However, estimating ET from satellites for precise water resource management is still challenging due to the limitations in both existing ET models and satellite input data. Specifically, the process of ET is complex and difficult to model, and existing satellite remote-sensing data could not fulfill high resolutions in both space and time. To address the above two issues, this study presents a new high spatiotemporal resolution ET mapping framework, i.e., BESS-STAIR, which integrates a satellite-driven water–carbon–energy coupled biophysical model, BESS (Breathing Earth System Simulator), with a generic and fully automated fusion algorithm, STAIR (SaTallite dAta IntegRation). In this framework, STAIR provides daily 30 m multispectral surface reflectance by fusing Landsat and MODIS satellite data to derive a fine-resolution leaf area index and visible/near-infrared albedo, all of which, along with coarse-resolution meteorological and CO2 data, are used to drive BESS to estimate gap-free 30 m resolution daily ET. We applied BESS-STAIR from 2000 through 2017 in six areas across the US Corn Belt and validated BESS-STAIR ET estimations using flux-tower measurements over 12 sites (85 site years). Results showed that BESS-STAIR daily ET achieved an overall R2=0.75 , with root mean square error RMSE  =0.93  mm d −1 and relative error RE  =27.9  % when benchmarked with the flux measurements. In addition, BESS-STAIR ET estimations captured the spatial patterns, seasonal cycles, and interannual dynamics well in different sub-regions. The high performance of the BESS-STAIR framework primarily resulted from (1) the implementation of coupled constraints on water, carbon, and energy in BESS, (2) high-quality daily 30 m data from the STAIR fusion algorithm, and (3) BESS's applicability under all-sky conditions. BESS-STAIR is calibration-free and has great potentials to be a reliable tool for water resource management and precision agriculture applications for the US Corn Belt and even worldwide given the global coverage of its input data.
With increasing crop water demands and drought threats, mapping and monitoring of cropland evapotranspiration (ET) at high spatial and temporal resolutions become increasingly critical for water management and sustainability. However, estimating ET from satellites for precise water resource management is still challenging due to the limitations in both existing ET models and satellite input data. Specifically, the process of ET is complex and difficult to model, and existing satellite remote-sensing data could not fulfill high resolutions in both space and time. To address the above two issues, this study presents a new high spatiotemporal resolution ET mapping framework, i.e., BESS-STAIR, which integrates a satellite-driven water–carbon–energy coupled biophysical model, BESS (Breathing Earth System Simulator), with a generic and fully automated fusion algorithm, STAIR (SaTallite dAta IntegRation). In this framework, STAIR provides daily 30 m multispectral surface reflectance by fusing Landsat and MODIS satellite data to derive a fine-resolution leaf area index and visible/near-infrared albedo, all of which, along with coarse-resolution meteorological and CO2 data, are used to drive BESS to estimate gap-free 30 m resolution daily ET. We applied BESS-STAIR from 2000 through 2017 in six areas across the US Corn Belt and validated BESS-STAIR ET estimations using flux-tower measurements over 12 sites (85 site years). Results showed that BESS-STAIR daily ET achieved an overall R2=0.75, with root mean square error RMSE =0.93 mm d−1 and relative error RE =27.9 % when benchmarked with the flux measurements. In addition, BESS-STAIR ET estimations captured the spatial patterns, seasonal cycles, and interannual dynamics well in different sub-regions. The high performance of the BESS-STAIR framework primarily resulted from (1) the implementation of coupled constraints on water, carbon, and energy in BESS, (2) high-quality daily 30 m data from the STAIR fusion algorithm, and (3) BESS's applicability under all-sky conditions. BESS-STAIR is calibration-free and has great potentials to be a reliable tool for water resource management and precision agriculture applications for the US Corn Belt and even worldwide given the global coverage of its input data.
With increasing crop water demands and drought threats, mapping and monitoring of cropland evapotranspiration (ET) at high spatial and temporal resolutions become increasingly critical for water management and sustainability. However, estimating ET from satellites for precise water resource management is still challenging due to the limitations in both existing ET models and satellite input data. Specifically, the process of ET is complex and difficult to model, and existing satellite remote-sensing data could not fulfill high resolutions in both space and time. To address the above two issues, this study presents a new high spatiotemporal resolution ET mapping framework, i.e., BESS-STAIR, which integrates a satellite-driven water–carbon–energy coupled biophysical model, BESS (Breathing Earth System Simulator), with a generic and fully automated fusion algorithm, STAIR (SaTallite dAta IntegRation). In this framework, STAIR provides daily 30 m multispectral surface reflectance by fusing Landsat and MODIS satellite data to derive a fine-resolution leaf area index and visible/near-infrared albedo, all of which, along with coarse-resolution meteorological and CO2 data, are used to drive BESS to estimate gap-free 30 m resolution daily ET. We applied BESS-STAIR from 2000 through 2017 in six areas across the US Corn Belt and validated BESS-STAIR ET estimations using flux-tower measurements over 12 sites (85 site years). Results showed that BESS-STAIR daily ET achieved an overall R2=0.75, with root mean square error RMSE =0.93 mm d-1 and relative error RE =27.9 % when benchmarked with the flux measurements. In addition, BESS-STAIR ET estimations captured the spatial patterns, seasonal cycles, and interannual dynamics well in different sub-regions. The high performance of the BESS-STAIR framework primarily resulted from (1) the implementation of coupled constraints on water, carbon, and energy in BESS, (2) high-quality daily 30 m data from the STAIR fusion algorithm, and (3) BESS's applicability under all-sky conditions. BESS-STAIR is calibration-free and has great potentials to be a reliable tool for water resource management and precision agriculture applications for the US Corn Belt and even worldwide given the global coverage of its input data.
Audience Academic
Author Jiang, Chongya
Peng, Bin
Pan, Ming
Guan, Kaiyu
Wang, Sibo
Ryu, Youngryel
Author_xml – sequence: 1
  givenname: Chongya
  orcidid: 0000-0002-1660-7320
  surname: Jiang
  fullname: Jiang, Chongya
– sequence: 2
  givenname: Kaiyu
  surname: Guan
  fullname: Guan, Kaiyu
– sequence: 3
  givenname: Ming
  surname: Pan
  fullname: Pan, Ming
– sequence: 4
  givenname: Youngryel
  orcidid: 0000-0001-6238-2479
  surname: Ryu
  fullname: Ryu, Youngryel
– sequence: 5
  givenname: Bin
  surname: Peng
  fullname: Peng, Bin
– sequence: 6
  givenname: Sibo
  orcidid: 0000-0002-7601-8886
  surname: Wang
  fullname: Wang, Sibo
BookMark eNp9Ustu1DAUjVCRaAsfwM4SK6Sm-BUnYTcdlTJSJaSmXVu3fkw9JPFgeyjdse2SX-RLcGYQMAghL2xdnXN87r3nqDgY_WiK4iXBpxVp-Zs7E2NJeUloRUqKKX5SHBKB67JuWXPwx_tZcRTjCmPaNIIeFt_Ozruu7K5ni6u3CJANMJh7Hz6i5JGJyQ2QDNLg-ocTxPD3r4_DCYJRI-j78t5AujMBqeDXyHyGtU8Bxrh2AZLzI9pENy7RsOmTK6PfBGVQzHJ977aaKX_nA8oS6KZDcx9GdGb69Lx4aqGP5sXP-7i4eXd-PX9fXn64WMxnl6XihKXSMsqxoloRJbC9ta3SthGaEl5jpivCLcHC2rZuFW9rIRhrcEMYkFbX7FYZdlwsdrraw0quQ241PEgPTm4LPiwlhORUbyTFUIGoqGai5cBxwzUWYBsrhAXD66z1aqe1Dv7TJs9NrnK_Y7YvKZ8c0Zrx36glZFE32mleanBRyZkgDa4butU6_QcqH20Gp_LWrcv1PcLrPULGJPMlLWETo1x0V_tYssPmncUYjP3VOMFyCpKcgpRNyylIcgpS5tR_cZRL2w1nY67_D_MH39vONg
CitedBy_id crossref_primary_10_3390_rs12142337
crossref_primary_10_1016_j_jhydrol_2020_125398
crossref_primary_10_1016_j_rse_2021_112519
crossref_primary_10_1016_j_jhydrol_2024_132201
crossref_primary_10_3389_fclim_2020_583509
crossref_primary_10_1029_2022WR032800
crossref_primary_10_1029_2022WR032967
crossref_primary_10_1016_j_jhydrol_2025_133476
crossref_primary_10_1029_2021WR030211
crossref_primary_10_1038_s41598_021_91646_w
crossref_primary_10_1016_j_rse_2023_113880
crossref_primary_10_1016_j_rse_2022_113365
crossref_primary_10_1080_02626667_2025_2541749
crossref_primary_10_1016_j_jag_2024_104206
crossref_primary_10_1007_s00521_025_11197_3
crossref_primary_10_1038_s41467_021_25254_7
crossref_primary_10_5194_essd_16_1811_2024
crossref_primary_10_1016_j_agrformet_2020_108255
crossref_primary_10_1016_j_jhydrol_2023_129880
crossref_primary_10_1016_j_jhydrol_2024_132558
crossref_primary_10_1016_j_jhydrol_2024_131525
crossref_primary_10_1088_1748_9326_abe436
crossref_primary_10_1016_j_jhydrol_2025_133785
crossref_primary_10_5194_essd_13_281_2021
crossref_primary_10_1016_j_earscirev_2020_103295
crossref_primary_10_1016_j_rse_2022_113011
crossref_primary_10_1007_s00271_024_00963_1
crossref_primary_10_1016_j_agwat_2021_107249
Cites_doi 10.3390/rs8030225
10.1111/gcb.12664
10.1016/j.rse.2017.09.020
10.1016/j.agrformet.2007.04.001
10.1109/IGARSS.2017.8128248
10.1016/S0034-4257(02)00091-3
10.1126/science.275.5299.502
10.1016/S0034-4257(96)00215-5
10.1016/j.agrformet.2011.09.010
10.5194/hess-6-85-2002
10.1016/B978-0-12-417104-6.00002-9
10.1016/j.agrformet.2006.08.008
10.1016/j.agrformet.2012.10.011
10.1007/978-94-017-0519-6_48
10.1007/s10712-008-9037-z
10.3390/rs10060889
10.1073/pnas.1304551110
10.1016/j.rse.2018.02.045
10.5194/hess-21-3879-2017
10.1111/pce.12871
10.1080/01431161.2019.1587208
10.1016/0034-4257(84)90057-9
10.5194/bg-14-4711-2017
10.1029/2011RG000366
10.3390/s17092142
10.1016/j.rse.2018.03.031
10.1016/S0034-4257(01)00240-1
10.1111/nph.14623
10.1016/j.jhydrol.2011.12.006
10.1016/0034-4257(95)00238-3
10.3390/s90503801
10.1007/s10712-018-9478-y
10.1016/j.agsy.2014.01.004
10.1175/BAMS-D-17-0149.1
10.1016/j.rse.2016.11.004
10.1111/nph.14332
10.1016/j.rse.2016.08.030
10.1016/j.rse.2015.08.030
10.1016/j.agrformet.2018.03.014
10.1016/j.rse.2010.05.032
10.1016/j.rse.2007.06.025
10.5194/bg-13-3245-2016
10.1111/j.1365-3040.1997.00094.x
10.1016/j.rse.2012.11.004
10.1016/j.rse.2011.02.019
10.1002/2014JD022453
10.1175/JCLI-D-11-00300.1
10.1016/j.scitotenv.2017.09.325
10.3390/rs11060650
10.1029/2011JD017015
10.1071/PP9920519
10.5194/hess-15-453-2011
10.1073/pnas.1215404110
10.1016/j.rse.2014.01.023
10.1016/j.isprsjprs.2016.05.014
10.1038/nature09396
10.1175/JAMC-D-11-0203.1
10.1016/S0034-4257(02)00074-3
10.1016/j.rse.2018.04.042
10.1175/JCLI-D-16-0758.1
10.1016/j.rse.2008.01.026
10.2134/jeq2016.01.0036
10.1111/j.1365-3040.1995.tb00628.x
10.1029/2010JG001593
10.1080/10106049.2011.562309
10.1016/j.rse.2018.02.067
10.1175/BAMS-D-15-00230.1
10.1029/2011RG000373
10.1111/j.1365-2486.2005.01050.x
10.1029/2007GL031620
10.1111/j.1365-2486.2008.01744.x
10.1016/j.rse.2014.09.013
10.2134/agronj2012.0065
10.1029/2011GB004053
10.1016/j.isprsjprs.2016.03.008
10.1016/j.rse.2018.07.019
10.1109/LGRS.2005.857030
10.5194/bg-11-5021-2014
10.1126/science.1251423
10.1016/j.rse.2007.02.018
10.1016/j.rse.2019.01.039
10.1029/2009GB003768
10.1016/j.agrformet.2004.01.011
10.1061/(ASCE)0733-9437(2008)134:3(273)
10.1016/j.rse.2007.04.010
10.1029/1999GL006049
10.1051/agro:2000105
10.1016/0168-1923(88)90087-1
10.1126/science.1253884
10.1890/07-1609.1
10.1002/2015WR017311
10.1016/S0168-1923(97)00072-5
10.1175/BAMS-D-11-00175.1
10.1016/j.rse.2015.05.024
10.1109/TGRS.2006.872081
10.1016/j.jag.2013.05.007
10.1016/0034-4257(85)90072-0
10.1016/0168-1923(91)90002-8
10.1029/2018WR023884
10.1016/j.rse.2010.04.001
10.1002/wrcr.20349
10.1016/j.rse.2006.07.006
10.1109/LGRS.2007.907537
10.5194/amt-7-1723-2014
10.1016/0034-4257(90)90100-Z
10.1016/S0034-4257(00)00205-4
10.1016/j.rse.2015.12.043
10.1016/j.foreco.2009.10.009
10.1016/j.rse.2007.12.003
10.1016/j.agrformet.2004.03.001
10.5194/gmd-9-2499-2016
10.1016/j.rse.2017.09.021
10.1016/j.agrformet.2017.05.023
10.1002/wat2.1168
10.1016/j.rse.2008.02.012
10.1016/j.rse.2018.02.020
10.1016/j.rse.2013.10.029
ContentType Journal Article
Copyright COPYRIGHT 2020 Copernicus GmbH
2020. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Copyright_xml – notice: COPYRIGHT 2020 Copernicus GmbH
– notice: 2020. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
DBID AAYXX
CITATION
ISR
7QH
7TG
7UA
8FD
8FE
8FG
ABJCF
ABUWG
AEUYN
AFKRA
ATCPS
AZQEC
BENPR
BFMQW
BGLVJ
BHPHI
BKSAR
C1K
CCPQU
DWQXO
F1W
FR3
GNUQQ
H96
HCIFZ
KL.
KR7
L.G
L6V
M7S
PATMY
PCBAR
PHGZM
PHGZT
PIMPY
PKEHL
PQEST
PQGLB
PQQKQ
PQUKI
PRINS
PTHSS
PYCSY
DOA
DOI 10.5194/hess-24-1251-2020
DatabaseName CrossRef
Gale In Context: Science
Aqualine
Meteorological & Geoastrophysical Abstracts
Water Resources Abstracts
Technology Research Database
ProQuest SciTech Collection
ProQuest Technology Collection
Materials Science & Engineering Collection
ProQuest Central (Alumni)
ProQuest One Sustainability
ProQuest Central UK/Ireland
Agricultural & Environmental Science Collection
ProQuest Central Essentials - QC
ProQuest Central
Continental Europe Database
ProQuest Technology Collection
Natural Science Collection
Earth, Atmospheric & Aquatic Science Collection
Environmental Sciences and Pollution Management
ProQuest One Community College
ProQuest Central Korea
ASFA: Aquatic Sciences and Fisheries Abstracts
Engineering Research Database
ProQuest Central Student
Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources
SciTech Premium Collection
Meteorological & Geoastrophysical Abstracts - Academic
Civil Engineering Abstracts
Aquatic Science & Fisheries Abstracts (ASFA) Professional
ProQuest Engineering Collection
Engineering Database
Environmental Science Database
Earth, Atmospheric & Aquatic Science Database
Proquest Central Premium
ProQuest One Academic (New)
ProQuest Publicly Available Content Database
ProQuest One Academic Middle East (New)
ProQuest One Academic Eastern Edition (DO NOT USE)
ProQuest One Applied & Life Sciences
ProQuest One Academic (retired)
ProQuest One Academic UKI Edition
ProQuest Central China
Engineering Collection
Environmental Science Collection
DOAJ Directory of Open Access Journals
DatabaseTitle CrossRef
Publicly Available Content Database
Aquatic Science & Fisheries Abstracts (ASFA) Professional
ProQuest Central Student
Technology Collection
Technology Research Database
ProQuest One Academic Middle East (New)
ProQuest Central Essentials
ProQuest Central (Alumni Edition)
SciTech Premium Collection
ProQuest One Community College
ProQuest Central China
Water Resources Abstracts
Environmental Sciences and Pollution Management
Earth, Atmospheric & Aquatic Science Collection
ProQuest Central
ProQuest One Applied & Life Sciences
ProQuest One Sustainability
ProQuest Engineering Collection
Meteorological & Geoastrophysical Abstracts
Natural Science Collection
ProQuest Central Korea
Agricultural & Environmental Science Collection
ProQuest Central (New)
Engineering Collection
Civil Engineering Abstracts
Engineering Database
ProQuest One Academic Eastern Edition
Earth, Atmospheric & Aquatic Science Database
ProQuest Technology Collection
Continental Europe Database
ProQuest SciTech Collection
Aqualine
Environmental Science Collection
Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources
ProQuest One Academic UKI Edition
ASFA: Aquatic Sciences and Fisheries Abstracts
Materials Science & Engineering Collection
Environmental Science Database
Engineering Research Database
ProQuest One Academic
Meteorological & Geoastrophysical Abstracts - Academic
ProQuest One Academic (New)
DatabaseTitleList

CrossRef
Publicly Available Content Database
Database_xml – sequence: 1
  dbid: DOA
  name: DOAJ Directory of Open Access Journals
  url: https://www.doaj.org/
  sourceTypes: Open Website
– sequence: 2
  dbid: PIMPY
  name: Publicly Available Content Database
  url: http://search.proquest.com/publiccontent
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Geography
Agriculture
EISSN 1607-7938
EndPage 1273
ExternalDocumentID oai_doaj_org_article_20a5a652d3694a4084d06af8f66fae47
A618078247
10_5194_hess_24_1251_2020
GeographicLocations United States--US
GeographicLocations_xml – name: United States--US
GroupedDBID 29I
2WC
5GY
5VS
7XC
8CJ
8FE
8FG
8FH
8R4
8R5
AAFWJ
AAYXX
ABJCF
ABUWG
ACGFO
ACIWK
ADBBV
AENEX
AEUYN
AFFHD
AFKRA
AFPKN
AFRAH
AHGZY
AIAGR
ALMA_UNASSIGNED_HOLDINGS
ATCPS
BANNL
BCNDV
BENPR
BFMQW
BGLVJ
BHPHI
BKSAR
BPHCQ
CCPQU
CITATION
D1J
D1K
E3Z
EBS
ECGQY
EDH
EJD
GROUPED_DOAJ
GX1
H13
HCIFZ
IAO
IEA
IEP
IGS
ISR
ITC
K6-
KQ8
L6V
L8X
LK5
M7R
M7S
OK1
OVT
P2P
PATMY
PCBAR
PHGZM
PHGZT
PIMPY
PQGLB
PQQKQ
PROAC
PTHSS
PYCSY
Q2X
RKB
RNS
TR2
XSB
~02
~KM
7QH
7TG
7UA
8FD
AZQEC
C1K
DWQXO
F1W
FR3
GNUQQ
H96
KL.
KR7
L.G
PKEHL
PQEST
PQUKI
PRINS
ID FETCH-LOGICAL-c413t-f3240c2dc1c60fbf9cdf86d214703d514f106ff979c497663380813a19d73bce3
IEDL.DBID BENPR
ISICitedReferencesCount 33
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000521595100001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 1607-7938
1027-5606
IngestDate Fri Oct 03 12:52:00 EDT 2025
Fri Jul 25 12:20:16 EDT 2025
Sat Nov 29 13:08:40 EST 2025
Sat Nov 29 09:59:09 EST 2025
Wed Nov 26 10:02:25 EST 2025
Tue Nov 18 21:16:56 EST 2025
Sat Nov 29 04:01:59 EST 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 3
Language English
License https://creativecommons.org/licenses/by/4.0
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c413t-f3240c2dc1c60fbf9cdf86d214703d514f106ff979c497663380813a19d73bce3
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ORCID 0000-0002-7601-8886
0000-0001-6238-2479
0000-0002-1660-7320
OpenAccessLink https://www.proquest.com/docview/2414702734?pq-origsite=%requestingapplication%
PQID 2414702734
PQPubID 105724
PageCount 23
ParticipantIDs doaj_primary_oai_doaj_org_article_20a5a652d3694a4084d06af8f66fae47
proquest_journals_2414702734
gale_infotracmisc_A618078247
gale_infotracacademiconefile_A618078247
gale_incontextgauss_ISR_A618078247
crossref_primary_10_5194_hess_24_1251_2020
crossref_citationtrail_10_5194_hess_24_1251_2020
PublicationCentury 2000
PublicationDate 2020-03-20
PublicationDateYYYYMMDD 2020-03-20
PublicationDate_xml – month: 03
  year: 2020
  text: 2020-03-20
  day: 20
PublicationDecade 2020
PublicationPlace Katlenburg-Lindau
PublicationPlace_xml – name: Katlenburg-Lindau
PublicationTitle Hydrology and earth system sciences
PublicationYear 2020
Publisher Copernicus GmbH
Copernicus Publications
Publisher_xml – name: Copernicus GmbH
– name: Copernicus Publications
References ref57
ref56
ref59
ref58
ref53
ref52
ref55
ref54
ref51
ref50
ref46
ref45
ref48
ref47
ref42
ref41
ref44
ref43
ref49
ref8
ref7
ref9
ref4
ref3
ref6
ref5
ref100
ref101
ref40
ref35
ref34
ref37
ref36
ref31
ref30
ref33
ref32
ref39
ref38
ref24
ref23
ref26
ref25
ref20
ref22
ref21
ref28
ref27
ref29
ref13
ref12
ref15
ref128
ref14
ref97
ref126
ref96
ref127
ref11
ref99
ref124
ref10
ref98
ref125
ref17
ref16
ref19
ref18
ref93
ref92
ref95
ref94
ref91
ref90
ref89
ref86
ref85
ref88
ref87
ref82
ref81
ref84
ref83
ref80
ref79
ref108
ref78
ref109
ref106
ref107
ref75
ref104
ref74
ref105
ref77
ref102
ref76
ref103
ref2
ref1
ref71
ref111
ref70
ref112
ref73
ref72
ref110
ref68
ref119
ref67
ref117
ref69
ref118
ref64
ref115
ref63
ref116
ref66
ref113
ref65
ref114
ref60
ref122
ref123
ref62
ref120
ref61
ref121
References_xml – ident: ref123
  doi: 10.3390/rs8030225
– ident: ref1
– ident: ref124
  doi: 10.1111/gcb.12664
– ident: ref62
  doi: 10.1016/j.rse.2017.09.020
– ident: ref91
– ident: ref115
  doi: 10.1016/j.agrformet.2007.04.001
– ident: ref43
  doi: 10.1109/IGARSS.2017.8128248
– ident: ref89
  doi: 10.1016/S0034-4257(02)00091-3
– ident: ref92
  doi: 10.1126/science.275.5299.502
– ident: ref3
  doi: 10.1016/S0034-4257(96)00215-5
– ident: ref86
  doi: 10.1016/j.agrformet.2011.09.010
– ident: ref97
  doi: 10.5194/hess-6-85-2002
– ident: ref35
  doi: 10.1016/B978-0-12-417104-6.00002-9
– ident: ref51
  doi: 10.1016/j.agrformet.2006.08.008
– ident: ref83
  doi: 10.1016/j.agrformet.2012.10.011
– ident: ref9
  doi: 10.1007/978-94-017-0519-6_48
– ident: ref53
  doi: 10.1007/s10712-008-9037-z
– ident: ref2
  doi: 10.3390/rs10060889
– ident: ref44
– ident: ref103
  doi: 10.1073/pnas.1304551110
– ident: ref16
  doi: 10.1016/j.rse.2018.02.045
– ident: ref71
  doi: 10.5194/hess-21-3879-2017
– ident: ref102
– ident: ref73
  doi: 10.1111/pce.12871
– ident: ref111
  doi: 10.1080/01431161.2019.1587208
– ident: ref104
  doi: 10.1016/0034-4257(84)90057-9
– ident: ref114
  doi: 10.5194/bg-14-4711-2017
– ident: ref55
  doi: 10.1029/2011RG000366
– ident: ref118
  doi: 10.3390/s17092142
– ident: ref125
  doi: 10.1016/j.rse.2018.03.031
– ident: ref5
  doi: 10.1016/S0034-4257(01)00240-1
– ident: ref107
  doi: 10.1111/nph.14623
– ident: ref45
  doi: 10.1016/j.jhydrol.2011.12.006
– ident: ref47
  doi: 10.1016/0034-4257(95)00238-3
– ident: ref60
  doi: 10.3390/s90503801
– ident: ref106
  doi: 10.1007/s10712-018-9478-y
– ident: ref15
  doi: 10.1016/j.agsy.2014.01.004
– ident: ref80
  doi: 10.1175/BAMS-D-17-0149.1
– ident: ref30
  doi: 10.1016/j.rse.2016.11.004
– ident: ref109
  doi: 10.1111/nph.14332
– ident: ref49
  doi: 10.1016/j.rse.2016.08.030
– ident: ref18
  doi: 10.1016/j.rse.2015.08.030
– ident: ref42
  doi: 10.1016/j.agrformet.2018.03.014
– ident: ref128
  doi: 10.1016/j.rse.2010.05.032
– ident: ref26
  doi: 10.1016/j.rse.2007.06.025
– ident: ref113
  doi: 10.5194/bg-13-3245-2016
– ident: ref22
  doi: 10.1111/j.1365-3040.1997.00094.x
– ident: ref121
  doi: 10.1016/j.rse.2012.11.004
– ident: ref76
  doi: 10.1016/j.rse.2011.02.019
– ident: ref88
  doi: 10.1002/2014JD022453
– ident: ref81
  doi: 10.1175/JCLI-D-11-00300.1
– ident: ref36
  doi: 10.1016/j.scitotenv.2017.09.325
– ident: ref126
  doi: 10.3390/rs11060650
– ident: ref39
  doi: 10.1029/2011JD017015
– ident: ref19
  doi: 10.1071/PP9920519
– ident: ref74
  doi: 10.5194/hess-15-453-2011
– ident: ref116
  doi: 10.1073/pnas.1215404110
– ident: ref75
  doi: 10.1016/j.rse.2014.01.023
– ident: ref127
  doi: 10.1016/j.isprsjprs.2016.05.014
– ident: ref52
  doi: 10.1038/nature09396
– ident: ref8
– ident: ref11
  doi: 10.1175/JAMC-D-11-0203.1
– ident: ref77
  doi: 10.1016/S0034-4257(02)00074-3
– ident: ref66
  doi: 10.1016/j.rse.2018.04.042
– ident: ref31
  doi: 10.1175/JCLI-D-16-0758.1
– ident: ref48
  doi: 10.1016/j.rse.2008.01.026
– ident: ref100
  doi: 10.2134/jeq2016.01.0036
– ident: ref58
  doi: 10.1111/j.1365-3040.1995.tb00628.x
– ident: ref13
  doi: 10.1029/2010JG001593
– ident: ref14
  doi: 10.1080/10106049.2011.562309
– ident: ref41
  doi: 10.1016/j.rse.2018.02.067
– ident: ref90
  doi: 10.1175/BAMS-D-15-00230.1
– ident: ref110
  doi: 10.1029/2011RG000373
– ident: ref12
  doi: 10.1111/j.1365-2486.2005.01050.x
– ident: ref32
  doi: 10.1029/2007GL031620
– ident: ref57
– ident: ref54
  doi: 10.1111/j.1365-2486.2008.01744.x
– ident: ref117
  doi: 10.1016/j.rse.2014.09.013
– ident: ref78
  doi: 10.2134/agronj2012.0065
– ident: ref85
  doi: 10.1029/2011GB004053
– ident: ref33
  doi: 10.1016/j.isprsjprs.2016.03.008
– ident: ref67
  doi: 10.1016/j.rse.2018.07.019
– ident: ref68
  doi: 10.1109/LGRS.2005.857030
– ident: ref38
  doi: 10.5194/bg-11-5021-2014
– ident: ref63
  doi: 10.1126/science.1251423
– ident: ref10
  doi: 10.1016/j.rse.2007.02.018
– ident: ref119
  doi: 10.1016/j.rse.2019.01.039
– ident: ref37
  doi: 10.1029/2009GB003768
– ident: ref40
– ident: ref98
  doi: 10.1016/j.agrformet.2004.01.011
– ident: ref96
  doi: 10.1061/(ASCE)0733-9437(2008)134:3(273)
– ident: ref56
  doi: 10.1016/j.rse.2007.04.010
– ident: ref50
  doi: 10.1029/1999GL006049
– ident: ref112
  doi: 10.1051/agro:2000105
– ident: ref82
  doi: 10.1016/0168-1923(88)90087-1
– ident: ref79
  doi: 10.1126/science.1253884
– ident: ref69
  doi: 10.1890/07-1609.1
– ident: ref108
  doi: 10.1002/2015WR017311
– ident: ref6
  doi: 10.1016/S0168-1923(97)00072-5
– ident: ref34
  doi: 10.1175/BAMS-D-11-00175.1
– ident: ref95
  doi: 10.1016/j.rse.2015.05.024
– ident: ref29
  doi: 10.1109/TGRS.2006.872081
– ident: ref101
– ident: ref24
  doi: 10.1016/j.jag.2013.05.007
– ident: ref93
  doi: 10.1126/science.275.5299.502
– ident: ref105
  doi: 10.1016/0034-4257(85)90072-0
– ident: ref20
  doi: 10.1016/0168-1923(91)90002-8
– ident: ref7
  doi: 10.1029/2018WR023884
– ident: ref84
– ident: ref65
  doi: 10.1016/j.rse.2010.04.001
– ident: ref17
  doi: 10.1002/wrcr.20349
– ident: ref70
  doi: 10.1016/j.rse.2006.07.006
– ident: ref4
  doi: 10.1109/LGRS.2007.907537
– ident: ref23
  doi: 10.5194/amt-7-1723-2014
– ident: ref46
  doi: 10.1016/0034-4257(90)90100-Z
– ident: ref28
– ident: ref61
  doi: 10.1016/S0034-4257(00)00205-4
– ident: ref94
  doi: 10.1016/j.rse.2015.12.043
– ident: ref99
  doi: 10.1016/j.foreco.2009.10.009
– ident: ref21
  doi: 10.1016/j.rse.2007.12.003
– ident: ref72
  doi: 10.1016/j.agrformet.2004.03.001
– ident: ref64
  doi: 10.5194/gmd-9-2499-2016
– ident: ref87
  doi: 10.1016/j.rse.2017.09.021
– ident: ref59
  doi: 10.1016/j.agrformet.2017.05.023
– ident: ref122
  doi: 10.1002/wat2.1168
– ident: ref25
  doi: 10.1016/j.rse.2008.02.012
– ident: ref120
  doi: 10.1016/j.rse.2018.02.020
– ident: ref27
  doi: 10.1016/j.rse.2013.10.029
SSID ssj0028862
Score 2.4344866
Snippet With increasing crop water demands and drought threats, mapping and monitoring of cropland evapotranspiration (ET) at high spatial and temporal resolutions...
With increasing crop water demands and drought threats, mapping and monitoring of cropland evapotranspiration (ET) at high spatial and temporal resolutions...
SourceID doaj
proquest
gale
crossref
SourceType Open Website
Aggregation Database
Enrichment Source
Index Database
StartPage 1251
SubjectTerms Agricultural land
Agricultural management
Agriculture
Albedo
Albedo (solar)
Algorithms
Analysis
Belts
Carbon
Carbon dioxide
Computer simulation
Corn
Corn belt
Crop evapotranspiration
Crop water
Daily
Data
Data integration
Decision making
Drought
Droughts
Energy
Evapotranspiration
Evapotranspiration estimates
Evapotranspiration models
Frameworks
Generic drugs
Humidity
Hydrologic cycle
Landsat
Landsat satellites
Leaf area
Leaf area index
Mapping
Precision agriculture
Reflectance
Remote sensing
Resolution
Resource management
Root-mean-square errors
Satellite data
Satellites
Seasonal variation
Simulators
Sustainability
Sustainable development
Time
Tower measurements
Vegetation
Water management
Water resource management
Water resources
Water resources management
Water shortages
Weather
SummonAdditionalLinks – databaseName: Copernicus Publications
  dbid: RKB
  link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1Lb9QwELZQhQQX3oiFgkYICQnVInG8TsJtt6KiEqrQbot6sxw_2pVCUm3TVr31ypG_yC9hJs5W3QNwgGsyduL5xvaMPP6GsTfO5xXxfvMqVBmXyiteFGPFjSPioVAE05PpfP2c7-0Vh4fllxulvignLNIDR8VhcG7GRo2Fy1QpjUwK6RJlsBOlgvGS7pGjGdKUnFENtyHUKgoVzzlFznFPV_E8E70V-f4YVxAuiKxvnKKNUKHvGztST9z_u-W533N27v_D3z5g9wZHEyaxyUN2yzeP2J2h5vnx5WP2Y4q65_P9ye7sAxgIqywt6Fog6g10ZT04s6gvtyBLfl59_7YFpnFg6ppfRMcRqP4X-HNz0nY9Sfoi2hNQNv0R9MmKPB4PwKnpuT_7Pjv8XLsE7AIO5rDdLhuY-rp7wg52Pu5vf-JDgQZuce_reCA2PyucTa1KQhVK60KhHJU-SjKHrljAgDOEMi-tRLdHYTiMHkhm0tLlWWV99pRtNG3jnzHwIghvhM-8SGQqRaXQgGSwmcwxgBdyxJIVSNoO7OVURKPWGMUQrppw1UJqwlUTriP27rrJSaTu-JPwlMC8FiTW7f4BoqsHdPXf0B2x12Q3mng1GkrcOTJn-J3d-UxPVErM_oKE3g5CgbCxZrgHgXogKq41yc01SZz4dv31yjz1sPDQmEj5xFn0_H-M6AW7S9qhpDuRbLKNbnnmX7Lb9rxbnC5f9XPuF0g5Kto
  priority: 102
  providerName: Copernicus Gesellschaft
– databaseName: DOAJ Directory of Open Access Journals
  dbid: DOA
  link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrZ3Na9VAEMAXKQW9iJ_4tMoggiBdTDb7Nom394rFghTpa6W3ZbMf7YOYlNe0pbdePfZf7F_SmU1e6TuoF6_JZJPMTHZnkslvGPvgfF4R95tXocq4VF7xohgrbhyBh0IRTITp_Pye7-4Wh4flj3utvqgmrMcD94rD5NyMjRoLl6lSGpkU0iXK4CBKBeNl_I88yctlMjWkWkWh-u-cIue4pqv-eyZGK_LzMc4gXBCsb5yij1Cj73srUgT3_2l6jmvO9hP2eAgWYdJf5FP2wDfP2MOhb_nx5XN2PUX98dn-ZGfvCxgIy0or6FogfAaGox6cmdeXm5AlN1e_f22CaRyYuuYXffAH1MML_Lk5absIOp_3PgFUEX8EseCQ96_44dREfmccs8PTtQvAIeBgBlvtooGpr7sX7GD76_7WNz40WeAW16-OByLyWeFsalUSqlBaFwrlqH1RkjkMpwImjSGUeWklhi4KU1qMIjKTli7PKuuzl2ytaRv_ioEXQXgjfOZFIlMpKoVOIIPNZI5JuJAjliwVre1AIKdGGLXGTIRso8k2WkhNttFkmxH7dHfISY_f-JvwlKx3J0jk7LgB_UkP_qT_5U8j9p5sr4mN0VDxzZE5w_PszPb0RKVE5xck9HEQCmQba4Z_GVAPhNNakdxYkcSH167uXrqYHiYPuidSPnGHXv-PO3rDHpF2qHBOJBtsrVuc-bds3Z5389PFu_jc3AKftxjU
  priority: 102
  providerName: Directory of Open Access Journals
Title BESS-STAIR: a framework to estimate daily, 30 m, and all-weather crop evapotranspiration using multi-source satellite data for the US Corn Belt
URI https://www.proquest.com/docview/2414702734
https://doaj.org/article/20a5a652d3694a4084d06af8f66fae47
Volume 24
WOSCitedRecordID wos000521595100001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVAGF
  databaseName: Copernicus Publications
  customDbUrl:
  eissn: 1607-7938
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0028862
  issn: 1607-7938
  databaseCode: RKB
  dateStart: 19970101
  isFulltext: true
  titleUrlDefault: http://publications.copernicus.org/open-access_journals/open_access_journals_a_z.html
  providerName: Copernicus Gesellschaft
– providerCode: PRVAON
  databaseName: DOAJ Directory of Open Access Journals
  customDbUrl:
  eissn: 1607-7938
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0028862
  issn: 1607-7938
  databaseCode: DOA
  dateStart: 19970101
  isFulltext: true
  titleUrlDefault: https://www.doaj.org/
  providerName: Directory of Open Access Journals
– providerCode: PRVPQU
  databaseName: Continental Europe Database
  customDbUrl:
  eissn: 1607-7938
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0028862
  issn: 1607-7938
  databaseCode: BFMQW
  dateStart: 20090601
  isFulltext: true
  titleUrlDefault: https://search.proquest.com/conteurope
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: Earth, Atmospheric & Aquatic Science Database
  customDbUrl:
  eissn: 1607-7938
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0028862
  issn: 1607-7938
  databaseCode: PCBAR
  dateStart: 20090601
  isFulltext: true
  titleUrlDefault: https://search.proquest.com/eaasdb
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: Engineering Database
  customDbUrl:
  eissn: 1607-7938
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0028862
  issn: 1607-7938
  databaseCode: M7S
  dateStart: 20090601
  isFulltext: true
  titleUrlDefault: http://search.proquest.com
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: Environmental Science Database
  customDbUrl:
  eissn: 1607-7938
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0028862
  issn: 1607-7938
  databaseCode: PATMY
  dateStart: 20090601
  isFulltext: true
  titleUrlDefault: http://search.proquest.com/environmentalscience
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: ProQuest Central
  customDbUrl:
  eissn: 1607-7938
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0028862
  issn: 1607-7938
  databaseCode: BENPR
  dateStart: 20090601
  isFulltext: true
  titleUrlDefault: https://www.proquest.com/central
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: Publicly Available Content Database
  customDbUrl:
  eissn: 1607-7938
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0028862
  issn: 1607-7938
  databaseCode: PIMPY
  dateStart: 20090601
  isFulltext: true
  titleUrlDefault: http://search.proquest.com/publiccontent
  providerName: ProQuest
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1Lb9NAEF7RFgk48ChFBEq0QkhIqKs6683a5oKSqhURNIqSFJWTtd5HGinYwXGL-iv4y8zYm4gc6IWTJXv8WM_neeyOvyHknbFRhrzfLHNZyIS0ksVxVzJlkHjIxU7VZDrfvkbDYXx5mYz8hNvKl1WubWJtqE2hcY78GDyNiGoylk_Lnwy7RuHqqm-hsUP2kKkMcL7XPx2OxpuUK45ls97JIwa-XTbrmhC1iOMrsCSMI2lftwNYwYbff3mmmsD_X2a69j1nT_73qZ-Sxz7qpL0GJs_IPZvvk0e9WemZN-w-eeDboV_dPie_-6AWNpn2BuOPVFG3LuCiVUGRlQOiXEuNmi9uj2gY0B9HVOWGqsWC_WoiSoqNwai9UcuiqtnT5w3QKJbZz2hdxciadQO6UjUpaH3FCm5WlBQuQS8m9KQoc9q3i-qAXJydTk8-M9-5gWlwihVzSPOnudEdLQOXuUQbF0uDPZGC0ECM5iATdS6JEi0gHpKQJ0NoEqpOYqIw0zZ8QXbzIrcvCbXccau4DS0P4GXyTAKyhNOhiCCz56JFgrXWUu1pzbG7xiKF9AYVnaKiUy5SVHSKim6RD5tTlg2nx13CfYTCRhDpuOsdRTlL_dcNgqqrZJebUCZCiSAWJpAKkC6lU1ZELfIWgZQi4UaOFT0zdQ33GUzGaU92kPKfo9B7L-RQN1r5HyTgPSBH15bk4ZYkWAS9fXgNxtRbJBzTGomv7j78mjzEcWOdHQ8OyW5VXts35L6-qearsu0_sHY9d9HGStkJ7Bv1puffcTs4H8F2Z_yl_wdRnzGG
linkProvider ProQuest
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1bb9MwFLZGhzR44DJAFAZYCISEZi11XCdBQqgdTKvWVdXaofEUHMfuKpWkpNmm_gr-Cb-Rc3Kp6AN72wOvzamj2t-51fb3EfImNl6EvN8sspHLhDSS-X5bMhUj8ZD1rSrIdL72vcHAPzsLhhvkd30XBo9V1jGxCNRxqvE_8j3INMIryFg-zX8yVI3C3dVaQqOExZFZXkHLtvjY-wzr-5bzgy_j_UNWqQowDQE7ZxYp6DSPdUtLx0Y20LH1ZYx6PY4bQ_1goUuyNvACLSBXS-jhIG26qhXEnhtp48K4t8imALA7DbI57B0Pv61aPN-X5f4q9xjUErLcR4UqSeydQ-RiHEkC2y3AJgqM_5UJC8GAf6WFItcd3P_fZukBuVdV1bRTusFDsmGSbXK3M8kqZhGzTbYquffz5SPyqwuwY6Nxp3fygSpq6wNqNE8pso5AFW9orKaz5S51Hfpjl6okpmo2Y1dlxUxR-IyaSzVP84Idflo6EsVrBBNanNJk5b4IXaiC9LQYMYeXpRmFIejpiO6nWUK7ZpY_Jqc3MjtPSCNJE_OUUMMtN4ob13AHFo9HEjxHWO0KT0hojpvEqVES6oq2HdVDZiG0bwisEIEVchEisEIEVpO8X31lXnKWXGfcReitDJFuvPggzSZhFb3AULWVbPPYlYFQwvFF7EgFniylVUZ4TfIagRsioUiCJ5Ym6gLe0xudhB3ZQkkDjkbvKiOLa6NVdQEE5gE5yNYsd9YsIeLp9cc1-MMq4uJvqpH_7PrHr8jW4fi4H_Z7g6Pn5A7OAZ4p5M4OaeTZhXlBbuvLfLrIXlbOTcn3m_aUP_gphuo
linkToPdf http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1bb9MwFLZGh7g8cBkgCgMsBEJCs5o6qZMgIdRuq6g2VVW7ob0Fx5euUklKmm3qr-D_8Os4J5eKPrC3PfDanDqq_Z1bbX8fIe-08WPk_WaxjV3mCSNYEHQEkxqJh2xgZUGm8-3YHw6Ds7NwtEV-13dh8FhlHROLQK1Thf-RtyDTeH5BxtKy1bGI0UH_y-InQwUp3Gmt5TRKiByZ1RW0b8vPgwNY6_ec9w9P9r-ySmGAKQjeObNIR6e4Vm0lHBvbUGkbCI3aPY6roZaw0DFZG_qh8iBvC-jnIIW6sh1q342VcWHcW2Tbd6HpaZDt3uFwNF63e0Egyr1W7jOoK0S5pwoVk9c6hyjGOBIGdtqAUxQb_ysrFuIB_0oRRd7rP_yfZ-wReVBV27RbusdjsmWSHXK_O80qxhGzQ-5WMvDnqyfkVw_gyCYn3cH4E5XU1gfXaJ5SZCOB6t5QLWfz1R51Hfpjj8pEUzmfs6uykqYoiEbNpVykecEaPysdjOL1giktTm-ycr-ELmVBhlqMmMPL0ozCEPR0QvfTLKE9M8-fktMbmZ1npJGkiXlOqOGWG8mNa7gDC8ljAR7lWeV6viegaW4Sp0ZMpCo6d1QVmUfQ1iHIIgRZxL0IQRYhyJrk4_ori5LL5DrjHsJwbYg05MUHaTaNqqgGhrIjRYdrV4Se9JzA046Q4OFCWGk8v0neIogjJBpJEIBTeQHvGUzGUVe0UeqAo9GHysji2ihZXQyBeUBusg3L3Q1LiIRq83HtCFEVifE31V7w4vrHb8gdcI_oeDA8eknu4RTgUUPu7JJGnl2YV-S2usxny-x15eeUfL9pR_kDkLePhA
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=BESS-STAIR%3A+a+framework+to+estimate+daily%2C+30+m%2C+and+all-weather+crop+evapotranspiration+using+multi-source+satellite+data+for+the+US+Corn+Belt&rft.jtitle=Hydrology+and+earth+system+sciences&rft.au=Jiang%2C+Chongya&rft.au=Guan%2C+Kaiyu&rft.au=Pan%2C+Ming&rft.au=Ryu%2C+Youngryel&rft.date=2020-03-20&rft.pub=Copernicus+GmbH&rft.issn=1027-5606&rft.volume=24&rft.issue=3&rft.spage=1251&rft_id=info:doi/10.5194%2Fhess-24-1251-2020&rft.externalDocID=A618078247
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1607-7938&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1607-7938&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1607-7938&client=summon