Establishing a Relationship Between Soil Moisture and RADARSAT-1 SAR Data Obtained over the Great Basin, Nevada, U.S.A.

Nancy F. Glenn; J. R. Carr

doi:10.5589/m03-057

Establishing a Relationship Between Soil Moisture and RADARSAT-1 SAR Data Obtained over the Great Basin, Nevada, U.S.A.

Nancy F. Glenn, J. R. Carr

Idaho State University

Research output: Contribution to journal › Article › peer-review

11 Scopus citations

Abstract

A predictive model estimating soil moisture with RADARSAT-1 data is developed for Winnemucca Lake, Nevada, in the western Great Basin of North America. Winnemucca Lake, a playa, is used for testing based on its hydrologic and geomorphic properties and its nonvegetated environment. The empirical model predicts soil moisture (%) as 2.4 sigma nought (σo) + 137.8 db, yielding a correlation coefficient between soil moisture and σo of 0.86. This relationship was developed by using block kriging to geostatistically register the point field soil moisture measurements to the σo values from the RADARSAT-1 pixels. It is considered to be significant because it depicts a new geostatistical approach for relating point measurements with area estimates of soil moisture from remote sensing data.

Original language	American English
Pages (from-to)	176-181
Number of pages	6
Journal	Canadian Journal of Remote Sensing
Volume	30
Issue number	2
DOIs	https://doi.org/10.5589/m03-057
State	Published - 2004
Externally published	Yes

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Plant Sciences

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10.5589/m03-057

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title = "Establishing a Relationship Between Soil Moisture and RADARSAT-1 SAR Data Obtained over the Great Basin, Nevada, U.S.A.",

abstract = " A predictive model estimating soil moisture with RADARSAT-1 data is developed for Winnemucca Lake, Nevada, in the western Great Basin of North America. Winnemucca Lake, a playa, is used for testing based on its hydrologic and geomorphic properties and its nonvegetated environment. The empirical model predicts soil moisture (\%) as 2.4 sigma nought (σo) + 137.8 db, yielding a correlation coefficient between soil moisture and σo of 0.86. This relationship was developed by using block kriging to geostatistically register the point field soil moisture measurements to the σo values from the RADARSAT-1 pixels. It is considered to be significant because it depicts a new geostatistical approach for relating point measurements with area estimates of soil moisture from remote sensing data.",

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pages = "176--181",

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AU - Glenn, Nancy F.

AU - Carr, J. R.

PY - 2004

Y1 - 2004

N2 - A predictive model estimating soil moisture with RADARSAT-1 data is developed for Winnemucca Lake, Nevada, in the western Great Basin of North America. Winnemucca Lake, a playa, is used for testing based on its hydrologic and geomorphic properties and its nonvegetated environment. The empirical model predicts soil moisture (%) as 2.4 sigma nought (σo) + 137.8 db, yielding a correlation coefficient between soil moisture and σo of 0.86. This relationship was developed by using block kriging to geostatistically register the point field soil moisture measurements to the σo values from the RADARSAT-1 pixels. It is considered to be significant because it depicts a new geostatistical approach for relating point measurements with area estimates of soil moisture from remote sensing data.

AB - A predictive model estimating soil moisture with RADARSAT-1 data is developed for Winnemucca Lake, Nevada, in the western Great Basin of North America. Winnemucca Lake, a playa, is used for testing based on its hydrologic and geomorphic properties and its nonvegetated environment. The empirical model predicts soil moisture (%) as 2.4 sigma nought (σo) + 137.8 db, yielding a correlation coefficient between soil moisture and σo of 0.86. This relationship was developed by using block kriging to geostatistically register the point field soil moisture measurements to the σo values from the RADARSAT-1 pixels. It is considered to be significant because it depicts a new geostatistical approach for relating point measurements with area estimates of soil moisture from remote sensing data.

U2 - 10.5589/m03-057

DO - 10.5589/m03-057

M3 - Article

VL - 30

SP - 176

EP - 181

JO - Canadian Journal of Remote Sensing

JF - Canadian Journal of Remote Sensing

IS - 2

ER -

Establishing a Relationship Between Soil Moisture and RADARSAT-1 SAR Data Obtained over the Great Basin, Nevada, U.S.A.

Abstract

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