TY - JOUR
T1 - Spatial sampling uncertainty in SMEX04 soil moisture fields
T2 - A data-based resampling experiment
AU - Gebremichael, Mekonnen
AU - Vivoni, Enrique R.
N1 - Funding Information:
We would like to acknowledge funding for this work from NSF NM EPSCoR project. We particularly thank Thomas J. Jackson and Rajat Bindlish (USDA-ARS) for providing the PSR/CX soil moisture data over the SMEX04 Sonora region. In addition, we thank David Gochis (NCAR), Julio C. Rodríguez (IMADES), Christopher J. Watts (Universidad de Sonora) and Jaime Garatuza-Payán (ITSON) for providing useful ancillary data sets used in this study. This effort would not have been possible without the organization and implementation of the SMEX04 experiment in Sonora. We are grateful to all the participants in the field activities and initial data processing.
Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
PY - 2008/2/15
Y1 - 2008/2/15
N2 - A data-based resampling experiment is performed to estimate sampling errors of area-averaged soil moisture estimates due to spatial sampling by ground-based sensors. The data consists of high-resolution soil moisture images derived from the Polarimetric Scanning Radiometer (PSR/CX) sensor flown on an aircraft as part of the summer field experiment (SMEX04 - Soil Moisture Experiment 2004) in the monsoon region of Sonora, Mexico. The sampling characteristics are investigated by accounting for random networks and evenly spaced networks. For random network designs, we develop a simple model that can be used to estimate the sampling uncertainty (expressed as standard deviation of sampling error as a percentage of the areal mean soil moisture) as a function of the number of sensors, mean soil moisture content and averaging area. This model is valid for five or more sensors. The model should prove useful to those wishing to assess the area-averaged performance of a soil moisture network. Furthermore, the method of analysis is applicable to other study regions (Oklahoma, Iowa, Alabama, Georgia, and Arizona) where soil moisture fields have been mapped at high resolution using airborne passive microwave remote sensors.
AB - A data-based resampling experiment is performed to estimate sampling errors of area-averaged soil moisture estimates due to spatial sampling by ground-based sensors. The data consists of high-resolution soil moisture images derived from the Polarimetric Scanning Radiometer (PSR/CX) sensor flown on an aircraft as part of the summer field experiment (SMEX04 - Soil Moisture Experiment 2004) in the monsoon region of Sonora, Mexico. The sampling characteristics are investigated by accounting for random networks and evenly spaced networks. For random network designs, we develop a simple model that can be used to estimate the sampling uncertainty (expressed as standard deviation of sampling error as a percentage of the areal mean soil moisture) as a function of the number of sensors, mean soil moisture content and averaging area. This model is valid for five or more sensors. The model should prove useful to those wishing to assess the area-averaged performance of a soil moisture network. Furthermore, the method of analysis is applicable to other study regions (Oklahoma, Iowa, Alabama, Georgia, and Arizona) where soil moisture fields have been mapped at high resolution using airborne passive microwave remote sensors.
KW - Remote sensing
KW - SMEX04
KW - Sampling uncertainty
KW - Soil moisture
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U2 - 10.1016/j.rse.2006.12.021
DO - 10.1016/j.rse.2006.12.021
M3 - Article
AN - SCOPUS:38049045661
SN - 0034-4257
VL - 112
SP - 326
EP - 336
JO - Remote Sensing of Environment
JF - Remote Sensing of Environment
IS - 2
ER -