An RFI Index to Quantify the Contamination of SMOS Data by Radio-Frequency Interference

• Published in: IEEE journal of selected topics in applied earth observations and remote sensing Vol. 9; no. 4; pp. 1577 - 1589
• Main Authors: Soldo, Yan, Khazaal, Ali, Cabot, Francois, Kerr, Yann H.
• Format: Journal Article
• Language: English
• Published: IEEE 01-04-2016
• Subjects: Contamination; Detection; Earth; Indexes; Instruments; kurtosis; noise injection radiometers (NIRs); Pollution measurement; radio-frequency interference (RFI); RFI index; Sea measurements; soil moisture and ocean salinity (SMOS); Temperature measurement; radio-frequency interference (RFI); soil moisture and ocean salinity (SMOS); noise injection radiometers (NIRs); Detection; kurtosis; RFI index
• ISSN: 1939-1404
• DOI: 10.1109/JSTARS.2015.2425542

The quality of science data provided by ESA soil moisture and ocean salinity (SMOS) satellite is degraded by the presence of artificial sources emitting in the protected part of the L-band, which is preserved for passive measurements by ITU regulation. These sources appear as high temperature points in SMOS brightness temperature products (e.g., Level 1C products), and may affect the retrievals of both SMOS (e.g., Level 2 products). In this contribution, a method is presented to quantify the impact of radio-frequency interference (RFI) on each SMOS snapshots, through the definition of an "RFI index" based on the number, position, and intensity of the RFI sources present in the snapshot. The main purpose of RFI indices is to provide the user of SMOS scientific data with information to ease the RFI filtering, thus achieving more accurate results. The comparison of RFI indices with the outputs of two different methods providing similar snapshot-wise information about RFI shows that the use of RFI indices reduces the probability of missed RFI detections, without increasing the risk for false alarms.