Water Quality Retrieval from PRISMA Hyperspectral Images: First Experience in a Turbid Lake and Comparison with Sentinel-2

A new era of spaceborne hyperspectral imaging has just begun with the recent availability of data from PRISMA (PRecursore IperSpettrale della Missione Applicativa) launched by the Italian space agency (ASI). There has been pre-launch optimism that the wealth of spectral information offered by PRISMA...

Full description

Saved in:
Bibliographic Details
Published inRemote sensing (Basel, Switzerland) Vol. 12; no. 23; p. 3984
Main Authors Niroumand-Jadidi, Milad, Bovolo, Francesca, Bruzzone, Lorenzo
Format Journal Article
LanguageEnglish
Published MDPI AG 01.12.2020
Subjects
Online AccessGet full text

Cover

Loading…
Abstract A new era of spaceborne hyperspectral imaging has just begun with the recent availability of data from PRISMA (PRecursore IperSpettrale della Missione Applicativa) launched by the Italian space agency (ASI). There has been pre-launch optimism that the wealth of spectral information offered by PRISMA can contribute to a variety of aquatic science and management applications. Here, we examine the potential of PRISMA level 2D images in retrieving standard water quality parameters, including total suspended matter (TSM), chlorophyll-a (Chl-a), and colored dissolved organic matter (CDOM) in a turbid lake (Lake Trasimeno, Italy). We perform consistency analyses among the aquatic products (remote sensing reflectance (Rrs) and constituents) derived from PRISMA and those from Sentinel-2. The consistency analyses are expanded to synthesized Sentinel-2 data as well. By spectral downsampling of the PRISMA images, we better isolate the impact of spectral resolution in retrieving the constituents. The retrieval of constituents from both PRISMA and Sentinel-2 images is built upon inverting the radiative transfer model implemented in the Water Color Simulator (WASI) processor. The inversion involves a parameter (gdd) to compensate for atmospheric and sun-glint artifacts. A strong agreement is indicated for the cross-sensor comparison of Rrs products at different wavelengths (average R ≈ 0.87). However, the Rrs of PRISMA at shorter wavelengths (<500 nm) is slightly overestimated with respect to Sentinel-2. This is in line with the estimates of gdd through the inversion that suggests an underestimated atmospheric path radiance of PRISMA level 2D products compared to the atmospherically corrected Sentinel-2 data. The results indicate the high potential of PRISMA level 2D imagery in mapping water quality parameters in Lake Trasimeno. The PRISMA-based retrievals agree well with those of Sentinel-2, particularly for TSM.
AbstractList A new era of spaceborne hyperspectral imaging has just begun with the recent availability of data from PRISMA (PRecursore IperSpettrale della Missione Applicativa) launched by the Italian space agency (ASI). There has been pre-launch optimism that the wealth of spectral information offered by PRISMA can contribute to a variety of aquatic science and management applications. Here, we examine the potential of PRISMA level 2D images in retrieving standard water quality parameters, including total suspended matter (TSM), chlorophyll-a (Chl-a), and colored dissolved organic matter (CDOM) in a turbid lake (Lake Trasimeno, Italy). We perform consistency analyses among the aquatic products (remote sensing reflectance (Rrs) and constituents) derived from PRISMA and those from Sentinel-2. The consistency analyses are expanded to synthesized Sentinel-2 data as well. By spectral downsampling of the PRISMA images, we better isolate the impact of spectral resolution in retrieving the constituents. The retrieval of constituents from both PRISMA and Sentinel-2 images is built upon inverting the radiative transfer model implemented in the Water Color Simulator (WASI) processor. The inversion involves a parameter (gdd) to compensate for atmospheric and sun-glint artifacts. A strong agreement is indicated for the cross-sensor comparison of Rrs products at different wavelengths (average R ≈ 0.87). However, the Rrs of PRISMA at shorter wavelengths (<500 nm) is slightly overestimated with respect to Sentinel-2. This is in line with the estimates of gdd through the inversion that suggests an underestimated atmospheric path radiance of PRISMA level 2D products compared to the atmospherically corrected Sentinel-2 data. The results indicate the high potential of PRISMA level 2D imagery in mapping water quality parameters in Lake Trasimeno. The PRISMA-based retrievals agree well with those of Sentinel-2, particularly for TSM.
A new era of spaceborne hyperspectral imaging has just begun with the recent availability of data from PRISMA (PRecursore IperSpettrale della Missione Applicativa) launched by the Italian space agency (ASI). There has been pre-launch optimism that the wealth of spectral information offered by PRISMA can contribute to a variety of aquatic science and management applications. Here, we examine the potential of PRISMA level 2D images in retrieving standard water quality parameters, including total suspended matter (TSM), chlorophyll-a (Chl-a), and colored dissolved organic matter (CDOM) in a turbid lake (Lake Trasimeno, Italy). We perform consistency analyses among the aquatic products (remote sensing reflectance (Rᵣₛ) and constituents) derived from PRISMA and those from Sentinel-2. The consistency analyses are expanded to synthesized Sentinel-2 data as well. By spectral downsampling of the PRISMA images, we better isolate the impact of spectral resolution in retrieving the constituents. The retrieval of constituents from both PRISMA and Sentinel-2 images is built upon inverting the radiative transfer model implemented in the Water Color Simulator (WASI) processor. The inversion involves a parameter (gdd) to compensate for atmospheric and sun-glint artifacts. A strong agreement is indicated for the cross-sensor comparison of Rᵣₛ products at different wavelengths (average R ≍ 0.87). However, the Rᵣₛ of PRISMA at shorter wavelengths (<500 nm) is slightly overestimated with respect to Sentinel-2. This is in line with the estimates of gdd through the inversion that suggests an underestimated atmospheric path radiance of PRISMA level 2D products compared to the atmospherically corrected Sentinel-2 data. The results indicate the high potential of PRISMA level 2D imagery in mapping water quality parameters in Lake Trasimeno. The PRISMA-based retrievals agree well with those of Sentinel-2, particularly for TSM.
Author Bruzzone, Lorenzo
Niroumand-Jadidi, Milad
Bovolo, Francesca
Author_xml – sequence: 1
  givenname: Milad
  orcidid: 0000-0002-9432-3032
  surname: Niroumand-Jadidi
  fullname: Niroumand-Jadidi, Milad
– sequence: 2
  givenname: Francesca
  surname: Bovolo
  fullname: Bovolo, Francesca
– sequence: 3
  givenname: Lorenzo
  orcidid: 0000-0002-6036-459X
  surname: Bruzzone
  fullname: Bruzzone, Lorenzo
BookMark eNptUctuFDEQtFCQCEkufIGPCGnAY3te3KJVQlZalJAEcbR67HZwmLEH2wssX49hiUCIvvSjqkut6qfkwAePhDyr2UshBvYqpprzUvXyETnkrOOV5AM_-Kt-Qk5SumclhKgHJg_J9w-QMdJ3W5hc3tFrzNHhF5iojWGmV9frm7en9GK3YEwL6hwLsp7hDtNreu5iyvTsW8Eceo3UeQr0dhtHZ-gGPiEFb-gqzAtEl4KnX13-SG_QZ-dxqvgxeWxhSnjyOx-R9-dnt6uLanP5Zr063VRatG2uOisaJq0dWxBybKXoR44d1tz2drCNwIY1QozctNBpw7qhF70xUg68HvkouTgi672uCXCvluhmiDsVwKlfgxDvFMTs9ITK9Ka3NdOCjUaKVoIsZvZQeq470eui9XyvtcTweYspq9kljdMEHsM2Kd7UNWe8bdtCZXuqjiGliFZplyG74IuLblI1Uz-_pv58ray8-Gfl4dr_kH8ALPyYmQ
CitedBy_id crossref_primary_10_1109_JSTARS_2024_3502796
crossref_primary_10_3390_rs14153652
crossref_primary_10_3390_ijerph191912583
crossref_primary_10_3390_rs15092268
crossref_primary_10_3390_rs13122381
crossref_primary_10_3390_w13223286
crossref_primary_10_3390_app132011217
crossref_primary_10_1016_j_ecoinf_2023_102205
crossref_primary_10_1080_15481603_2021_1969630
crossref_primary_10_3390_rs14133083
crossref_primary_10_3390_resources11020008
crossref_primary_10_1016_j_isprsjprs_2022_08_009
crossref_primary_10_3390_rs16101704
crossref_primary_10_3390_jmse13020246
crossref_primary_10_1016_j_ejrs_2022_04_001
crossref_primary_10_3390_rs16122149
crossref_primary_10_3389_frsen_2022_986013
crossref_primary_10_3390_land11112070
crossref_primary_10_3390_rs14246284
crossref_primary_10_3390_app12157501
crossref_primary_10_3390_rs13193952
crossref_primary_10_1007_s10661_023_11497_y
crossref_primary_10_3390_rs14184596
crossref_primary_10_3390_rs13050888
crossref_primary_10_3390_rs15051390
crossref_primary_10_1016_j_asr_2022_09_047
crossref_primary_10_3390_su14042221
crossref_primary_10_1007_s12517_022_10494_8
crossref_primary_10_1016_j_oregeorev_2022_105244
crossref_primary_10_1080_01431161_2021_1931541
crossref_primary_10_3390_rs15235505
crossref_primary_10_1016_j_rsase_2023_100955
crossref_primary_10_1364_OE_523813
crossref_primary_10_3390_su132112144
crossref_primary_10_1016_j_sciaf_2023_e01877
crossref_primary_10_3390_rs16183504
crossref_primary_10_3390_rs15082163
crossref_primary_10_1016_j_optlaseng_2022_107256
crossref_primary_10_1016_j_asr_2024_12_065
crossref_primary_10_1016_j_rse_2024_114051
crossref_primary_10_1002_ldr_5414
crossref_primary_10_3390_rs15082117
crossref_primary_10_1016_j_rse_2022_113045
crossref_primary_10_1016_j_rse_2024_114379
crossref_primary_10_1109_MGRS_2024_3509139
crossref_primary_10_1080_01431161_2023_2275324
crossref_primary_10_3390_rs16173235
crossref_primary_10_3390_rs15235578
crossref_primary_10_3390_rs16224196
crossref_primary_10_1109_JSTARS_2023_3266929
crossref_primary_10_1016_j_isprsjprs_2024_07_003
crossref_primary_10_24927_rce2022_053
crossref_primary_10_1016_j_isprsjprs_2023_09_019
crossref_primary_10_3390_rs14133077
crossref_primary_10_3390_rs13245112
crossref_primary_10_1029_2020RG000728
crossref_primary_10_1016_j_jaridenv_2023_105024
crossref_primary_10_1088_1742_6596_2255_1_012015
crossref_primary_10_3390_smartcities8020051
crossref_primary_10_3390_rs13101999
crossref_primary_10_3390_rs15051299
crossref_primary_10_3390_rs15102619
crossref_primary_10_3390_rs14051264
crossref_primary_10_3390_rs14051267
crossref_primary_10_3390_rs15092242
Cites_doi 10.3390/rs8080640
10.1016/j.rse.2015.02.007
10.1016/j.isprsjprs.2013.06.008
10.1007/s10712-018-9476-0
10.1016/j.pocean.2013.12.008
10.1016/j.rse.2004.11.009
10.3390/rs9101070
10.1016/j.marpolbul.2016.02.076
10.3390/rs8060497
10.3390/rs12142247
10.1016/j.rse.2015.05.014
10.1016/j.rse.2014.11.017
10.1016/j.rse.2007.12.014
10.1364/AO.32.003531
10.3390/w12010284
10.5194/isprsarchives-XLI-B8-361-2016
10.1016/B978-0-12-804644-9.00001-X
10.1364/OE.26.007404
10.1016/j.rse.2018.09.022
10.3390/rs5126812
10.1016/j.rse.2014.04.034
10.1109/TGRS.2019.2933251
10.1016/j.hal.2016.01.005
10.1364/AO.36.008710
10.3390/rs11010064
10.1016/j.rse.2019.03.018
10.1080/01431168108948342
10.1109/TGRS.2004.827260
10.1364/AO.51.001407
10.1016/j.rse.2020.112091
10.1029/2017WR022437
10.3390/rs70708830
10.3390/s19163609
10.3390/s20030742
10.1016/j.rse.2014.05.020
10.1080/01431160500104111
10.4319/lo.1990.35.8.1657
10.3390/rs11121469
10.3390/ijgi6120383
10.3390/rs8110941
10.3390/rs11232883
10.1016/j.watres.2011.11.068
10.3390/rs12152381
10.3390/w12010169
10.3390/rs10020157
10.1038/s41598-019-54453-y
10.3390/s16081298
10.1175/BAMS-D-18-0056.1
10.1080/01431161.2018.1506951
10.1016/j.rse.2006.12.017
10.1016/j.cageo.2004.03.005
10.3390/rs71114781
10.3390/rs10070982
10.1109/TGRS.2003.815999
10.1016/j.rse.2015.05.003
10.3390/rs11030262
10.1016/j.rse.2020.111900
10.3390/s20164553
10.1109/IGARSS.2018.8518384
10.1016/j.rse.2016.01.007
10.3390/jmse8020143
10.1016/j.rse.2018.07.014
10.1016/j.rse.2015.05.022
10.1016/j.rse.2008.12.003
10.14358/PERS.69.6.695
10.1016/j.cageo.2013.07.022
10.1364/OE.11.002873
10.1016/j.rse.2015.01.025
ContentType Journal Article
DBID AAYXX
CITATION
7S9
L.6
DOA
DOI 10.3390/rs12233984
DatabaseName CrossRef
AGRICOLA
AGRICOLA - Academic
DOAJ Directory of Open Access Journals
DatabaseTitle CrossRef
AGRICOLA
AGRICOLA - Academic
DatabaseTitleList CrossRef
AGRICOLA

Database_xml – sequence: 1
  dbid: DOA
  name: DOAJ Directory of Open Access Journals
  url: https://www.doaj.org/
  sourceTypes: Open Website
DeliveryMethod fulltext_linktorsrc
Discipline Geography
EISSN 2072-4292
ExternalDocumentID oai_doaj_org_article_d8d8f10c30bd4364a49848ac302c738c
10_3390_rs12233984
GeographicLocations Italy
GeographicLocations_xml – name: Italy
GroupedDBID 29P
2WC
2XV
5VS
8FE
8FG
8FH
AADQD
AAHBH
AAYXX
ABDBF
ABJCF
ACUHS
ADBBV
ADMLS
AENEX
AFKRA
AFZYC
ALMA_UNASSIGNED_HOLDINGS
ARAPS
BCNDV
BENPR
BGLVJ
BHPHI
BKSAR
CCPQU
CITATION
E3Z
ESX
FRP
GROUPED_DOAJ
HCIFZ
I-F
IAO
ITC
KQ8
L6V
LK5
M7R
M7S
MODMG
M~E
OK1
P62
PCBAR
PHGZM
PHGZT
PIMPY
PROAC
PTHSS
TR2
TUS
7S9
L.6
PQGLB
PUEGO
ID FETCH-LOGICAL-c366t-7f3504ffb6a34b6438b2e7e12f8f9f53e50533b2d6a7cd079838dd44921b2b423
IEDL.DBID DOA
ISSN 2072-4292
IngestDate Wed Aug 27 01:28:05 EDT 2025
Fri Jul 11 10:57:55 EDT 2025
Tue Jul 01 01:58:23 EDT 2025
Thu Apr 24 23:08:47 EDT 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 23
Language English
License https://creativecommons.org/licenses/by/4.0
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c366t-7f3504ffb6a34b6438b2e7e12f8f9f53e50533b2d6a7cd079838dd44921b2b423
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ORCID 0000-0002-9432-3032
0000-0002-6036-459X
OpenAccessLink https://doaj.org/article/d8d8f10c30bd4364a49848ac302c738c
PQID 2511202666
PQPubID 24069
ParticipantIDs doaj_primary_oai_doaj_org_article_d8d8f10c30bd4364a49848ac302c738c
proquest_miscellaneous_2511202666
crossref_citationtrail_10_3390_rs12233984
crossref_primary_10_3390_rs12233984
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 2020-12-01
PublicationDateYYYYMMDD 2020-12-01
PublicationDate_xml – month: 12
  year: 2020
  text: 2020-12-01
  day: 01
PublicationDecade 2020
PublicationTitle Remote sensing (Basel, Switzerland)
PublicationYear 2020
Publisher MDPI AG
Publisher_xml – name: MDPI AG
References ref_50
Vitti (ref_19) 2018; 218
ref_58
ref_13
ref_57
ref_12
ref_54
Guanter (ref_32) 2015; 7
ref_51
Bruzzone (ref_55) 2018; Volume 10789
Seegers (ref_79) 2018; 26
ref_18
Xi (ref_43) 2015; 7
Mishra (ref_10) 2019; 9
Barnsley (ref_34) 2004; 42
Moses (ref_41) 2012; 46
Ungar (ref_33) 2003; 41
Kutser (ref_15) 2015; 157
ref_61
ref_60
Gege (ref_59) 2014; 62
ref_25
ref_68
ref_23
ref_67
ref_66
ref_64
Werdell (ref_37) 2019; 100
Gege (ref_76) 2012; 51
Slonecker (ref_16) 2016; 107
Bovolo (ref_22) 2020; 251
ref_28
ref_27
Lyzenga (ref_20) 1981; 2
Gower (ref_6) 2014; 123
Vanhellemont (ref_63) 2015; 161
ref_70
Pu (ref_48) 2013; 83
Sheffield (ref_2) 2018; 54
Bovolo (ref_56) 2019; 57
Giardino (ref_62) 2015; 157
Harvey (ref_3) 2015; 158
Lee (ref_47) 2007; 1
ref_35
Palacios (ref_42) 2015; 167
ref_78
Kutser (ref_14) 2005; 94
Hu (ref_45) 2015; 167
ref_31
ref_75
ref_30
ref_74
Warren (ref_65) 2019; 225
Pope (ref_71) 1997; 36
Albert (ref_69) 2003; 11
Goetz (ref_29) 2009; 113
Devred (ref_36) 2013; 5
ref_80
Giardino (ref_46) 2007; 109
Stumpf (ref_11) 2016; 54
Schweizer (ref_17) 2005; 26
Wicaksono (ref_26) 2018; 39
Brando (ref_53) 2009; 113
Kou (ref_72) 1993; 32
Ritchie (ref_1) 2003; 69
Hedley (ref_21) 2018; 216
Morel (ref_73) 1974; 14
Olmanson (ref_24) 2016; 185
Gregg (ref_77) 1990; 35
Gege (ref_52) 2004; 30
ref_49
ref_9
Bell (ref_44) 2015; 167
ref_8
Kudela (ref_40) 2015; 167
ref_5
ref_4
ref_7
Vandermeulen (ref_39) 2020; 247
Giardino (ref_38) 2019; 40
References_xml – ident: ref_78
– ident: ref_74
– ident: ref_7
  doi: 10.3390/rs8080640
– volume: 161
  start-page: 89
  year: 2015
  ident: ref_63
  article-title: Advantages of high quality SWIR bands for ocean colour processing: Examples from Landsat-8
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2015.02.007
– volume: 83
  start-page: 116
  year: 2013
  ident: ref_48
  article-title: A protocol for improving mapping and assessing of seagrass abundance along the West Central Coast of Florida using Landsat TM and EO-1 ALI/Hyperion images
  publication-title: ISPRS J. Photogramm. Remote Sens.
  doi: 10.1016/j.isprsjprs.2013.06.008
– ident: ref_51
– volume: 40
  start-page: 401
  year: 2019
  ident: ref_38
  article-title: Imaging Spectrometry of Inland and Coastal Waters: State of the Art, Achievements and Perspectives
  publication-title: Surv. Geophys.
  doi: 10.1007/s10712-018-9476-0
– ident: ref_68
– volume: 123
  start-page: 123
  year: 2014
  ident: ref_6
  article-title: A review of ocean color remote sensing methods and statistical techniques for the detection, mapping and analysis of phytoplankton blooms in coastal and open oceans
  publication-title: Prog. Oceanogr.
  doi: 10.1016/j.pocean.2013.12.008
– volume: 94
  start-page: 535
  year: 2005
  ident: ref_14
  article-title: Mapping lake CDOM by satellite remote sensing
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2004.11.009
– volume: Volume 10789
  start-page: 23
  year: 2018
  ident: ref_55
  article-title: A novel approach for bathymetry of shallow rivers based on spectral magnitude and shape predictors using stepwise regression
  publication-title: Proceedings of the Image and Signal Processing for Remote Sensing XXIV
– ident: ref_23
  doi: 10.3390/rs9101070
– volume: 107
  start-page: 518
  year: 2016
  ident: ref_16
  article-title: The new Landsat 8 potential for remote sensing of colored dissolved organic matter (CDOM)
  publication-title: Mar. Pollut. Bull.
  doi: 10.1016/j.marpolbul.2016.02.076
– ident: ref_8
  doi: 10.3390/rs8060497
– volume: 1
  start-page: 1
  year: 2007
  ident: ref_47
  article-title: Water and bottom properties of a coastal environment derived from Hyperion data measured from the EO-1 spacecraft platform
  publication-title: J. Appl. Remote Sens.
– ident: ref_31
  doi: 10.3390/rs12142247
– volume: 167
  start-page: 269
  year: 2015
  ident: ref_42
  article-title: Remote sensing of phytoplankton functional types in the coastal ocean from the HyspIRI Preparatory Flight Campaign
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2015.05.014
– volume: 158
  start-page: 417
  year: 2015
  ident: ref_3
  article-title: Satellite-based water quality monitoring for improved spatial and temporal retrieval of chlorophyll-a in coastal waters
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2014.11.017
– volume: 113
  start-page: S5
  year: 2009
  ident: ref_29
  article-title: Three decades of hyperspectral remote sensing of the Earth: A personal view
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2007.12.014
– volume: 32
  start-page: 3531
  year: 1993
  ident: ref_72
  article-title: Refractive indices of water and ice in the 065- to 25-μm spectral range
  publication-title: Appl. Opt.
  doi: 10.1364/AO.32.003531
– ident: ref_9
  doi: 10.3390/w12010284
– ident: ref_54
  doi: 10.5194/isprsarchives-XLI-B8-361-2016
– ident: ref_60
  doi: 10.1016/B978-0-12-804644-9.00001-X
– volume: 26
  start-page: 7404
  year: 2018
  ident: ref_79
  article-title: Performance metrics for the assessment of satellite data products: An ocean color case study
  publication-title: Opt. Express
  doi: 10.1364/OE.26.007404
– volume: 218
  start-page: 132
  year: 2018
  ident: ref_19
  article-title: Multiple Optimal Depth Predictors Analysis (MODPA) for river bathymetry: Findings from spectroradiometry, simulations, and satellite imagery
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2018.09.022
– volume: 14
  start-page: 1
  year: 1974
  ident: ref_73
  article-title: Optical Properties of Pure Water and Pure Sea Water
  publication-title: Opt. Asp. Oceanogr.
– volume: 5
  start-page: 6812
  year: 2013
  ident: ref_36
  article-title: Future Retrievals of Water Column Bio-Optical Properties using the Hyperspectral Infrared Imager (HyspIRI)
  publication-title: Remote Sens.
  doi: 10.3390/rs5126812
– volume: 157
  start-page: 48
  year: 2015
  ident: ref_62
  article-title: Airborne hyperspectral data to assess suspended particulate matter and aquatic vegetation in a shallow and turbid lake
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2014.04.034
– volume: 57
  start-page: 10285
  year: 2019
  ident: ref_56
  article-title: Novel Spectra-Derived Features for Empirical Retrieval of Water Quality Parameters: Demonstrations for OLI, MSI, and OLCI Sensors
  publication-title: IEEE Trans. Geosci. Remote Sens.
  doi: 10.1109/TGRS.2019.2933251
– volume: 54
  start-page: 160
  year: 2016
  ident: ref_11
  article-title: Challenges for mapping cyanotoxin patterns from remote sensing of cyanobacteria
  publication-title: Harmful Algae
  doi: 10.1016/j.hal.2016.01.005
– volume: 36
  start-page: 8710
  year: 1997
  ident: ref_71
  article-title: Absorption spectrum (380–700 nm) of pure water II Integrating cavity measurements
  publication-title: Appl. Opt.
  doi: 10.1364/AO.36.008710
– ident: ref_5
  doi: 10.3390/rs11010064
– volume: 225
  start-page: 267
  year: 2019
  ident: ref_65
  article-title: Assessment of atmospheric correction algorithms for the Sentinel-2A MultiSpectral Imager over coastal and inland waters
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2019.03.018
– volume: 2
  start-page: 71
  year: 1981
  ident: ref_20
  article-title: Remote sensing of bottom reflectance and water attenuation parameters in shallow water using aircraft and Landsat data
  publication-title: Int. J. Remote Sens.
  doi: 10.1080/01431168108948342
– volume: 42
  start-page: 1512
  year: 2004
  ident: ref_34
  article-title: The PROBA/CHRIS mission: A low-cost smallsat for hyperspectral multiangle observations of the earth surface and atmosphere
  publication-title: IEEE Trans. Geosci. Remote Sens.
  doi: 10.1109/TGRS.2004.827260
– volume: 51
  start-page: 1407
  year: 2012
  ident: ref_76
  article-title: Analytic model for the direct and diffuse components of downwelling spectral irradiance in water
  publication-title: Appl. Opt.
  doi: 10.1364/AO.51.001407
– volume: 251
  start-page: 112091
  year: 2020
  ident: ref_22
  article-title: SMART-SDB: Sample-specific multiple band ratio technique for satellite-derived bathymetry
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2020.112091
– volume: 54
  start-page: 9724
  year: 2018
  ident: ref_2
  article-title: Satellite Remote Sensing for Water Resources Management: Potential for Supporting Sustainable Development in Data-Poor Regions
  publication-title: Water Resour. Res.
  doi: 10.1029/2017WR022437
– volume: 7
  start-page: 8830
  year: 2015
  ident: ref_32
  article-title: The EnMAP Spaceborne Imaging Spectroscopy Mission for Earth Observation
  publication-title: Remote Sens.
  doi: 10.3390/rs70708830
– ident: ref_66
  doi: 10.3390/s19163609
– ident: ref_12
  doi: 10.3390/s20030742
– volume: 157
  start-page: 138
  year: 2015
  ident: ref_15
  article-title: Estimating lake carbon fractions from remote sensing data
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2014.05.020
– volume: 26
  start-page: 2657
  year: 2005
  ident: ref_17
  article-title: Remote sensing characterization of benthic habitats and submerged vegetation biomass in Los Roques Archipelago National Park, Venezuela
  publication-title: Int. J. Remote Sens.
  doi: 10.1080/01431160500104111
– volume: 35
  start-page: 1657
  year: 1990
  ident: ref_77
  article-title: A simple spectral solar irradiance model for cloudless maritime atmospheres
  publication-title: Limnol. Oceanogr.
  doi: 10.4319/lo.1990.35.8.1657
– ident: ref_67
– ident: ref_64
  doi: 10.3390/rs11121469
– ident: ref_57
  doi: 10.3390/ijgi6120383
– ident: ref_61
  doi: 10.3390/rs8110941
– ident: ref_4
  doi: 10.3390/rs11232883
– volume: 46
  start-page: 993
  year: 2012
  ident: ref_41
  article-title: Estimation of chlorophyll-a concentration in turbid productive waters using airborne hyperspectral data
  publication-title: Water Res.
  doi: 10.1016/j.watres.2011.11.068
– ident: ref_28
  doi: 10.3390/rs12152381
– ident: ref_49
  doi: 10.3390/w12010169
– ident: ref_30
  doi: 10.3390/rs10020157
– volume: 9
  start-page: 1
  year: 2019
  ident: ref_10
  article-title: Measurement of Cyanobacterial Bloom Magnitude using Satellite Remote Sensing
  publication-title: Sci. Rep.
  doi: 10.1038/s41598-019-54453-y
– ident: ref_80
  doi: 10.3390/s16081298
– volume: 100
  start-page: 1775
  year: 2019
  ident: ref_37
  article-title: The plankton, aerosol, cloud, ocean ecosystem mission status, science, advances
  publication-title: Bull. Am. Meteorol. Soc.
  doi: 10.1175/BAMS-D-18-0056.1
– volume: 39
  start-page: 5739
  year: 2018
  ident: ref_26
  article-title: Assessment of PlanetScope images for benthic habitat and seagrass species mapping in a complex optically shallow water environment
  publication-title: Int. J. Remote Sens.
  doi: 10.1080/01431161.2018.1506951
– ident: ref_75
– ident: ref_25
– volume: 109
  start-page: 183
  year: 2007
  ident: ref_46
  article-title: Assessment of water quality in Lake Garda (Italy) using Hyperion
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2006.12.017
– ident: ref_50
– volume: 30
  start-page: 523
  year: 2004
  ident: ref_52
  article-title: The water color simulator WASI: An integrating software tool for analysis and simulation of optical in situ spectra
  publication-title: Comput. Geosci.
  doi: 10.1016/j.cageo.2004.03.005
– volume: 7
  start-page: 14781
  year: 2015
  ident: ref_43
  article-title: Hyperspectral Differentiation of Phytoplankton Taxonomic Groups: A Comparison between Using Remote Sensing Reflectance and Absorption Spectra
  publication-title: Remote Sens.
  doi: 10.3390/rs71114781
– ident: ref_13
  doi: 10.3390/rs10070982
– volume: 41
  start-page: 1149
  year: 2003
  ident: ref_33
  article-title: Overview of the Earth Observing One (EO-1) mission
  publication-title: IEEE Trans. Geosci. Remote Sens.
  doi: 10.1109/TGRS.2003.815999
– volume: 167
  start-page: 218
  year: 2015
  ident: ref_44
  article-title: Remote monitoring of giant kelp biomass and physiological condition: An evaluation of the potential for the Hyperspectral Infrared Imager (HyspIRI) mission
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2015.05.003
– ident: ref_18
  doi: 10.3390/rs11030262
– volume: 247
  start-page: 111900
  year: 2020
  ident: ref_39
  article-title: 150 shades of green: Using the full spectrum of remote sensing reflectance to elucidate color shifts in the ocean
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2020.111900
– ident: ref_58
  doi: 10.3390/s20164553
– ident: ref_35
  doi: 10.1109/IGARSS.2018.8518384
– volume: 185
  start-page: 119
  year: 2016
  ident: ref_24
  article-title: Comparison of Landsat 8 and Landsat 7 for regional measurements of CDOM and water clarity in lakes
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2016.01.007
– ident: ref_70
– ident: ref_27
  doi: 10.3390/jmse8020143
– volume: 216
  start-page: 598
  year: 2018
  ident: ref_21
  article-title: Coral reef applications of Sentinel-2: Coverage, characteristics, bathymetry and benthic mapping with comparison to Landsat 8
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2018.07.014
– volume: 167
  start-page: 229
  year: 2015
  ident: ref_45
  article-title: Spectral and spatial requirements of remote measurements of pelagic Sargassum macroalgae
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2015.05.022
– volume: 113
  start-page: 755
  year: 2009
  ident: ref_53
  article-title: A physics based retrieval and quality assessment of bathymetry from suboptimal hyperspectral data
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2008.12.003
– volume: 69
  start-page: 695
  year: 2003
  ident: ref_1
  article-title: Remote Sensing Techniques to Assess Water Quality
  publication-title: Photogramm. Eng. Remote Sens.
  doi: 10.14358/PERS.69.6.695
– volume: 62
  start-page: 208
  year: 2014
  ident: ref_59
  article-title: WASI-2D: A software tool for regionally optimized analysis of imaging spectrometer data from deep and shallow waters
  publication-title: Comput. Geosci.
  doi: 10.1016/j.cageo.2013.07.022
– volume: 11
  start-page: 2873
  year: 2003
  ident: ref_69
  article-title: An analytical model for subsurface irradiance and remote sensing reflectance in deep and shallow case-2 waters
  publication-title: Opt. Express
  doi: 10.1364/OE.11.002873
– volume: 167
  start-page: 196
  year: 2015
  ident: ref_40
  article-title: Application of hyperspectral remote sensing to cyanobacterial blooms in inland waters
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2015.01.025
SSID ssj0000331904
Score 2.5157661
Snippet A new era of spaceborne hyperspectral imaging has just begun with the recent availability of data from PRISMA (PRecursore IperSpettrale della Missione...
SourceID doaj
proquest
crossref
SourceType Open Website
Aggregation Database
Enrichment Source
Index Database
StartPage 3984
SubjectTerms administrative management
chlorophyll
chlorophyll-a
color
dissolved organic matter
hyperspectral imagery
information
Italy
lake
lakes
PRISMA
radiative transfer
reflectance
remote sensing
remote sensing reflectance
water
water quality
wavelengths
Title Water Quality Retrieval from PRISMA Hyperspectral Images: First Experience in a Turbid Lake and Comparison with Sentinel-2
URI https://www.proquest.com/docview/2511202666
https://doaj.org/article/d8d8f10c30bd4364a49848ac302c738c
Volume 12
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1Nb9NAEF1BOcAF8SlCIRoEFw5W7d31eswtLQ0paqoqaUVv1n6qEcWtnORQfj2ztpsWgcSFk2V7JVuzb2fm2TtvGPvAJZY6cxmBN6hECusSo1JMcqeNzqwVPI3FydMjNTmVX8_yszutvuKesE4euDPcjkOHIUutSI2TQkktS5So6ZzbQqCN3pdi3h0y1fpgQdBKZadHKojX7zTLjCKhKFH-FoFaof4__HAbXMZP2OM-K4RR9zZP2T1fP2MP-wbl59fP2c9vlBM20CleXMOs7YNFIIFYHgLHs4P5dAQT4pRd6WRDdw5-kKtYfoLxghI8uJU0hkUNGk7WjVk4ONTfPejawd6mHyHET7Mwj7uIan-R8BfsdLx_sjdJ-rYJiRVKrZIiiDyVIRilhTSUcaDhvvAZDxjKkAufx_pbw53ShXVpUaJA56QseWa4ofTqJduqL2v_ioFH4zTFK1SWFrcxGnlQNA1oc5MHIQbs440pK9trisfWFhcVcYto9urW7AP2fjP2qlPS-Ouo3TgjmxFR_bq9QJioekxU_8LEgL27mc-KVkv8BaJrf7leVpFQcaKdSr3-Hw_aZo945N_t9pY3bGvVrP1bSlJWZsju4_jLkD0YfZ4ezum4u390PBu2KP0FR_zoZg
linkProvider Directory of Open Access Journals
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=Water+Quality+Retrieval+from+PRISMA+Hyperspectral+Images%3A+First+Experience+in+a+Turbid+Lake+and+Comparison+with+Sentinel-2&rft.jtitle=Remote+sensing+%28Basel%2C+Switzerland%29&rft.au=Niroumand-Jadidi%2C+Milad&rft.au=Bovolo%2C+Francesca&rft.au=Bruzzone%2C+Lorenzo&rft.date=2020-12-01&rft.issn=2072-4292&rft.eissn=2072-4292&rft.volume=12&rft.issue=23&rft.spage=3984&rft_id=info:doi/10.3390%2Frs12233984&rft.externalDBID=n%2Fa&rft.externalDocID=10_3390_rs12233984
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2072-4292&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2072-4292&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2072-4292&client=summon