On the Relationship Between Radar Backscatter and Radiometer Brightness Temperature From SMAP

The synergy of active and passive microwave measurements has attracted considerable attention in recent years since they offer complementary information on the characteristics of the observed target (e.g., soil moisture), which motivates the launch of NASA's Soil Moisture Active Passive (SMAP)...

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Vydáno v:IEEE transactions on geoscience and remote sensing Ročník 60; s. 1 - 16
Hlavní autoři: Zeng, Jiangyuan, Shi, Pengfei, Chen, Kun-Shan, Ma, Hongliang, Bi, Haiyun, Cui, Chenyang
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Active microwave
Algorithms
Arid regions
Backscatter
Backscattering
Brightness
Brightness temperature
Climate
Correlation coefficient
Correlation coefficients
Dynamics
Environmental factors
Land cover
Microwave measurement
Microwave radiometry
passive microwave
Radar
Radar signatures
Radiometers
Resolution
Soil
Soil conditions
Soil dynamics
Soil moisture
soil moisture (SM)
soil moisture active passive (SMAP)
Soil properties
Soil texture
Spaceborne radar
Surface radiation temperature
synergy
Texture
Vegetation
Vegetation mapping
ISSN:0196-2892, 1558-0644
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Abstract The synergy of active and passive microwave measurements has attracted considerable attention in recent years since they offer complementary information on the characteristics of the observed target (e.g., soil moisture), which motivates the launch of NASA's Soil Moisture Active Passive (SMAP) mission. An assumption of a near-linear relationship between active and passive measurements has been made in the SMAP active-passive baseline algorithm, which is essential to downscale coarse-resolution radiometer brightness temperature (TB) using high-resolution radar backscatter (<inline-formula> <tex-math notation="LaTeX">\sigma ^{0} </tex-math></inline-formula>) but has not yet been fully tested under a wide range of ground conditions. Motivated by this, we first examined the validity of the linear assumption by using concurrent and coincident SMAP active and passive observations under diverse environmental factors (e.g., land cover, climate types, terrain and its complexity, soil texture, vegetation coverage, soil moisture, and its dynamics). We also adopted SMAP enhanced TB to evaluate the performance of the disaggregated TB at the same grid resolution of 9 km. The results reveal there is a generally good linear relationship between <inline-formula> <tex-math notation="LaTeX">\sigma ^{0} </tex-math></inline-formula> (no matter in dB or in linear unit) and TB at a global scale. There is no significant difference in the correlation among the four polarization combinations (<inline-formula> <tex-math notation="LaTeX">\sigma ^{0}_{\text {hh}} </tex-math></inline-formula> versus TB h , <inline-formula> <tex-math notation="LaTeX">\sigma ^{{0}}_{\text {hh}} </tex-math></inline-formula> versus TB v , <inline-formula> <tex-math notation="LaTeX">\sigma ^{{0}}_{\text {vv}} </tex-math></inline-formula> versus TB h , and <inline-formula> <tex-math notation="LaTeX">\sigma ^{{0}}_{\text {vv}} </tex-math></inline-formula> versus TB v ) with the <inline-formula> <tex-math notation="LaTeX">\sigma ^{{0}}_{\text {vv}} </tex-math></inline-formula> and TB h combination displaying an overall slightly higher correlation. The linear relationship between <inline-formula> <tex-math notation="LaTeX">\sigma ^{{0}} </tex-math></inline-formula> and TB is significantly affected by environmental factors. Particularly in bare soils and densely vegetated areas (e.g., large forest fraction and vegetation coverage), and arid and polar climate zones, the linear correlation between active and passive measurements worsens, whereas it is favorable in moderate vegetation and soil moisture as well as large soil moisture dynamic conditions. Interestingly, the linear correlation generally decreases as sand content increases while increases with the increase of clay content. The absolute linear correlation coefficient is higher with larger soil moisture dynamics. When compared to SMAP enhanced TB, it shows the linear assumption may have more influence on the correlation (i.e., temporal evolution) of downscaled TB than its absolute accuracy. These findings can enhance the understanding of the geophysical relationship between radar and radiometer signatures, and thus benefit active-passive joint algorithms for future satellite missions.
AbstractList The synergy of active and passive microwave measurements has attracted considerable attention in recent years since they offer complementary information on the characteristics of the observed target (e.g., soil moisture), which motivates the launch of NASA's Soil Moisture Active Passive (SMAP) mission. An assumption of a near-linear relationship between active and passive measurements has been made in the SMAP active-passive baseline algorithm, which is essential to downscale coarse-resolution radiometer brightness temperature (TB) using high-resolution radar backscatter (<inline-formula> <tex-math notation="LaTeX">\sigma ^{0} </tex-math></inline-formula>) but has not yet been fully tested under a wide range of ground conditions. Motivated by this, we first examined the validity of the linear assumption by using concurrent and coincident SMAP active and passive observations under diverse environmental factors (e.g., land cover, climate types, terrain and its complexity, soil texture, vegetation coverage, soil moisture, and its dynamics). We also adopted SMAP enhanced TB to evaluate the performance of the disaggregated TB at the same grid resolution of 9 km. The results reveal there is a generally good linear relationship between <inline-formula> <tex-math notation="LaTeX">\sigma ^{0} </tex-math></inline-formula> (no matter in dB or in linear unit) and TB at a global scale. There is no significant difference in the correlation among the four polarization combinations (<inline-formula> <tex-math notation="LaTeX">\sigma ^{0}_{\text {hh}} </tex-math></inline-formula> versus TB h , <inline-formula> <tex-math notation="LaTeX">\sigma ^{{0}}_{\text {hh}} </tex-math></inline-formula> versus TB v , <inline-formula> <tex-math notation="LaTeX">\sigma ^{{0}}_{\text {vv}} </tex-math></inline-formula> versus TB h , and <inline-formula> <tex-math notation="LaTeX">\sigma ^{{0}}_{\text {vv}} </tex-math></inline-formula> versus TB v ) with the <inline-formula> <tex-math notation="LaTeX">\sigma ^{{0}}_{\text {vv}} </tex-math></inline-formula> and TB h combination displaying an overall slightly higher correlation. The linear relationship between <inline-formula> <tex-math notation="LaTeX">\sigma ^{{0}} </tex-math></inline-formula> and TB is significantly affected by environmental factors. Particularly in bare soils and densely vegetated areas (e.g., large forest fraction and vegetation coverage), and arid and polar climate zones, the linear correlation between active and passive measurements worsens, whereas it is favorable in moderate vegetation and soil moisture as well as large soil moisture dynamic conditions. Interestingly, the linear correlation generally decreases as sand content increases while increases with the increase of clay content. The absolute linear correlation coefficient is higher with larger soil moisture dynamics. When compared to SMAP enhanced TB, it shows the linear assumption may have more influence on the correlation (i.e., temporal evolution) of downscaled TB than its absolute accuracy. These findings can enhance the understanding of the geophysical relationship between radar and radiometer signatures, and thus benefit active-passive joint algorithms for future satellite missions.
The synergy of active and passive microwave measurements has attracted considerable attention in recent years since they offer complementary information on the characteristics of the observed target (e.g., soil moisture), which motivates the launch of NASA’s Soil Moisture Active Passive (SMAP) mission. An assumption of a near-linear relationship between active and passive measurements has been made in the SMAP active–passive baseline algorithm, which is essential to downscale coarse-resolution radiometer brightness temperature (TB) using high-resolution radar backscatter ([Formula Omitted]) but has not yet been fully tested under a wide range of ground conditions. Motivated by this, we first examined the validity of the linear assumption by using concurrent and coincident SMAP active and passive observations under diverse environmental factors (e.g., land cover, climate types, terrain and its complexity, soil texture, vegetation coverage, soil moisture, and its dynamics). We also adopted SMAP enhanced TB to evaluate the performance of the disaggregated TB at the same grid resolution of 9 km. The results reveal there is a generally good linear relationship between [Formula Omitted] (no matter in dB or in linear unit) and TB at a global scale. There is no significant difference in the correlation among the four polarization combinations ([Formula Omitted] versus TBh, [Formula Omitted] versus TBv, [Formula Omitted] versus TBh, and [Formula Omitted] versus TBv) with the [Formula Omitted] and TBh combination displaying an overall slightly higher correlation. The linear relationship between [Formula Omitted] and TB is significantly affected by environmental factors. Particularly in bare soils and densely vegetated areas (e.g., large forest fraction and vegetation coverage), and arid and polar climate zones, the linear correlation between active and passive measurements worsens, whereas it is favorable in moderate vegetation and soil moisture as well as large soil moisture dynamic conditions. Interestingly, the linear correlation generally decreases as sand content increases while increases with the increase of clay content. The absolute linear correlation coefficient is higher with larger soil moisture dynamics. When compared to SMAP enhanced TB, it shows the linear assumption may have more influence on the correlation (i.e., temporal evolution) of downscaled TB than its absolute accuracy. These findings can enhance the understanding of the geophysical relationship between radar and radiometer signatures, and thus benefit active–passive joint algorithms for future satellite missions.
Author Chen, Kun-Shan
Zeng, Jiangyuan
Bi, Haiyun
Cui, Chenyang
Shi, Pengfei
Ma, Hongliang
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Cites_doi 10.1016/j.rse.2019.03.021
10.1016/j.rse.2015.03.018
10.1109/TGRS.1981.350328
10.1109/TGRS.2010.2089526
10.1109/TGRS.2018.2864689
10.1127/0941-2948/2006/0130
10.1029/2012GL052988
10.1109/TGRS.2017.2762462
10.1109/TGRS.2014.2373972
10.1109/JSTARS.2016.2570424
10.1109/TGRS.2019.2955542
10.1109/JSTARS.2016.2611491
10.1016/j.jag.2019.01.005
10.5194/hess-14-2605-2010
10.1016/j.rse.2015.11.011
10.1109/TGRS.2020.2991252
10.1038/s41586-021-03325-5
10.1109/IGARSS.2017.8127919
10.1109/TGRS.2013.2257605
10.1109/JPROC.2010.2043918
10.3390/rs10010033
10.1016/j.rse.2015.03.008
10.2136/sssaj2013.03.0093
10.1109/TGRS.2017.2734070
10.1016/S0034-4257(02)00096-2
10.1016/j.rse.2017.08.025
10.5721/EuJRS20124511
10.1016/j.rse.2018.02.006
10.1007/s10712-008-9044-0
10.1109/TGRS.2016.2561938
10.1109/IGARSS.2016.7729886
10.1109/JSTARS.2016.2562660
10.2136/vzj2016.10.0105
10.18393/ejss.2016.4.266-274
10.1016/j.rse.2014.08.021
10.1016/j.rse.2018.04.011
10.3998/0472119356
10.1109/TGRS.2013.2280701
10.1038/s41558-020-00945-z
10.1016/j.jag.2015.08.002
10.1016/j.rse.2012.02.002
10.1175/JAMC-D-13-0270.1
10.1016/j.rse.2019.111380
10.1002/qj.3803
10.1016/j.xinn.2021.100146
10.1029/JC087iC13p11229
10.1109/TGRS.2010.2096514
10.1073/pnas.2015821118
10.1109/36.210456
10.1016/j.rse.2019.111215
10.1109/TGRS.2017.2688403
10.1002/2016rg000543
10.1109/TGRS.2006.871199
10.1109/TGRS.2020.3035204
10.1109/TGRS.2015.2407611
10.3390/rs6098594
10.1109/JSTARS.2013.2272053
10.1109/TGRS.2009.2022088
10.1080/17538947.2021.1907461
10.1016/j.rse.2015.02.002
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References ref13
ref57
ref12
ref56
ref15
ref59
ref58
ref53
ref52
ref11
ref55
ref10
ref54
ref17
ref16
ref19
ref18
ref51
ref50
ref46
ref48
ref47
ref42
Entekhabi (ref14) 2014
Das (ref35) 2019
ref43
ref49
ref8
ref7
ref9
ref4
ref3
ref6
ref5
ref40
ref34
ref31
ref30
ref33
ref32
O’Neill (ref38) 2020
ref2
ref1
ref39
ref24
ref68
ref23
ref67
ref26
ref25
ref20
ref64
ref63
ref22
ref66
ref21
ref65
Entekhabi (ref36) 2016
ref28
O’Neill (ref37) 2020
ref27
ref29
Kim (ref41) 2017
Nachtergaele (ref44) 2012
ref60
ref62
ref61
Hastings (ref45) 1998; 4
References_xml – ident: ref20
  doi: 10.1016/j.rse.2019.03.021
– ident: ref52
  doi: 10.1016/j.rse.2015.03.018
– ident: ref66
  doi: 10.1109/TGRS.1981.350328
– ident: ref17
  doi: 10.1109/TGRS.2010.2089526
– ident: ref26
  doi: 10.1109/TGRS.2018.2864689
– ident: ref43
  doi: 10.1127/0941-2948/2006/0130
– ident: ref65
  doi: 10.1029/2012GL052988
– year: 2019
  ident: ref35
  article-title: Algorithm theoretical basis document-SMAP-Sentinel L2 radar/radiometer (active/passive) soil moisture data products
– ident: ref33
  doi: 10.1109/TGRS.2017.2762462
– ident: ref6
  doi: 10.1109/TGRS.2014.2373972
– ident: ref22
  doi: 10.1109/JSTARS.2016.2570424
– ident: ref49
  doi: 10.1109/TGRS.2019.2955542
– ident: ref7
  doi: 10.1109/JSTARS.2016.2611491
– ident: ref12
  doi: 10.1016/j.jag.2019.01.005
– ident: ref55
  doi: 10.5194/hess-14-2605-2010
– ident: ref9
  doi: 10.1016/j.rse.2015.11.011
– ident: ref28
  doi: 10.1109/TGRS.2020.2991252
– ident: ref1
  doi: 10.1038/s41586-021-03325-5
– ident: ref48
  doi: 10.1109/IGARSS.2017.8127919
– ident: ref18
  doi: 10.1109/TGRS.2013.2257605
– ident: ref13
  doi: 10.1109/JPROC.2010.2043918
– ident: ref67
  doi: 10.3390/rs10010033
– ident: ref5
  doi: 10.1016/j.rse.2015.03.008
– ident: ref4
  doi: 10.2136/sssaj2013.03.0093
– ident: ref11
  doi: 10.1109/TGRS.2017.2734070
– ident: ref46
  doi: 10.1016/S0034-4257(02)00096-2
– ident: ref39
  doi: 10.1016/j.rse.2017.08.025
– ident: ref21
  doi: 10.5721/EuJRS20124511
– ident: ref40
  doi: 10.1016/j.rse.2018.02.006
– ident: ref56
  doi: 10.1007/s10712-008-9044-0
– year: 2020
  ident: ref37
  article-title: SMAP L3 radiometer global daily 36 km EASE-grid soil moisture
– ident: ref64
  doi: 10.1109/TGRS.2016.2561938
– ident: ref30
  doi: 10.1109/IGARSS.2016.7729886
– year: 2014
  ident: ref14
  article-title: SMAP handbook soil moisture active passive, mapping soil moisture freeze/thaw from space
– ident: ref23
  doi: 10.1109/JSTARS.2016.2562660
– ident: ref3
  doi: 10.2136/vzj2016.10.0105
– ident: ref62
  doi: 10.18393/ejss.2016.4.266-274
– ident: ref25
  doi: 10.1016/j.rse.2014.08.021
– ident: ref54
  doi: 10.1016/j.rse.2018.04.011
– ident: ref53
  doi: 10.3998/0472119356
– ident: ref57
  doi: 10.1109/TGRS.2013.2280701
– ident: ref2
  doi: 10.1038/s41558-020-00945-z
– ident: ref10
  doi: 10.1016/j.jag.2015.08.002
– ident: ref34
  doi: 10.1016/j.rse.2012.02.002
– ident: ref42
  doi: 10.1175/JAMC-D-13-0270.1
– ident: ref19
  doi: 10.1016/j.rse.2019.111380
– year: 2020
  ident: ref38
  article-title: SMAP enhanced L3 radiometer global daily 9 km EASE-grid soil moisture
– ident: ref47
  doi: 10.1002/qj.3803
– ident: ref58
  doi: 10.1016/j.xinn.2021.100146
– ident: ref63
  doi: 10.1029/JC087iC13p11229
– year: 2017
  ident: ref41
  article-title: Soil moisture active passive (SMAP) project calibration and validation for the L2/3_SM_A validated-stage 1 release data products (version 4)
– volume-title: Harmonized World Soil Database
  year: 2012
  ident: ref44
– ident: ref60
  doi: 10.1109/TGRS.2010.2096514
– ident: ref50
  doi: 10.1073/pnas.2015821118
– ident: ref61
  doi: 10.1109/36.210456
– ident: ref51
  doi: 10.1016/j.rse.2019.111215
– ident: ref8
  doi: 10.1109/TGRS.2017.2688403
– ident: ref32
  doi: 10.1002/2016rg000543
– ident: ref15
  doi: 10.1109/TGRS.2006.871199
– volume: 4
  start-page: 218
  issue: 6
  year: 1998
  ident: ref45
  article-title: Development & assessment of the global land one-km base elevation digital elevation model (GLOBE)
  publication-title: Group
– ident: ref27
  doi: 10.1109/TGRS.2020.3035204
– ident: ref24
  doi: 10.1109/TGRS.2015.2407611
– ident: ref68
  doi: 10.3390/rs6098594
– ident: ref31
  doi: 10.1109/JSTARS.2013.2272053
– year: 2016
  ident: ref36
  article-title: SMAP L3 radar/radiometer global daily 9 km EASE-grid soil moisture
– ident: ref16
  doi: 10.1109/TGRS.2009.2022088
– ident: ref29
  doi: 10.1080/17538947.2021.1907461
– ident: ref59
  doi: 10.1016/j.rse.2015.02.002
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Snippet The synergy of active and passive microwave measurements has attracted considerable attention in recent years since they offer complementary information on the...
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SubjectTerms Active microwave
Algorithms
Arid regions
Backscatter
Backscattering
Brightness
Brightness temperature
Climate
Correlation coefficient
Correlation coefficients
Dynamics
Environmental factors
Land cover
Microwave measurement
Microwave radiometry
passive microwave
Radar
Radar signatures
Radiometers
Resolution
Soil
Soil conditions
Soil dynamics
Soil moisture
soil moisture (SM)
soil moisture active passive (SMAP)
Soil properties
Soil texture
Spaceborne radar
Surface radiation temperature
synergy
Texture
Vegetation
Vegetation mapping
Title On the Relationship Between Radar Backscatter and Radiometer Brightness Temperature From SMAP
URI https://ieeexplore.ieee.org/document/9560162
https://www.proquest.com/docview/2624756724
Volume 60
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