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Removal of Ionospheric Effects from Sigma Naught Images of the ALOS/PALSAR-2 Satellite

1
Earth Observation and Geoinformatics Division, National Institute for Space Research (INPE), São José dos Campos 12227-010, SP, Brazil
2
Department of Geography, School of Environment, Education and Development, University of Manchester, Oxford Road, Manchester M13 9PL, UK
*
Author to whom correspondence should be addressed.
Academic Editors: Jean-Christophe Cexus and Ali Khenchaf
Remote Sens. 2022, 14(4), 962; https://doi.org/10.3390/rs14040962
Received: 23 January 2022 / Revised: 8 February 2022 / Accepted: 9 February 2022 / Published: 16 February 2022
(This article belongs to the Special Issue Advances in SAR Image Processing and Applications)
The monitoring of forest degradation in the Amazon through radar remote sensing methodologies has increased intensely in recent years. Synthetic aperture radar (SAR) sensors that operate in L-band have an interesting response for land use and land cover (LULC) as well as for aboveground biomass (AGB). Depending on the magnetic and solar activities and seasonality, plasma bubbles in the ionosphere appear in the equatorial and tropical regions; these factors can cause stripes across SAR images, which disturb the interpretation and the classification. Our article shows a methodology to filter these stripes using Fourier fast transform (FFT), in which a stop-band filter removes this noise. In order to make this possible, we used Environment for Visualizing Images (ENVI), Sentinel Application Platform (SNAP), and Interactive Data Language (IDL). The final filtered scenes were classified by random forest (RF), and the results of this classification showed superior performance compared to the original scenes, showing this methodology can help to recover historic series of L-band images. View Full-Text
Keywords: ionospheric scintillation; ALOS/PALSAR-2; FFT filtering; SNAP; ENVI ionospheric scintillation; ALOS/PALSAR-2; FFT filtering; SNAP; ENVI
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MDPI and ACS Style

Gama, F.F.; Wiederkehr, N.C.; da Conceição Bispo, P. Removal of Ionospheric Effects from Sigma Naught Images of the ALOS/PALSAR-2 Satellite. Remote Sens. 2022, 14, 962. https://doi.org/10.3390/rs14040962

AMA Style

Gama FF, Wiederkehr NC, da Conceição Bispo P. Removal of Ionospheric Effects from Sigma Naught Images of the ALOS/PALSAR-2 Satellite. Remote Sensing. 2022; 14(4):962. https://doi.org/10.3390/rs14040962

Chicago/Turabian Style

Gama, Fábio Furlan, Natalia Cristina Wiederkehr, and Polyanna da Conceição Bispo. 2022. "Removal of Ionospheric Effects from Sigma Naught Images of the ALOS/PALSAR-2 Satellite" Remote Sensing 14, no. 4: 962. https://doi.org/10.3390/rs14040962

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