SENTINEL-1 TIME SERIES ANALYSIS ON CENTRAL AMAZON FLOODS

DOI: https://doi.org/10.4215/rm2022.e21019

Abstract

This study aimed to analyze the dynamics of the flooded areas of the Sentinel 1-SAR time series in a section of the Central Amazon between September 26, 2016, and February 8, 2020. The total of images was 59 for each polarization. In addition, the study calculated the average ordinary flood line (ALOF) from the heights of the fluviometric rulers between the years 1967 to 2020 and compared it with the values present in the radar time series. The pre-processing of the Sentinel-1 time series in the VV and VH polarizations used the following methodological sequence: Apply Orbit File, Radiometric Calibration (σ0), Range-Doppler Terrain Correction, Speckle Filter, and conversion to decibels (dB). The previous analysis of the adaptive filters showed different results for the two polarizations, obtaining the best result for the VV polarization using the Frost filter with 3x3 and the VH polarization with the Lee filter 3x3. The extraction of water bodies and wetlands used a threshold value, making masks for the entire period. The most considerable extent of the floodable area occurred on June 17, 2019, with 6,611.86 km2, representing 16.42% of the SAR scene in the VH polarization and 6,443.19 km2, representing 16.10% of the SAR scene in the VV polarization. The relationship between the VH and VV wetlands to the ruler's height was satisfactory, with coefficients of determination (R2) of 0.79 in the VH polarization and of 0.64 in the VV polarization and a p-value less than 0.05. 

Keywords: Remote sensing; Radar; Mapping of Water Bodies. 

Author Biographies

Ivo Augusto Lopes Magalhães, University of Brasilia, Brasilia (DF), Brazil

PhD in Geography from the University of Brasília - UNB, researching the following areas: Remote Sensing, RADAR, Geoprocessing and Geostatistics at the Spatial Information Systems Laboratory - LSIE. Environmental Engineer graduated from IESA (2010). Possui Mestrado em Ciências Florestais by the Federal University of Espírito Santo - (UFES), in the research line: Remote sensing and management of hydrographic basins (2013). He has experience in the areas of Environmental Sciences and Geosciences with an emphasis on Geographic Information Systems - GIS, Remote Sensing, RADAR - SAR Image Processing, Photogrammetry, Geoprocessing, Management of Hydrographic Basins, Environmental Licensing, Recovery of Degraded Areas, Control of Environmental Disasters (Encostas, Quedas de Rochas, Enchentes and Inundação Landslides), Environmental Control Plan, Environmental Expertise and Management Plan of Conservation Units.

Osmar Abílio de Carvalho Junior, University of Brasilia, Brasilia (DF), Brazil

PhD in Geology from the University of Brasília (2000). He is currently an associate professor at the University of Brasília. He has experience in the area of Geosciences, with an emphasis in Geomorphology, working mainly on the following topics: remote sensing, geographic information system, hyperspectral, digital image processing, and geomorphology.

Renato Fontes Guimarães, University of Brasilia, Brasilia (DF), Brazil.

PhD in Geology from the Federal University of Rio de Janeiro (2000). Currently he is Full Professor of the Department of Geography of the University of Brasília. He has experience in the area of Geosciences, with an emphasis in Geomorphology, working mainly on the following topics: remote sensing, geomorphology, GIS, mathematical modeling and geoprocessing.

Roberto Arnaldo Trancoso Gomes, University of Brasilia, Brasilia (DF), Brazil.

PhD in Geography from the Federal University of Rio de Janeiro (2006). He is currently Associate Professor of the Geography Department of the University of Brasília and Professor of the Post-Graduation Program in Geography of the University of Brasília. He is editor of Revista Espaço & Geografia and reviewer in various scientific journals (national and international). He has experience in the area of Geosciences and Geomorphology, with an emphasis on geotechnologies, mapping, process modeling, digital image processing, artificial intelligence.

References

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Published
27/12/2022
How to Cite
MAGALHÃES, Ivo Augusto Lopes et al. SENTINEL-1 TIME SERIES ANALYSIS ON CENTRAL AMAZON FLOODS. Mercator, Fortaleza, v. 21, dec. 2022. ISSN 1984-2201. Available at: <http://www.mercator.ufc.br/mercator/article/view/e21019>. Date accessed: 25 apr. 2024. doi: https://doi.org/10.4215/rm2022.e21019.
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Vol 21 (2022)
Section
ARTICLES
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