|Colliander, A -|
|Chan, S -|
|Kim, S -|
|Das, N -|
|Yueh, S -|
|Bindlish, R -|
|Njoku, E -|
Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: February 12, 2012
Publication Date: June 1, 2012
Citation: Colliander, A., Chan, S., Kim, S., Das, N., Yueh, S., Cosh, M.H., Bindlish, R., Jackson, T.J., Njoku, E. 2012. Long term analysis of PALS soil moisture campaign measurements for global soil moisture algorithm development. Remote Sensing of Environment. 121:309-322. Interpretive Summary: The upcoming NASA Soil Moisture Active Passive (SMAP) mission will use both active and passive radiometers to estimate surface soil moisture for the globe. This mission is a culmination of a series of field experiments which established the feasibility and accuracy of this combined radiometer concept. Previous satellite missions have used either passive or active, but not both. The Passive and Active L-Band System (PALS) is the current aircraft simulator for the SMAP mission and has been flown over a span of 10 years. This paper provides an overview of those field experiments and summarizes the findings and points to future questions which must still be addressed by field experimentation. These include how to estimate soil moisture over dense vegetation, and how does the system perform for lengthy time scales over the same domain.
Technical Abstract: An important component of satellite-based soil moisture algorithm development and validation is the comparison of coincident remote sensing and in situ observations that are typically provided by intensive field campaigns. The planned NASA Soil Moisture Active Passive (SMAP) mission has unique requirements compared to previous soil moisture satellite programs because both active and passive microwave observations are needed. The primary source of these combined observations has been an aircraft-based SMAP simulator called PALS (Passive and Active L-band System). This paper presents an overview of the field experiment data collected using PALS that spans 10 years. Data from the various campaigns were merged to form a single data set. Analyses showed that the data set contains an extensive range of soil moisture values collected under a variety of conditions and that the quality of both the PALS and ground truth data meets the needs of SMAP algorithm development and validation. The study suggests that the data set should be expanded in order to achieve globally representative land cover diversity and that more observations under dense vegetation conditions and longer time series would be desirable.