Application of Sentinel-1 Data to Estimate Height and Biomass of Rice Crop in Astaneh-ye Ashrafiyeh, Iran

Crops monitoring is a challengeable subject that radar images can help it. The applicability of Sentinel-1 SAR data with dual polarization provided a splendid opportunity to develop a method for estimating rice parameters. Heights of cereal and biomass are two significant characteristics of rice tha...

Full description

Saved in:
Bibliographic Details
Published inJournal of the Indian Society of Remote Sensing Vol. 48; no. 1; pp. 11 - 19
Main Authors Sharifi, Alireza, Hosseingholizadeh, Mohammad
Format Journal Article
LanguageEnglish
Published New Delhi Springer India 01.01.2020
Springer Nature B.V
Subjects
Online AccessGet full text

Cover

Loading…
Abstract Crops monitoring is a challengeable subject that radar images can help it. The applicability of Sentinel-1 SAR data with dual polarization provided a splendid opportunity to develop a method for estimating rice parameters. Heights of cereal and biomass are two significant characteristics of rice that can be estimated with assessing satellite data and field measurements by classical regression methods [multiple linear regression (MLR), relevance vector regression (RVR), and support vector regression (SVR)]. In this study, Sentinel-1 SAR data from April 2018 to September 2018 in Astaneh-ye Ashrafiyeh region in the north of Iran were used. To evaluate and analyze validation of regression methods, field measurements (gathered from 15 plots) were utilized. The efficiency of nonparametric methods (SVR and RVR) is much better than that of the parametric regression (MLR) for rice parameter estimations. Among nonparametric approaches, RVR method has better results than SVR, because of the highest correlation coefficient ( R 2 ) and lowest root mean square error (RMSE). R 2  = 0.92, RMSE = 162.1, and MAE = 971.9 and R 2  = 0.92, RMSE = 10.9, and MAE = 70.71 are the results of height and biomass, respectively.
AbstractList Crops monitoring is a challengeable subject that radar images can help it. The applicability of Sentinel-1 SAR data with dual polarization provided a splendid opportunity to develop a method for estimating rice parameters. Heights of cereal and biomass are two significant characteristics of rice that can be estimated with assessing satellite data and field measurements by classical regression methods [multiple linear regression (MLR), relevance vector regression (RVR), and support vector regression (SVR)]. In this study, Sentinel-1 SAR data from April 2018 to September 2018 in Astaneh-ye Ashrafiyeh region in the north of Iran were used. To evaluate and analyze validation of regression methods, field measurements (gathered from 15 plots) were utilized. The efficiency of nonparametric methods (SVR and RVR) is much better than that of the parametric regression (MLR) for rice parameter estimations. Among nonparametric approaches, RVR method has better results than SVR, because of the highest correlation coefficient (R2) and lowest root mean square error (RMSE). R2 = 0.92, RMSE = 162.1, and MAE = 971.9 and R2 = 0.92, RMSE = 10.9, and MAE = 70.71 are the results of height and biomass, respectively.
Crops monitoring is a challengeable subject that radar images can help it. The applicability of Sentinel-1 SAR data with dual polarization provided a splendid opportunity to develop a method for estimating rice parameters. Heights of cereal and biomass are two significant characteristics of rice that can be estimated with assessing satellite data and field measurements by classical regression methods [multiple linear regression (MLR), relevance vector regression (RVR), and support vector regression (SVR)]. In this study, Sentinel-1 SAR data from April 2018 to September 2018 in Astaneh-ye Ashrafiyeh region in the north of Iran were used. To evaluate and analyze validation of regression methods, field measurements (gathered from 15 plots) were utilized. The efficiency of nonparametric methods (SVR and RVR) is much better than that of the parametric regression (MLR) for rice parameter estimations. Among nonparametric approaches, RVR method has better results than SVR, because of the highest correlation coefficient ( R 2 ) and lowest root mean square error (RMSE). R 2  = 0.92, RMSE = 162.1, and MAE = 971.9 and R 2  = 0.92, RMSE = 10.9, and MAE = 70.71 are the results of height and biomass, respectively.
Crops monitoring is a challengeable subject that radar images can help it. The applicability of Sentinel-1 SAR data with dual polarization provided a splendid opportunity to develop a method for estimating rice parameters. Heights of cereal and biomass are two significant characteristics of rice that can be estimated with assessing satellite data and field measurements by classical regression methods [multiple linear regression (MLR), relevance vector regression (RVR), and support vector regression (SVR)]. In this study, Sentinel-1 SAR data from April 2018 to September 2018 in Astaneh-ye Ashrafiyeh region in the north of Iran were used. To evaluate and analyze validation of regression methods, field measurements (gathered from 15 plots) were utilized. The efficiency of nonparametric methods (SVR and RVR) is much better than that of the parametric regression (MLR) for rice parameter estimations. Among nonparametric approaches, RVR method has better results than SVR, because of the highest correlation coefficient (R²) and lowest root mean square error (RMSE). R² = 0.92, RMSE = 162.1, and MAE = 971.9 and R² = 0.92, RMSE = 10.9, and MAE = 70.71 are the results of height and biomass, respectively.
Author Hosseingholizadeh, Mohammad
Sharifi, Alireza
Author_xml – sequence: 1
  givenname: Alireza
  surname: Sharifi
  fullname: Sharifi, Alireza
  email: a_sharifi@sru.ac.ir
  organization: Department of Surveying Engineering, Faculty of Civil Engineering, Shahid Rajaee Teacher Training University
– sequence: 2
  givenname: Mohammad
  surname: Hosseingholizadeh
  fullname: Hosseingholizadeh, Mohammad
  organization: Department of Surveying Engineering, Faculty of Civil Engineering, Shahid Rajaee Teacher Training University
BookMark eNp9kUtLAzEUhYMo-PwDrgJuXBjNazIzy1rrAwTBB7gLaeaOjUyTMUkX_fdGKwguXIRckvOFk3P20bYPHhA6ZvScUVpfJMYrLgllbVm0qkmzhfZoW0siKFXbZeZVRZSir7toP6X3cigrxveQm4zj4KzJLngcevwEPjsPA2H4ymSDc8CzlN3SZMC34N4WGRvf4UsXlialL-LRWcDTGEbsPJ6kbDwsyBrKuIimd2tYnOG7aPwh2unNkODoZz9AL9ez5-ktuX-4uZtO7okVFc9E1I2w5QfccClsV8tGqfm8nXdcicayTom2Y23bUNUrDhTknIueM2jLjez7Whyg0827YwwfK0hZL12yMAzFWFglzSWlUtISWJGe_JG-h1X0xZ3mQgpeV7XgRdVsVDaGlCL02rr8HViOxg2aUf3Vgd50oEsH-rsD3RSU_0HHWLKM6_8hsYFSEfs3iL-u_qE-AWLXmM0
CitedBy_id crossref_primary_10_1016_j_jfca_2024_107107
crossref_primary_10_1016_j_heliyon_2024_e39297
crossref_primary_10_1108_AEAT_06_2020_0121
crossref_primary_10_1007_s12145_025_01701_7
crossref_primary_10_1371_journal_pone_0313946
crossref_primary_10_1016_j_jag_2025_104373
crossref_primary_10_1080_19479832_2022_2055157
crossref_primary_10_1007_s11869_025_01718_3
crossref_primary_10_1016_j_compag_2024_109370
crossref_primary_10_3390_rs14225633
crossref_primary_10_3390_agronomy11071363
crossref_primary_10_1186_s13007_024_01224_0
crossref_primary_10_1016_j_rsase_2024_101353
crossref_primary_10_1016_j_bdr_2024_100480
crossref_primary_10_1080_01431161_2022_2027547
crossref_primary_10_1007_s12524_024_02028_4
crossref_primary_10_1016_j_compag_2022_107260
crossref_primary_10_1016_j_zool_2025_126240
crossref_primary_10_1111_wej_12681
crossref_primary_10_1088_1742_6596_2273_1_012028
crossref_primary_10_1016_j_ecoinf_2022_101743
crossref_primary_10_3389_fpls_2022_903643
crossref_primary_10_1007_s10668_023_04138_4
crossref_primary_10_1080_07038992_2021_2011180
crossref_primary_10_1007_s12524_021_01362_1
crossref_primary_10_1002_jsfa_10568
crossref_primary_10_1016_j_eja_2024_127367
crossref_primary_10_1007_s12524_020_01155_y
crossref_primary_10_1007_s12524_021_01382_x
crossref_primary_10_1007_s10661_024_13493_2
crossref_primary_10_1007_s10708_024_11254_9
crossref_primary_10_1016_j_eja_2024_127372
crossref_primary_10_1016_j_eja_2024_127496
crossref_primary_10_1016_j_tfp_2024_100657
crossref_primary_10_1016_j_sciaf_2024_e02314
crossref_primary_10_1002_jsfa_10696
crossref_primary_10_1016_j_measurement_2024_116535
crossref_primary_10_1016_j_prime_2024_100611
crossref_primary_10_1108_AEAT_11_2020_0262
crossref_primary_10_1109_JSTARS_2021_3099118
crossref_primary_10_3390_agriengineering6020063
crossref_primary_10_3390_agriculture12122083
crossref_primary_10_1007_s12524_024_02027_5
crossref_primary_10_1007_s12524_022_01499_7
crossref_primary_10_1109_JSTARS_2020_2998638
crossref_primary_10_1007_s12524_021_01399_2
crossref_primary_10_1016_j_asr_2022_02_021
crossref_primary_10_1016_j_ejrs_2024_11_003
crossref_primary_10_3390_rs14040934
crossref_primary_10_1016_j_rsase_2025_101503
crossref_primary_10_3390_rs14030546
crossref_primary_10_1016_j_rsase_2023_101029
Cites_doi 10.3390/s17091966
10.1016/j.cj.2016.01.008
10.1007/s12524-014-0423-3
10.1109/TGRS.2015.2482001
10.14358/PERS.83.1.41
10.1080/014311698215748
10.1117/1.JRS.9.097695
10.1080/10095020.2018.1489576
10.3390/rs11040400
10.1016/j.rse.2016.10.007
10.1109/36.964973
10.3390/rs10020206
10.1109/JSTARS.2017.2737543
10.1016/j.isprsjprs.2016.01.004
10.1109/JSTARS.2018.2834383
10.1016/S0169-5347(03)00070-3
10.1109/JSTARS.2016.2575362
10.1080/10095020.2017.1419607
10.1016/b978-0-12-813148-0.00001-3
10.1016/j.jag.2016.12.014
10.1016/j.jag.2012.07.016
10.1007/s12524-019-00966-y
10.1201/9781315272573
10.1038/nclimate1945
10.1080/01431161.2012.738946
10.3390/rs71215808
10.1109/LGRS.2014.2334371
10.1111/2041-210X.13025
10.1080/2150704X.2018.1452058
10.1016/j.agsy.2018.05.007
ContentType Journal Article
Copyright Indian Society of Remote Sensing 2019
2019© Indian Society of Remote Sensing 2019
Copyright_xml – notice: Indian Society of Remote Sensing 2019
– notice: 2019© Indian Society of Remote Sensing 2019
DBID AAYXX
CITATION
7S9
L.6
DOI 10.1007/s12524-019-01057-8
DatabaseName CrossRef
AGRICOLA
AGRICOLA - Academic
DatabaseTitle CrossRef
AGRICOLA
AGRICOLA - Academic
DatabaseTitleList

AGRICOLA
DeliveryMethod fulltext_linktorsrc
Discipline Visual Arts
EISSN 0974-3006
EndPage 19
ExternalDocumentID 10_1007_s12524_019_01057_8
GeographicLocations Iran
GeographicLocations_xml – name: Iran
GrantInformation_xml – fundername: Shahid Rajaee Teacher Training University (IR)
GroupedDBID -5A
-5G
-5~
-BR
-EM
-Y2
-~C
.VR
06D
0R~
0VY
1N0
203
29O
2J2
2JN
2JY
2KG
2KM
2LR
30V
4.4
406
408
40D
40E
5GY
5VS
67M
67Z
6NX
95-
95.
95~
96X
AAAVM
AABHQ
AAHBH
AAHNG
AAIAL
AAJBT
AAJKR
AANZL
AARHV
AARTL
AASML
AATNV
AAYIU
AAYQN
AAYZH
ABDZT
ABECU
ABFTV
ABJOX
ABKCH
ABMNI
ABMQK
ABNWP
ABQBU
ABQSL
ABSXP
ABTEG
ABTHY
ABTKH
ABTMW
ABULA
ABXPI
ACGFS
ACHSB
ACHXU
ACIWK
ACKNC
ACMDZ
ACMLO
ACOKC
ACSNA
ACZOJ
ADHHG
ADHIR
ADKPE
ADRFC
ADTPH
ADURQ
ADYFF
ADZKW
AEBTG
AEFQL
AEGNC
AEJHL
AEJRE
AEKMD
AEMSY
AENEX
AEOHA
AEPYU
AESKC
AETLH
AEVLU
AEXYK
AFBBN
AFLOW
AFWTZ
AFZKB
AGDGC
AGJBK
AGMZJ
AGQEE
AGQMX
AGWIL
AGWZB
AGYKE
AHAVH
AHKAY
AHSBF
AHYZX
AIAKS
AIGIU
AIIXL
AILAN
AITGF
AJBLW
AJRNO
AJZVZ
ALMA_UNASSIGNED_HOLDINGS
ALWAN
AMKLP
AMXSW
AMYQR
AOCGG
ARMRJ
AXYYD
AYJHY
B-.
BA0
BDATZ
CAG
COF
CS3
CSCUP
DDRTE
DNIVK
DPUIP
EBLON
EBS
EIOEI
EJD
ESBYG
FERAY
FFXSO
FIGPU
FINBP
FNLPD
FRRFC
FSGXE
FWDCC
GGCAI
GGRSB
GJIRD
GNWQR
GQ6
H13
HF~
HG6
HMJXF
HRMNR
HZ~
IKXTQ
IWAJR
IXD
I~X
I~Z
J-C
J0Z
JBSCW
JZLTJ
KOV
LLZTM
MA-
N2Q
NDZJH
NF0
NPVJJ
NQJWS
O9-
O93
O9G
O9I
O9J
P19
P2P
PF0
PT4
PT5
QOK
QOS
R9I
RHV
ROL
RSV
S16
S1Z
S26
S27
S28
S3B
SAP
SCK
SCLPG
SDH
SEV
SHX
SISQX
SJYHP
SNE
SNPRN
SNX
SOHCF
SOJ
SPISZ
SRMVM
SSLCW
STPWE
SZN
T13
T16
TSG
TSK
TUC
U2A
UG4
UOJIU
UTJUX
UZXMN
VC2
VFIZW
W48
WK8
YLTOR
Z45
Z5O
Z7R
Z7Z
ZMTXR
~02
~A9
AAYXX
ABDBE
ABFSG
ACAOD
ACSTC
ADHKG
AEZWR
AFDZB
AFHIU
AGQPQ
AHPBZ
AHWEU
AIXLP
ATHPR
AYFIA
CITATION
ABRTQ
7S9
L.6
ID FETCH-LOGICAL-c352t-3783c0572a243cd74866bb9bd2638c1d639d199806f62e0e4b23f21e9d634ff73
IEDL.DBID U2A
ISSN 0255-660X
IngestDate Fri Jul 11 06:29:47 EDT 2025
Fri Jul 25 11:03:35 EDT 2025
Thu Apr 24 22:57:32 EDT 2025
Tue Jul 01 02:39:22 EDT 2025
Fri Feb 21 02:37:24 EST 2025
IsPeerReviewed true
IsScholarly true
Issue 1
Keywords Height estimation
Sentinel-1
Remote sensing
Biomass estimation
Rice
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c352t-3783c0572a243cd74866bb9bd2638c1d639d199806f62e0e4b23f21e9d634ff73
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
PQID 2343275732
PQPubID 2043996
PageCount 9
ParticipantIDs proquest_miscellaneous_2400440125
proquest_journals_2343275732
crossref_citationtrail_10_1007_s12524_019_01057_8
crossref_primary_10_1007_s12524_019_01057_8
springer_journals_10_1007_s12524_019_01057_8
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 20200100
2020-01-00
20200101
PublicationDateYYYYMMDD 2020-01-01
PublicationDate_xml – month: 1
  year: 2020
  text: 20200100
PublicationDecade 2020
PublicationPlace New Delhi
PublicationPlace_xml – name: New Delhi
– name: Dordrecht
PublicationTitle Journal of the Indian Society of Remote Sensing
PublicationTitleAbbrev J Indian Soc Remote Sens
PublicationYear 2020
Publisher Springer India
Springer Nature B.V
Publisher_xml – name: Springer India
– name: Springer Nature B.V
References Ancin-Murguzur, Taff, Davids, Tømmervik, Mølmann, Jørgensen (CR1) 2019; 11
Iizumi, Sakuma, Yokozawa, Luo, Challinor, Brown, Sakurai, Yamagata (CR7) 2013; 3
Gao, Shi, Li, Cheng (CR4) 2017; 10
Mostafazadeh-Fard, Jafari, Mousavi, Yazdani (CR14) 2010; 4
Quegan, Yu (CR19) 2001; 39
Lopez-Sanchez, Vicente-Guijalba, Ballester-Berman, Cloude (CR13) 2014; 12
Pulvirenti, Chini, Pierdicca, Boni (CR18) 2015; 54
Sharifi, Amini, Sumantyo, Tateishi (CR22) 2015; 43
Koppe, Gnyp, Hütt, Yao, Miao, Chen, Bareth (CR8) 2013; 21
Pagani, Guarneri, Busetto, Ranghetti, Boschetti, Movedi (CR16) 2019; 168
Sharifi, Hosseingholizadeh (CR24) 2019
Zhang, Yang, Liu, Wang (CR33) 2017; 57
Guan, Li, Rao, Gao, Xie, Hien, Zeng (CR6) 2018; 11
Deng, Chen, Li (CR50) 2018; 21
Pohl, Van Genderen (CR17) 1998; 19
Zhang, Chen, Li, Zhao, Ji, Zhang, Liu (CR32) 2018; 10
Lausch, Bastian, Klotz, Leitão, Jung, Rocchini (CR11) 2018; 9
Nguyen, Clauss, Cao, Naeimi, Kuenzer, Wagner (CR15) 2015; 7
Gao, Zribi, Escorihuela (CR5) 2017; 17
Tripathi, Mishra, Maurya, Singh, Wilson, Singh, Watson, Takahashi (CR26) 2018
Sharifi, Amini, Tateishi (CR23) 2016; 82
Wang, Zhou, Zhu, Dong, Guo (CR28) 2016; 4
CR2
Sharifi, Amini (CR21) 2015; 9
Kuenzer, Knauer (CR9) 2013; 34
Yu, Li, Fu (CR52) 2018; 29
CR25
Woodhouse (CR29) 2017
Song, Chen (CR51) 2018; 21
Turner, Spector, Gardiner, Fladeland, Sterling, Steininger (CR27) 2003; 18
Zhao, Du (CR34) 2016; 113
Kutner, Nachtsheim, Neter, Li (CR10) 1996
Sharifi (CR20) 2018; 9
Yuzugullu, Erten, Hajnsek (CR31) 2016; 10
Erten, Lopez-sanchez, Yuzugullu, Hajnsek (CR3) 2016; 187
1057_CR25
Q Gao (1057_CR5) 2017; 17
E Erten (1057_CR3) 2016; 187
Y Zhang (1057_CR33) 2017; 57
A Sharifi (1057_CR23) 2016; 82
X Deng (1057_CR50) 2018; 21
AD Tripathi (1057_CR26) 2018
1057_CR2
W Zhang (1057_CR32) 2018; 10
L Pulvirenti (1057_CR18) 2015; 54
IH Woodhouse (1057_CR29) 2017
G Gao (1057_CR4) 2017; 10
S Quegan (1057_CR19) 2001; 39
W Koppe (1057_CR8) 2013; 21
MH Kutner (1057_CR10) 1996
B Mostafazadeh-Fard (1057_CR14) 2010; 4
JM Lopez-Sanchez (1057_CR13) 2014; 12
V Pagani (1057_CR16) 2019; 168
T Iizumi (1057_CR7) 2013; 3
Y Yu (1057_CR52) 2018; 29
A Sharifi (1057_CR24) 2019
W Zhao (1057_CR34) 2016; 113
LA Wang (1057_CR28) 2016; 4
K Guan (1057_CR6) 2018; 11
O Yuzugullu (1057_CR31) 2016; 10
FJ Ancin-Murguzur (1057_CR1) 2019; 11
A Sharifi (1057_CR21) 2015; 9
C Kuenzer (1057_CR9) 2013; 34
W Turner (1057_CR27) 2003; 18
A Sharifi (1057_CR22) 2015; 43
D Nguyen (1057_CR15) 2015; 7
C Pohl (1057_CR17) 1998; 19
A Lausch (1057_CR11) 2018; 9
A Sharifi (1057_CR20) 2018; 9
M Song (1057_CR51) 2018; 21
References_xml – year: 1996
  ident: CR10
  publication-title: Applied linear statistical models
– volume: 17
  start-page: 1966
  issue: 9
  year: 2017
  ident: CR5
  article-title: Synergetic use of Sentinel-1 and Sentinel-2 data for soil moisture mapping at 100 m resolution
  publication-title: Sensors
  doi: 10.3390/s17091966
– volume: 4
  start-page: 212
  issue: 3
  year: 2016
  end-page: 219
  ident: CR28
  article-title: Estimation of biomass in wheat using random forest regression algorithm and remote sensing data
  publication-title: The Crop Journal
  doi: 10.1016/j.cj.2016.01.008
– ident: CR2
– volume: 43
  start-page: 339
  issue: 2
  year: 2015
  end-page: 346
  ident: CR22
  article-title: Speckle reduction of PolSAR images in forest regions using fast ICA algorithm
  publication-title: Journal of the Indian Society of Remote Sensing
  doi: 10.1007/s12524-014-0423-3
– volume: 54
  start-page: 1532
  issue: 3
  year: 2015
  end-page: 1544
  ident: CR18
  article-title: Use of SAR data for detecting floodwater in urban and agricultural areas: The role of the interferometric coherence
  publication-title: IEEE Transactions on Geoscience and Remote Sensing
  doi: 10.1109/TGRS.2015.2482001
– volume: 82
  start-page: 41
  issue: 1
  year: 2016
  end-page: 49
  ident: CR23
  article-title: Estimation of forest biomass using multivariate relevance vector regression
  publication-title: Photogrammetric Engineering & Remote Sensing
  doi: 10.14358/PERS.83.1.41
– volume: 19
  start-page: 823
  issue: 5
  year: 1998
  end-page: 854
  ident: CR17
  article-title: Review article multisensor image fusion in remote sensing: Concepts, methods and applications
  publication-title: International Journal of Remote Sensing
  doi: 10.1080/014311698215748
– volume: 9
  start-page: 097695
  issue: 1
  year: 2015
  ident: CR21
  article-title: Forest biomass estimation using synthetic aperture radar polarimetric features
  publication-title: Journal of Applied Remote Sensing
  doi: 10.1117/1.JRS.9.097695
– volume: 21
  start-page: 273
  issue: 4
  year: 2018
  end-page: 287
  ident: CR51
  article-title: An improved knowledge-informed NSGA-II for multi-objective land allocation (MOLA)
  publication-title: Geo-spatial Information Science
  doi: 10.1080/10095020.2018.1489576
– volume: 11
  start-page: 400
  issue: 4
  year: 2019
  ident: CR1
  article-title: Yield estimates by a two-step approach using hyperspectral methods in grasslands at high latitudes
  publication-title: Remote Sensing
  doi: 10.3390/rs11040400
– volume: 187
  start-page: 130
  year: 2016
  end-page: 144
  ident: CR3
  article-title: Remote sensing of environment retrieval of agricultural crop height from space: A comparison of SAR techniques
  publication-title: Remote Sensing of Environment
  doi: 10.1016/j.rse.2016.10.007
– volume: 4
  start-page: 136
  issue: 3
  year: 2010
  ident: CR14
  article-title: Effects of irrigation water management on yield and water use efficiency of rice in cracked paddy soils
  publication-title: Australian Journal of Crop Science
– volume: 39
  start-page: 2373
  issue: 11
  year: 2001
  end-page: 2379
  ident: CR19
  article-title: Filtering of multichannel SAR images
  publication-title: IEEE Transactions on Geoscience and Remote Sensing
  doi: 10.1109/36.964973
– volume: 10
  start-page: 206
  issue: 2
  year: 2018
  ident: CR32
  article-title: Rape ( L.) growth monitoring and mapping based on Radarsat-2 time-series data
  publication-title: Remote Sensing
  doi: 10.3390/rs10020206
– volume: 10
  start-page: 5026
  issue: 11
  year: 2017
  end-page: 5038
  ident: CR4
  article-title: Performance comparison between reflection symmetry metric and product of multilook amplitudes for ship detection in dual-polarization SAR images
  publication-title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  doi: 10.1109/JSTARS.2017.2737543
– ident: CR25
– volume: 113
  start-page: 155
  year: 2016
  end-page: 165
  ident: CR34
  article-title: Learning multiscale and deep representations for classifying remotely sensed imagery
  publication-title: ISPRS Journal of Photogrammetry and Remote Sensing
  doi: 10.1016/j.isprsjprs.2016.01.004
– volume: 11
  start-page: 2238
  issue: 7
  year: 2018
  end-page: 2252
  ident: CR6
  article-title: Mapping paddy rice area and yields over Thai Binh Province in Viet Nam from MODIS, Landsat, and ALOS-2/PALSAR-2
  publication-title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  doi: 10.1109/JSTARS.2018.2834383
– volume: 18
  start-page: 306
  issue: 6
  year: 2003
  end-page: 314
  ident: CR27
  article-title: Remote sensing for biodiversity science and conservation
  publication-title: Trends in Ecology & Evolution
  doi: 10.1016/S0169-5347(03)00070-3
– volume: 10
  start-page: 194
  issue: 1
  year: 2016
  end-page: 204
  ident: CR31
  article-title: Estimation of rice crop height from X-and C-band PolSAR by metamodel-based optimization
  publication-title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  doi: 10.1109/JSTARS.2016.2575362
– volume: 21
  start-page: 45
  issue: 1
  year: 2018
  end-page: 55
  ident: CR50
  article-title: Log-cumulants of the finite mixture model and their application to statistical analysis of fully polarimetric UAVSAR data
  publication-title: Geo-spatial Information
  doi: 10.1080/10095020.2017.1419607
– year: 2018
  ident: CR26
  article-title: Estimates for world population and global food availability for global health
  publication-title: The role of functional food security in global health
  doi: 10.1016/b978-0-12-813148-0.00001-3
– volume: 57
  start-page: 75
  year: 2017
  end-page: 85
  ident: CR33
  article-title: Estimation of rice grain yield from dual-polarization Radarsat-2 SAR data by integrating a rice canopy scattering model and a genetic algorithm
  publication-title: International Journal of Applied Earth Observation and Geoinformation
  doi: 10.1016/j.jag.2016.12.014
– volume: 21
  start-page: 568
  year: 2013
  end-page: 576
  ident: CR8
  article-title: Rice monitoring with multi-temporal and dual-polarimetric TerraSAR-X data
  publication-title: International Journal of Applied Earth Observation and Geoinformation
  doi: 10.1016/j.jag.2012.07.016
– year: 2019
  ident: CR24
  article-title: The effect of rapid population growth on urban expansion and destruction of green space in Tehran from 1972 to 2017
  publication-title: Journal of the Indian Society of Remote Sensing
  doi: 10.1007/s12524-019-00966-y
– year: 2017
  ident: CR29
  publication-title: Introduction to microwave remote sensing
  doi: 10.1201/9781315272573
– volume: 3
  start-page: 1
  issue: 7
  year: 2013
  end-page: 5
  ident: CR7
  article-title: Prediction of seasonal climate-induced variations in global food production
  publication-title: Nature Climate Change
  doi: 10.1038/nclimate1945
– volume: 34
  start-page: 2101
  issue: 6
  year: 2013
  end-page: 2139
  ident: CR9
  article-title: Remote sensing of rice crop areas
  publication-title: International Journal of Remote Sensing
  doi: 10.1080/01431161.2012.738946
– volume: 7
  start-page: 15868
  issue: 12
  year: 2015
  end-page: 15893
  ident: CR15
  article-title: Mapping rice seasonality in the Mekong Delta with multi-year Envisat ASAR WSM data
  publication-title: Remote Sensing
  doi: 10.3390/rs71215808
– volume: 12
  start-page: 249
  issue: 2
  year: 2014
  end-page: 253
  ident: CR13
  article-title: Influence of incidence angle on the coherent copolar polarimetric response of rice at X-band
  publication-title: IEEE Geoscience and Remote Sensing Letters
  doi: 10.1109/LGRS.2014.2334371
– volume: 9
  start-page: 1799
  issue: 8
  year: 2018
  end-page: 1809
  ident: CR11
  article-title: Understanding and assessing vegetation health by in situ species and remote-sensing approaches
  publication-title: Methods in Ecology and Evolution
  doi: 10.1111/2041-210X.13025
– volume: 29
  start-page: 1407
  issue: 5
  year: 2018
  end-page: 1414
  ident: CR52
  article-title: Forest type identification by random forest classification combined with SPOT and multitemporal SAR data
  publication-title: Journal of ForestryResearch
– volume: 9
  start-page: 559
  issue: 6
  year: 2018
  end-page: 568
  ident: CR20
  article-title: Estimation of biophysical parameters in wheat crops in Golestan province using ultra-high resolution images
  publication-title: Remote Sensing Letters
  doi: 10.1080/2150704X.2018.1452058
– volume: 168
  start-page: 181
  year: 2019
  end-page: 190
  ident: CR16
  article-title: A high-resolution, integrated system for rice yield forecasting at district level
  publication-title: Agricultural Systems
  doi: 10.1016/j.agsy.2018.05.007
– volume: 9
  start-page: 1799
  issue: 8
  year: 2018
  ident: 1057_CR11
  publication-title: Methods in Ecology and Evolution
  doi: 10.1111/2041-210X.13025
– volume: 7
  start-page: 15868
  issue: 12
  year: 2015
  ident: 1057_CR15
  publication-title: Remote Sensing
  doi: 10.3390/rs71215808
– volume: 21
  start-page: 45
  issue: 1
  year: 2018
  ident: 1057_CR50
  publication-title: Geo-spatial Information
  doi: 10.1080/10095020.2017.1419607
– volume: 4
  start-page: 212
  issue: 3
  year: 2016
  ident: 1057_CR28
  publication-title: The Crop Journal
  doi: 10.1016/j.cj.2016.01.008
– volume: 4
  start-page: 136
  issue: 3
  year: 2010
  ident: 1057_CR14
  publication-title: Australian Journal of Crop Science
– volume: 17
  start-page: 1966
  issue: 9
  year: 2017
  ident: 1057_CR5
  publication-title: Sensors
  doi: 10.3390/s17091966
– volume: 113
  start-page: 155
  year: 2016
  ident: 1057_CR34
  publication-title: ISPRS Journal of Photogrammetry and Remote Sensing
  doi: 10.1016/j.isprsjprs.2016.01.004
– volume: 10
  start-page: 206
  issue: 2
  year: 2018
  ident: 1057_CR32
  publication-title: Remote Sensing
  doi: 10.3390/rs10020206
– volume: 11
  start-page: 400
  issue: 4
  year: 2019
  ident: 1057_CR1
  publication-title: Remote Sensing
  doi: 10.3390/rs11040400
– volume: 43
  start-page: 339
  issue: 2
  year: 2015
  ident: 1057_CR22
  publication-title: Journal of the Indian Society of Remote Sensing
  doi: 10.1007/s12524-014-0423-3
– volume: 187
  start-page: 130
  year: 2016
  ident: 1057_CR3
  publication-title: Remote Sensing of Environment
  doi: 10.1016/j.rse.2016.10.007
– volume: 3
  start-page: 1
  issue: 7
  year: 2013
  ident: 1057_CR7
  publication-title: Nature Climate Change
  doi: 10.1038/nclimate1945
– volume: 29
  start-page: 1407
  issue: 5
  year: 2018
  ident: 1057_CR52
  publication-title: Journal of ForestryResearch
– volume: 10
  start-page: 194
  issue: 1
  year: 2016
  ident: 1057_CR31
  publication-title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  doi: 10.1109/JSTARS.2016.2575362
– volume: 9
  start-page: 559
  issue: 6
  year: 2018
  ident: 1057_CR20
  publication-title: Remote Sensing Letters
  doi: 10.1080/2150704X.2018.1452058
– volume: 21
  start-page: 273
  issue: 4
  year: 2018
  ident: 1057_CR51
  publication-title: Geo-spatial Information Science
  doi: 10.1080/10095020.2018.1489576
– volume: 39
  start-page: 2373
  issue: 11
  year: 2001
  ident: 1057_CR19
  publication-title: IEEE Transactions on Geoscience and Remote Sensing
  doi: 10.1109/36.964973
– volume: 21
  start-page: 568
  year: 2013
  ident: 1057_CR8
  publication-title: International Journal of Applied Earth Observation and Geoinformation
  doi: 10.1016/j.jag.2012.07.016
– volume: 19
  start-page: 823
  issue: 5
  year: 1998
  ident: 1057_CR17
  publication-title: International Journal of Remote Sensing
  doi: 10.1080/014311698215748
– ident: 1057_CR25
– ident: 1057_CR2
– volume: 82
  start-page: 41
  issue: 1
  year: 2016
  ident: 1057_CR23
  publication-title: Photogrammetric Engineering & Remote Sensing
  doi: 10.14358/PERS.83.1.41
– volume: 11
  start-page: 2238
  issue: 7
  year: 2018
  ident: 1057_CR6
  publication-title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  doi: 10.1109/JSTARS.2018.2834383
– volume: 34
  start-page: 2101
  issue: 6
  year: 2013
  ident: 1057_CR9
  publication-title: International Journal of Remote Sensing
  doi: 10.1080/01431161.2012.738946
– volume: 10
  start-page: 5026
  issue: 11
  year: 2017
  ident: 1057_CR4
  publication-title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  doi: 10.1109/JSTARS.2017.2737543
– volume: 18
  start-page: 306
  issue: 6
  year: 2003
  ident: 1057_CR27
  publication-title: Trends in Ecology & Evolution
  doi: 10.1016/S0169-5347(03)00070-3
– volume-title: Introduction to microwave remote sensing
  year: 2017
  ident: 1057_CR29
  doi: 10.1201/9781315272573
– volume: 12
  start-page: 249
  issue: 2
  year: 2014
  ident: 1057_CR13
  publication-title: IEEE Geoscience and Remote Sensing Letters
  doi: 10.1109/LGRS.2014.2334371
– volume-title: Applied linear statistical models
  year: 1996
  ident: 1057_CR10
– volume: 57
  start-page: 75
  year: 2017
  ident: 1057_CR33
  publication-title: International Journal of Applied Earth Observation and Geoinformation
  doi: 10.1016/j.jag.2016.12.014
– volume: 168
  start-page: 181
  year: 2019
  ident: 1057_CR16
  publication-title: Agricultural Systems
  doi: 10.1016/j.agsy.2018.05.007
– volume: 9
  start-page: 097695
  issue: 1
  year: 2015
  ident: 1057_CR21
  publication-title: Journal of Applied Remote Sensing
  doi: 10.1117/1.JRS.9.097695
– volume: 54
  start-page: 1532
  issue: 3
  year: 2015
  ident: 1057_CR18
  publication-title: IEEE Transactions on Geoscience and Remote Sensing
  doi: 10.1109/TGRS.2015.2482001
– volume-title: The role of functional food security in global health
  year: 2018
  ident: 1057_CR26
  doi: 10.1016/b978-0-12-813148-0.00001-3
– year: 2019
  ident: 1057_CR24
  publication-title: Journal of the Indian Society of Remote Sensing
  doi: 10.1007/s12524-019-00966-y
SSID ssj0064512
ssj0001852324
Score 2.4162505
Snippet Crops monitoring is a challengeable subject that radar images can help it. The applicability of Sentinel-1 SAR data with dual polarization provided a splendid...
SourceID proquest
crossref
springer
SourceType Aggregation Database
Enrichment Source
Index Database
Publisher
StartPage 11
SubjectTerms Biomass
Cereal crops
Correlation coefficient
Correlation coefficients
crops
Dual polarization radar
Earth and Environmental Science
Earth Sciences
Iran
Measurement methods
monitoring
Parameter estimation
radar
Radar imaging
Regression analysis
remote sensing
Remote Sensing/Photogrammetry
Research Article
Rice
Root-mean-square errors
Support vector machines
Synthetic aperture radar
Title Application of Sentinel-1 Data to Estimate Height and Biomass of Rice Crop in Astaneh-ye Ashrafiyeh, Iran
URI https://link.springer.com/article/10.1007/s12524-019-01057-8
https://www.proquest.com/docview/2343275732
https://www.proquest.com/docview/2400440125
Volume 48
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1Lb9QwEB5Be4ED4ikWSmUkbjRS4jhOcgxlywKCA7BoOUV2PNFGqpJqkz303zPjTRqBAIlbFD-ijD3jb54GeFVhiipmq411pKDIEAPaNybIjXZc4BJdztnInz7r1Vp92CSbMSmsn6LdJ5ekl9RzsptMJEdMcHwPoYwguw3HCevutIvXspgtK1kifQ3ygzzWKvE-TwbPgdbhZkyd-fOcvx5PM-b8zU3qT5-L-3BvhI2iOKzzA7iF7UO4-73p94e3_SNoitkXLbpafOU4oBYvg0i8NYMRQyeWxM-EUFGsvEFUmNaJNw1HCPU84gsJDXG-665E04qCYSNug2ukx-3O1M01bs_EezrbHsP6YvntfBWMFykEFeGrgYRIFlf0e9JIFVcuVZnW1ubWSeK-KnKEUhzn2oW61hJDVFbGtYwwpxZV12n8BI7arsWnIGwcV5Ighg6lUVY5Q3iGhK3GKMfM6nQB0US_shqrjPNlF5flXB-ZaV4SzUtP8zJbwOubMVeHGhv_7H0yLUs58ltfSs6PTZM0lgt4edNMnMLuD6JWt6c-yt-vTRMu4GxaznmKv3_x2f91fw53JCvl3k5zAkfDbo8vCLkM9hSOi3c_Pi5P_Yb9CRWR368
linkProvider Springer Nature
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1Lb9QwEB5BOQCHiqdYWsBI3GikxHGc5LiUVltoe4Au2ltkxxNtpCqpNtlD_z0z3qQRCJC4RfHYUcae8ed5GeBDiSmqmK021tEBRYYY0LoxQW604wKX6HLORr641Iul-rJKVkNSWDdGu48uSa-pp2Q3mUiOmOD4HkIZQXYfHhAYyDiQaynnk2UlS6SvQb7Tx1ol3ufJ4DnQOlwNqTN_HvPX7WnCnL-5Sf3uc_oE9gfYKOa7eX4K97B5Bo9_1N1297Z7DvV88kWLthLfOQ6owesgEp9Nb0TfihOSZ0KoKBbeICpM48SnmiOEOu7xjZSGON60N6JuxJxhI66DW6TH9cZU9S2uj8QZ7W0vYHl6cnW8CIaLFIKS8FVPSiSLS_o9aaSKS5eqTGtrc-skSV8ZOUIpjnPtQl1piSEqK-NKRphTi6qqNH4Je03b4CsQNo5LSRBDh9Ioq5whPEPKVmOUY2Z1OoNo5F9RDlXG-bKL62Kqj8w8L4jnhed5kc3g412fm12NjX9SH47TUgzy1hWS82PTJI3lDN7fNZOksPuDuNVuiUb5-7VpwBkcjdM5DfH3L77-P_J38HBxdXFenJ9dfj2AR5IP6N5mcwh7_WaLbwjF9PatX7Q_AcGD4Q4
linkToPdf http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3db9MwED_BkBA8ID5FYYCReGPREsdxkseyrer4mBBQ1LfIji9qpCmp2vRh_z13TroAAiTeovjsKGff-ef7MsCbElNUMVttrKMDigwxoHVjgtxoxwUu0eWcjfzpQs8X6v0yWf6Uxe-j3fcuyT6ngas0Nd3x2lXHY-KbTCRHT3CsDyGOILsJt0gdR7yuF3I6WlmyRPp65L1u1irx_k8G0oHW4XJIo_nzmL9uVSP-_M1l6nei2X24N0BIMe3n_AHcwOYh3P1eb3f92-0jqKejX1q0lfjKMUENXgaRODWdEV0rzki2Ca2imHvjqDCNE-9qjhbaco8vpEDEyaZdi7oRU4aQuAqukB5XG1PVV7g6Eue0zz2Gxezs28k8GC5VCErCWh0plCwu6fekkSouXaoyra3NrZMkiWXkCLE4zrsLdaUlhqisjCsZYU4tqqrS-AkcNG2DT0HYOC4lwQ0dSqOscoawDSlejVGOmdXpBKI9_4pyqDjOF19cFmOtZOZ5QTwvPM-LbAJvr_us-3ob_6Q-3E9LMcjetpCcK5smaSwn8Pq6maSGXSHErXZHNMrftU0DTuBoP53jEH__4rP_I38Ftz-fzoqP5xcfnsMdyWd1b745hINus8MXBGg6-9Kv2R8sbOVK
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=Application+of+Sentinel-1+Data+to+Estimate+Height+and+Biomass+of+Rice+Crop+in+Astaneh-ye+Ashrafiyeh%2C+Iran&rft.jtitle=Photonirvachak+%28Dehra+Dun%29&rft.au=Shar%C4%ABf%C4%AB%2C+%CA%BBAl%C4%AB+Riz%CC%A4%C4%81&rft.au=Hosseingholizadeh%2C+Mohammad&rft.date=2020-01-01&rft.issn=0255-660X&rft.volume=48&rft.issue=1+p.11-19&rft.spage=11&rft.epage=19&rft_id=info:doi/10.1007%2Fs12524-019-01057-8&rft.externalDBID=NO_FULL_TEXT
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0255-660X&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0255-660X&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0255-660X&client=summon