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 in | IEEE transactions on geoscience and remote sensing Vol. 49; no. 3; pp. 949 - 960 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
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. |
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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 fullname: Youngwook Kim email: youngwook.kim@ntsg.umt.edu organization: FLBS/NTSG, Univ. of Montana, Missoula, MT, USA – sequence: 2 givenname: J S surname: Kimball fullname: Kimball, J S email: johnk@ntsg.umt.edu organization: Div. of Biol. Sci., Univ. of Montana, Missoula, MT, USA – sequence: 3 givenname: K C surname: McDonald fullname: McDonald, K C email: kyle.c.mcdonald@jpl.nasa.gov organization: Jet Propulsion Lab., California Inst. of Technol., Pasadena, CA, USA – sequence: 4 givenname: J surname: Glassy fullname: Glassy, J email: joe.glassy@ntsg.umt.edu organization: Lupine Logic, Inc., Missoula, MT, USA |
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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 |
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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 |
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