H21H-1491
Satellite Based Soil Moisture Product Validation Using NOAA-CREST Ground and L-Band Observations

Tuesday, 15 December 2015
Poster Hall (Moscone South)
Christian Campo1, Hamidreza Norouzi2, Marouane Temimi3, Tarendra Lakhankar3 and Reza Khanbilvardi4, (1)New York City College of Technology, Brooklyn, NY, United States, (2)New York City College of Technology, CUNY, Brooklyn, NY, United States, (3)NOAA-CREST/City College, CUNY, New York, NY, United States, (4)CUNY-Civil Engineering T-107, New York, NY, United States
Abstract:
Soil moisture content is among most important physical parameters in hydrology, climate, and environmental studies. Many microwave-based satellite observations have been utilized to estimate this parameter. The Advanced Microwave Scanning Radiometer 2 (AMSR2) is one of many remotely sensors that collects daily information of land surface soil moisture. However, many factors such as ancillary data and vegetation scattering can affect the signal and the estimation. Therefore, this information needs to be validated against some “ground-truth” observations. NOAA – Cooperative Remote Sensing and Technology (CREST) center at the City University of New York has a site located at Millbrook, NY with several insitu soil moisture probes and an L-Band radiometer similar to Soil Moisture Passive and Active (SMAP) one. This site is among SMAP Cal/Val sites.

Soil moisture information was measured at seven different locations from 2012 to 2015. Hydra probes are used to measure six of these locations. This study utilizes the observations from insitu data and the L-Band radiometer close to ground (at 3 meters height) to validate and to compare soil moisture estimates from AMSR2. Analysis of the measurements and AMSR2 indicated a weak correlation with the hydra probes and a moderate correlation with Cosmic-ray Soil Moisture Observing System (COSMOS probes).

Several differences including the differences between pixel size and point measurements can cause these discrepancies. Some interpolation techniques are used to expand point measurements from 6 locations to AMSR2 footprint. Finally, the effect of penetration depth in microwave signal and inconsistencies with other ancillary data such as skin temperature is investigated to provide a better understanding in the analysis. The results show that the retrieval algorithm of AMSR2 is appropriate under certain circumstances. This validation algorithm and similar study will be conducted for SMAP mission.

Keywords: Remote Sensing, Soil Moisture, AMSR2, SMAP, L-Band.

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