Developing a Global Data Record of Daily Landscape Freeze/Thaw Status Using Satellite Passive Microwave Remote Sensing

The landscape freeze-thaw (F/T) state parameter derived from satellite microwave remote sensing is closely linked to the surface energy budget, hydrological activity, vegetation growing season dynamics, terrestrial carbon budgets, and land-atmosphere trace gas exchange. Satellite microwave remote se...

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Published inIEEE transactions on geoscience and remote sensing Vol. 49; no. 3; pp. 949 - 960
Main Authors Youngwook Kim, Kimball, J S, McDonald, K C, Glassy, J
Format Journal Article
LanguageEnglish
Published New York, NY IEEE 01.03.2011
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Abstract The landscape freeze-thaw (F/T) state parameter derived from satellite microwave remote sensing is closely linked to the surface energy budget, hydrological activity, vegetation growing season dynamics, terrestrial carbon budgets, and land-atmosphere trace gas exchange. Satellite microwave remote sensing is well suited for global F/T monitoring due to its insensitivity to atmospheric contamination and solar illumination effects, and its strong sensitivity to the relationship between landscape dielectric properties and predominantly frozen and thawed conditions. We investigated the utility of multifrequency and dual polarization brightness temperature (T b ) measurements from the Special Sensor Microwave Imager (SSM/I) to map global patterns and daily variations in terrestrial F/T cycles. We defined a global F/T classification domain by examining biophysical cold temperature constraints to vegetation growing seasons. We applied a temporal change classification algorithm based on a seasonal thresholding scheme to classify daily F/T states from time series T b measurements. The SSM/I F/T classification accuracy was assessed using in situ air temperature measurements from the global WMO weather station network. A single-channel classification of 37 GHz, V-polarization T b time series provided generally improved performance over other SSM/I frequencies, polarizations and channel combinations. Mean annual F/T classification accuracies were 92.2 ±0.8 [SD] % and 85.0 ±0.7 [SD] % for respective SSM/I time series of P.M. and A.M. orbital nodes over the global domain and a 20-year (1988-2007) satellite record. The resulting database provides a continuous and relatively long-term record of daily F/T dynamics for the global biosphere with well-defined accuracy.
AbstractList The landscape freeze-thaw (F/T) state parameter derived from satellite microwave remote sensing is closely linked to the surface energy budget, hydrological activity, vegetation growing season dynamics, terrestrial carbon budgets, and land-atmosphere trace gas exchange. Satellite microwave remote sensing is well suited for global F/T monitoring due to its insensitivity to atmospheric contamination and solar illumination effects, and its strong sensitivity to the relationship between landscape dielectric properties and predominantly frozen and thawed conditions. We investigated the utility of multifrequency and dual polarization brightness temperature (T b ) measurements from the Special Sensor Microwave Imager (SSM/I) to map global patterns and daily variations in terrestrial F/T cycles. We defined a global F/T classification domain by examining biophysical cold temperature constraints to vegetation growing seasons. We applied a temporal change classification algorithm based on a seasonal thresholding scheme to classify daily F/T states from time series T b measurements. The SSM/I F/T classification accuracy was assessed using in situ air temperature measurements from the global WMO weather station network. A single-channel classification of 37 GHz, V-polarization T b time series provided generally improved performance over other SSM/I frequencies, polarizations and channel combinations. Mean annual F/T classification accuracies were 92.2 ±0.8 [SD] % and 85.0 ±0.7 [SD] % for respective SSM/I time series of P.M. and A.M. orbital nodes over the global domain and a 20-year (1988-2007) satellite record. The resulting database provides a continuous and relatively long-term record of daily F/T dynamics for the global biosphere with well-defined accuracy.
The landscape freeze-thaw (F/T) state parameter derived from satellite microwave remote sensing is closely linked to the surface energy budget, hydrological activity, vegetation growing season dynamics, terrestrial carbon budgets, and land-atmosphere trace gas exchange. Satellite microwave remote sensing is well suited for global F/T monitoring due to its insensitivity to atmospheric contamination and solar illumination effects, and its strong sensitivity to the relationship between landscape dielectric properties and predominantly frozen and thawed conditions. We investigated the utility of multifrequency and dual polarization brightness temperature ( T b ) measurements from the Special Sensor Microwave Imager (SSM/I) to map global patterns and daily variations in terrestrial F/T cycles. We defined a global F/T classification domain by examining biophysical cold temperature constraints to vegetation growing seasons. We applied a temporal change classification algorithm based on a seasonal thresholding scheme to classify daily F/T states from time series T b measurements. The SSM/I F/T classification accuracy was assessed using in situ air temperature measurements from the global WMO weather station network. A single-channel classification of 37 GHz, V-polarization T b time series provided generally improved performance over other SSM/I frequencies, polarizations and channel combinations. Mean annual F/T classification accuracies were 92.2 +/- 0.8 [SD] % and 85.0 +/- 0.7 [SD] % for respective SSM/I time series of p.m. and a.m. orbital nodes over the global domain and a 20-year (1988-2007) satellite record. The resulting database provides a continuous and relatively long-term record of daily F/T dynamics for the global biosphere with well-defined accuracy.
The landscape freeze-thaw (F/T) state parameter derived from satellite microwave remote sensing is closely linked to the surface energy budget, hydrological activity, vegetation growing season dynamics, terrestrial carbon budgets, and land-atmosphere trace gas exchange. Satellite microwave remote sensing is well suited for global F/T monitoring due to its insensitivity to atmospheric contamination and solar illumination effects, and its strong sensitivity to the relationship between landscape dielectric properties and predominantly frozen and thawed conditions. We investigated the utility of multifrequency and dual polarization brightness temperature measurements from the Special Sensor Microwave Imager (SSM/I) to map global patterns and daily variations in terrestrial F/T cycles. We defined a global F/T classification domain by examining biophysical cold temperature constraints to vegetation growing seasons. We applied a temporal change classification algorithm based on a seasonal thresholding scheme to classify daily F/T states from time series measurements. The SSM/I F/T classification accuracy was assessed using in situ air temperature measurements from the global WMO weather station network. A single-channel classification of 37 GHz, V-polarization time series provided generally improved performance over other SSM/I frequencies, polarizations and channel combinations. Mean annual F/T classification accuracies were 92.2 0.8 [SD] % and 85.0 0.7 [SD] % for respective SSM/I time series of p.m. and a.m. orbital nodes over the global domain and a 20-year (1988-2007) satellite record. The resulting database provides a continuous and relatively long-term record of daily F/T dynamics for the global biosphere with well-defined accuracy.
Author McDonald, K C
Kimball, J S
Youngwook Kim
Glassy, J
Author_xml – sequence: 1
  surname: Youngwook Kim
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  organization: FLBS/NTSG, Univ. of Montana, Missoula, MT, USA
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  surname: McDonald
  fullname: McDonald, K C
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– sequence: 4
  givenname: J
  surname: Glassy
  fullname: Glassy, J
  email: joe.glassy@ntsg.umt.edu
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Issue 3
Keywords atmosphere
microwaves
algorithms
accuracy
vegetation
cycles
global
air
networks
passive microwave remote sensing
frequency
carbon
Special Sensor Microwave Imager
radiometry
polarization
soil moisture active passive
data bases
performances
energy
landscapes
satellites
Earth system data record
maps
dielectric properties
remote sensing
freeze/thaw
classification
in situ
contamination
brightness temperature
channels
Making Earth System Data Records for Use in Research Environments
Language English
License CC BY 4.0
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Snippet The landscape freeze-thaw (F/T) state parameter derived from satellite microwave remote sensing is closely linked to the surface energy budget, hydrological...
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SubjectTerms Accuracy
Applied geophysics
Artificial neural networks
Budgeting
Classification
Earth sciences
Earth system data record
Earth, ocean, space
Exact sciences and technology
freeze/thaw
Internal geophysics
Land surface temperature
Landscapes
Making Earth System Data Records for Use in Research Environments
Meteorology
Microwave measurements
Microwaves
passive microwave remote sensing
radiometry
Remote sensing
Satellites
soil moisture active passive
Special Sensor Microwave Imager
Temperature
Temperature measurement
Time series
Vegetation
Title Developing a Global Data Record of Daily Landscape Freeze/Thaw Status Using Satellite Passive Microwave Remote Sensing
URI https://ieeexplore.ieee.org/document/5599863
https://www.proquest.com/docview/853268833
https://search.proquest.com/docview/1019658798
Volume 49
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