Fábio Gama - Academia.edu (original) (raw)
Papers by Fábio Gama
Remote Sensing MDPI, 2024
This study aims to investigate the occurrence of surface displacements in the Canto do Amaro (CAM... more This study aims to investigate the occurrence of surface displacements in the Canto do Amaro (CAM) onshore oil field, situated in Rio Grande do Norte, Brazil, using Sentinel-1 data. The persistent scatterer interferometry (PSI) technique was used to perform the analysis based on 42 Sentinel-1 images, acquired from 23 July 2020 to 21 December 2021. Moreover, information regarding the structural geology of the study area was collected by referencing existing literature datasets. Additionally, a study of the water, gas, and oil production dynamics in the research site
was conducted, employing statistical analysis of publicly available well production data. The PSI points results were geospatially correlated with the closest oil well production data and the structural geology information. The PSI results indicate displacement rates from −20.93 mm/year up to 14.63 mm/year in the CAM region. However, approximately 90% of the deformation remained in the range of −5.50 mm/year to 4.95 mm/year, indicating low levels of ground displacement in the designated research area. No geospatial correlation was found between the oil production data and the zones of maximum deformation. In turn, ground displacement demonstrates geospatial correlation with geological structures such as strike-slip and rift faults, suggesting a tectonic movement processes. The PSI results provided a comprehensive overview of ground displacement in the Canto do Amaro field, with millimeter-level accuracy and highlighting its potential as a complementary tool to field investigations.
Journal of Applied Remote Sensing, Feb 6, 2023
Brazilian Journal of Geology, Apr 1, 2017
Carajás Mineral Province, Amazon region, is the most important one in Brazil. Vale S.A. Company h... more Carajás Mineral Province, Amazon region, is the most important one in Brazil. Vale S.A. Company has the right to operate in the area of the N5E mine. The work is conducted on rock alteration products of low geomechanical quality related to sandstones, siltstones, and a lateritic cover. In order to monitor ground deformation, 33 TerraSAR-X images covering the period of March 2012-April 2013 were used in the investigation. An interferometric synthetic aperture radar (InSAR) approach based on permanent scatterer interferometry (PSI) using an interferometric point target analysis algorithm was applied. Results demonstrated that most of the area was considered stable during the time span of the image acquisition. However, persistent scatterers (PSs) with high deformation rates were mapped over a landfill probably related to settlements. To validate the PSI data, graphs were generated with the displaced information based on topographic measurements in the field. The graphs showed that the surface deformations during TSX-1 runway coverage are within the miner's safety threshold and do not present a risk of major problems. The PSI data provided a synoptic and detailed view of the deformation process that affects the mining complex without the need of field campaign or instrumentation.
Geocarto International, Jun 9, 2020
Synthetic aperture radar (SAR) data has been an alternative for monitoring ground targets, especi... more Synthetic aperture radar (SAR) data has been an alternative for monitoring ground targets, especially in areas with cloud cover. This study evaluates the potential of Sentinel-1A attributes for mapping land use and land cover (LULC) in a region of the Brazilian Amazon, using two different machine learning classifiers: Random Forest (RF) and Support Vector Machine (SVM). Different scenarios were used that combined backscattering, polarimetry, and interferometry to the classification process, which was divided into two phases to improve the results. The RF shows superiority over the SVM for almost all scenarios for the two phases of the mapping. The scenario with all data, presented the best results with both classifiers. The final maps with RF and SVM, obtained a global accuracy of 82.7% and 74.5%, respectively. This study demonstrated the potential of Sentinel-1 to map LULC classes in the Amazon region using a classification in two phases.
Acta Geotechnica, Apr 14, 2023
Forests
Polarimetric synthetic aperture radar (SAR) images are essential to understand forest structure a... more Polarimetric synthetic aperture radar (SAR) images are essential to understand forest structure and plan forest inventories with the purpose of natural resource management and environmental conservation efforts. We developed a method for estimating above-ground biomass (AGB) from power and phase-radar attributes in L-band images. The model was based on the variables “Pv” (from Freeman–Durden decomposition) and “σ°HH”, complemented by the attributes of Touzi decomposition “αS2”, “τm”, “ ΦS3”, and “ ΦS2”. The analyses demonstrated the contribution of volumetric, multiple, and direct scattering resulting from the interaction between the signal and the random structure of canopies and their forest biomass. The proposed model had good predictive capacity and a positive correlation (R2 = 0.67 and = 0.81, respectively), with Syx = 56.9 Mg ha−1 and a low average estimation error of 7.5% at R2 = 0.81 in the validation. An additional exploratory analysis of the parallel polarimetric responses...
Mining
This article presents an investigation of ground movement measurements based on a combination of ... more This article presents an investigation of ground movement measurements based on a combination of TerraSAR-X and Sentinel-1 data, in opposite tracks, aiming to detect ground de-formation of the remaining dikes of Germano mine, after the Fundão dam collapse. The differential interferometry technique SBAS (Small Baseline Subset) was applied to obtain the deformation of the surface in different Line of Sight (LoS), in order to carry out the vector decomposition and generate the deformation measurements in the vertical and horizontal directions. A set of 37 single-look complex (SLC) images of TerraSAR-X (TSX), acquired during the period from 19 February 2016 to 15 May 2017, and 37 SLC images of Sentinel-1, acquired from 8 February 2016 to 15 May 2017, were used to perform this investigation. For the TerraSAR-X interferometric processing, a coherence threshold of 40%, 4 looks in range and 2 looks in azimuth, 1200 m of atmospheric filter, and 10 % of max normal baseline of the critical wer...
Remote Sensing, 2022
The monitoring of forest degradation in the Amazon through radar remote sensing methodologies has... more 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 ...
Remote Sensing, 2020
Differential Interferometric SAR (DInSAR) has been used to monitor surface deformations in open p... more Differential Interferometric SAR (DInSAR) has been used to monitor surface deformations in open pit mines and tailings dams. In this paper, ground deformations have been detected on the area of tailings Dam-I at the Córrego do Feijão Mine (Brumadinho, Brazil) before its catastrophic failure occurred on 25 January 2019. Two techniques optimized for different scattering models, SBAS (Small BAseline Subset) and PSI (Persistent Scatterer Interferometry), were used to perform the analysis based on 26 Sentinel-1B images in Interferometric Wide Swath (IW) mode, which were acquired on descending orbits from 03 March 2018 to 22 January 2019. A WorldDEM Digital Surface Model (DSM) product was used to remove the topographic phase component. The results provided by both techniques showed a synoptic and informative view of the deformation process affecting the study area, with the detection of persistent trends of deformation on the crest, middle, and bottom sectors of the dam face until its col...
Copernicus is the World’s largest single Earth Observation (EO) programme, whose satellite conste... more Copernicus is the World’s largest single Earth Observation (EO) programme, whose satellite constellations are planned to be launched between 2014 and 2025. Among the constellations, Sentinel-1 (S-1) is a C-band SAR able to support land cover mapping. Although optical data are commonly used for land cover monitoring, the low availability of cloud-free scenes along the year hinders the mapping process. In such a way, S-1 presents an important source of data, able of providing all-weather and day-and-night imagery of EO. In this study, we investigate the potential of using S-1 data to distinguish targets in Remote Sensing images in three different Brazilian biomes, Amazon, Cerrado, and Atlantic Forest. Based on that, we proposed a methodology to classify SAR images, which was validated considering a different area from the ones used for sampling purposes. The results showed that through S-1 data, it is possible to detect mainly water and urban area targets, with overall accuracy of 0.9...
Sandbanks represent a danger to river and sea navigation due to the significant damage they can c... more Sandbanks represent a danger to river and sea navigation due to the significant damage they can cause to ships, crews and passengers. This work aimed to develop a methodology for the automatic identification of sandbanks located in an Amazonian estuarine region (Baía do Guajará) using synthetic aperture radar (SAR) image and deep convolutional neural networks (Deep Learning) in order to assist the obstacles monitoring in the local navigation. The results demonstrated significant differences in the use of the SAR polarization for the monitoring of the sandbanks, as well as elevated accuracy (99,6%) for automatic identification through the convolutional neural network. Resumo. Bancos de areia representam um perigo à navegação fluvial e marítima devido aos danos significativos que podem gerar para as embarcações, tripulações e passageiros. Este trabalho buscou desenvolver uma metodologia para a identificação automática de bancos de areia situados em uma região estuarina Amazônica (Baía...
Anuário do Instituto de Geociências - UFRJ, 2020
A floresta amazônica é considerada um dos maiores reservatórios de carbono da Terra. No entanto, ... more A floresta amazônica é considerada um dos maiores reservatórios de carbono da Terra. No entanto, mudanças antrópicas indiscriminadas no uso e cobertura da terra, como a conversão da floresta em áreas agrícolas e pastagens, provocam grandes impactos ambientais na floresta. A utilização de técnicas que auxiliam o mapeamento do uso e cobertura da terra se torna cada vez mais necessária. Índices como o NDVI (Índice de Vegetação por Diferença Normalizada) e MLME (Modelo Linear de Mistura Espectral) são amplamente utilizados para estudos da vegetação, por permitirem analisar e realçar parâmetros e feições em imagens de sensoriamento remoto. Desse modo, o objetivo deste trabalho foi avaliar o desempenho do mapeamento do uso e cobertura da terra (LULC), utilizando dados do satélite Sentinel-2B, adicionado com o índice de vegetação NDVI e com o MLME, utilizando o classificador Random Forest (RF). Para a realização deste estudo, foram utilizadas imagens do sensor MSI do Sentinel-2B e calculad...
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020
This paper aims to map crops in two Brazilian municipalities, Luís Eduardo Magalhães (LEM) and Ca... more This paper aims to map crops in two Brazilian municipalities, Luís Eduardo Magalhães (LEM) and Campo Verde, using dualpolarimetric Sentinel-1A images. The specific objectives were: (1) to evaluate the accuracy gain in the crop classification using Sentinel-1A multitemporal data backscatter coefficients and ratio (σ 0 VH, σ 0 VV and, σ 0 VH/σ 0 VV, denominate BS group) in comparison to the addition of polarimetric attributes (σ 0 VH, σ 0 VV, σ 0 VH/σ 0 VV, H, and α, denominate BP group) and; (2) to assess the accuracy gain in the earliest crop classification, creating new scenarios with the addition of the new SAR data together with the previous images for each date and group (BS and BP) during the crop development. For BS and BP groups, 13 e 10 scenarios were analyzed in LEM and Campo Verde, respectively. For the classification process, we used the Random Forest (RF) algorithm. In the LEM site, the best results for BS and BP groups were equivalent (overall accuracy: ~82%), while for the Campo Verde site, the classification accuracy for the BP group (overall accuracy: ~80%) was 2% higher than the BS group. The addition of new images during the crop development period increased the earliest crop classification overall accuracy, stabilizing from mid-February in LEM and mid-December in Campo Verde, after 10 and 8 images, respectively. After these periods, the gain in classification accuracy was small with the addition of new images. In general, our results suggest the backscattering coefficients and polarimetric attributes extracted from the Sentinel-1A imagery exhibited a great performance to discriminate croplands.
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015
Now spanning five simultaneous open-pit operations with exploration carried out through open pit ... more Now spanning five simultaneous open-pit operations with exploration carried out through open pit benching, Carajás complex encompasses the world´s largest iron reserves. Open pit mining operations in the area can lead to slope instabilities with risks to personnel, equipment and production due to intense excavations in rock products of low geomechanical quality, blasting practices and heavy precipitation. Thus, an effective prediction and management of surface deformations should be a key concern for the mining operations. The ground displacement monitoring techniques in Carajás include surface measurement techniques at discrete points (total station/reflective prisms) and over area using SSR (Slope Stability Radar, a ground based radar). On the other hand, DInSAR techniques are receiving relevance in the mining industry for reasons such a synoptic and continuous coverage without the need for ground instrumentation and a point-to-point good accuracy of measuring displacements (millimeter to centimeter scale) over a dense grid. Using a stack of 33 StripMap TerraSAR-X images acquired over Carajás covering the time span from March 2012 to April 2013, a monitoring approach is discussed based on the complementary use of information provided by DInSAR (DInSAR Time-Series and Persistent Scatterer Interferometry) and surface measuring techniques (total station/prisms, ground-based radar).
IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477)
Fechar. Referência Completa. Tipo da Referência, Conference Proceedings. Repositório, sid.inpe.br... more Fechar. Referência Completa. Tipo da Referência, Conference Proceedings. Repositório, sid.inpe.br/marciana/2003/08.26.16.05. Metadados, sid.inpe.br/marciana/2003/08.26.16.05.12. Site, mtc-m12.sid.inpe.br. ISBN/ISSN, 0-7803-7929. Chave Secundária, INPE-9918-PRE/5480 ...
Remote Sensing - MDPI, 2022
The monitoring of forest degradation in the Amazon through radar remote sensing methodologies has... more 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.
Mining - MDPI, 2023
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Revista Brasileira de Cartografia, 2016
A producao mineral brasileira encontra-se entre as maiores do mundo, atuando como um dos pilares ... more A producao mineral brasileira encontra-se entre as maiores do mundo, atuando como um dos pilares da sustentacao economica. O processo minerador envolve, entre outras etapas, a retirada do material solido sem valor comercial agregado ao minerio, denominado esteril. Apos sua separacao do minerio, os estereis sao transportados e dispostos sob a forma de pilhas (PDEs), que sofrem assentamentos durante e apos esta operacao. A possibilidade de ocorrencia de acidentes nessas estruturas e seus impactos ambientais requerem ferramentas eficientes para o planejamento e prevencao ou minimizacao de eventuais danos. Neste contexto o Sensoriamento Remoto, em especial o Radar de Abertura Sintetica e suas tecnicas sao ferramentas eficientes para o monitoramento de deformacoes superficiais por permitir uma visao sinoptica de grandes areas, imageamento periodico e pouca influencia atmosferica. Assim, o objetivo deste trabalho consistiu em verificar a aplicabilidade da tecnica DInSAR Time-Series associ...
Remote Sensing, 2016
This work presents an investigation to determine ground deformation based on an integration of DI... more This work presents an investigation to determine ground deformation based on an integration of DInSAR Time-Series (DTS) and Persistent Scatterer Interferometry (PSI) techniques aiming at detecting high rates of linear and non-linear ground movement. The combined techniques were applied in an open pit iron mine located in Carajás Mineral Province (Brazilian Amazon region), using a set of 33 TerraSAR-X-1 images acquired from March 2012 to April 2013 when, due to a different deformation behavior during the dry and wet seasons in the Amazon region, a non-linear deformation was detected. The DTS analysis was performed on a stack of multi-look unwrapped interferograms using an extension of the SVD (Singular Value Decomposition), where a set of additional weighted constraints on the acceleration of the displacement was incorporated to control the smoothness of the time-series solutions, whose objective was to correct the atmospheric phase artifacts. The height errors and the deformation history provided by the DTS technique were used as previous information to perform the PSI analysis. This procedure improved the capability of the PSI technique to detect non-linear movement as well as to increase the numbers of point density of the final results. The results of the combined techniques are presented and compared with total station/prisms and ground-based radar (GBR) measurements.
Remote Sensing MDPI, 2024
This study aims to investigate the occurrence of surface displacements in the Canto do Amaro (CAM... more This study aims to investigate the occurrence of surface displacements in the Canto do Amaro (CAM) onshore oil field, situated in Rio Grande do Norte, Brazil, using Sentinel-1 data. The persistent scatterer interferometry (PSI) technique was used to perform the analysis based on 42 Sentinel-1 images, acquired from 23 July 2020 to 21 December 2021. Moreover, information regarding the structural geology of the study area was collected by referencing existing literature datasets. Additionally, a study of the water, gas, and oil production dynamics in the research site
was conducted, employing statistical analysis of publicly available well production data. The PSI points results were geospatially correlated with the closest oil well production data and the structural geology information. The PSI results indicate displacement rates from −20.93 mm/year up to 14.63 mm/year in the CAM region. However, approximately 90% of the deformation remained in the range of −5.50 mm/year to 4.95 mm/year, indicating low levels of ground displacement in the designated research area. No geospatial correlation was found between the oil production data and the zones of maximum deformation. In turn, ground displacement demonstrates geospatial correlation with geological structures such as strike-slip and rift faults, suggesting a tectonic movement processes. The PSI results provided a comprehensive overview of ground displacement in the Canto do Amaro field, with millimeter-level accuracy and highlighting its potential as a complementary tool to field investigations.
Journal of Applied Remote Sensing, Feb 6, 2023
Brazilian Journal of Geology, Apr 1, 2017
Carajás Mineral Province, Amazon region, is the most important one in Brazil. Vale S.A. Company h... more Carajás Mineral Province, Amazon region, is the most important one in Brazil. Vale S.A. Company has the right to operate in the area of the N5E mine. The work is conducted on rock alteration products of low geomechanical quality related to sandstones, siltstones, and a lateritic cover. In order to monitor ground deformation, 33 TerraSAR-X images covering the period of March 2012-April 2013 were used in the investigation. An interferometric synthetic aperture radar (InSAR) approach based on permanent scatterer interferometry (PSI) using an interferometric point target analysis algorithm was applied. Results demonstrated that most of the area was considered stable during the time span of the image acquisition. However, persistent scatterers (PSs) with high deformation rates were mapped over a landfill probably related to settlements. To validate the PSI data, graphs were generated with the displaced information based on topographic measurements in the field. The graphs showed that the surface deformations during TSX-1 runway coverage are within the miner's safety threshold and do not present a risk of major problems. The PSI data provided a synoptic and detailed view of the deformation process that affects the mining complex without the need of field campaign or instrumentation.
Geocarto International, Jun 9, 2020
Synthetic aperture radar (SAR) data has been an alternative for monitoring ground targets, especi... more Synthetic aperture radar (SAR) data has been an alternative for monitoring ground targets, especially in areas with cloud cover. This study evaluates the potential of Sentinel-1A attributes for mapping land use and land cover (LULC) in a region of the Brazilian Amazon, using two different machine learning classifiers: Random Forest (RF) and Support Vector Machine (SVM). Different scenarios were used that combined backscattering, polarimetry, and interferometry to the classification process, which was divided into two phases to improve the results. The RF shows superiority over the SVM for almost all scenarios for the two phases of the mapping. The scenario with all data, presented the best results with both classifiers. The final maps with RF and SVM, obtained a global accuracy of 82.7% and 74.5%, respectively. This study demonstrated the potential of Sentinel-1 to map LULC classes in the Amazon region using a classification in two phases.
Acta Geotechnica, Apr 14, 2023
Forests
Polarimetric synthetic aperture radar (SAR) images are essential to understand forest structure a... more Polarimetric synthetic aperture radar (SAR) images are essential to understand forest structure and plan forest inventories with the purpose of natural resource management and environmental conservation efforts. We developed a method for estimating above-ground biomass (AGB) from power and phase-radar attributes in L-band images. The model was based on the variables “Pv” (from Freeman–Durden decomposition) and “σ°HH”, complemented by the attributes of Touzi decomposition “αS2”, “τm”, “ ΦS3”, and “ ΦS2”. The analyses demonstrated the contribution of volumetric, multiple, and direct scattering resulting from the interaction between the signal and the random structure of canopies and their forest biomass. The proposed model had good predictive capacity and a positive correlation (R2 = 0.67 and = 0.81, respectively), with Syx = 56.9 Mg ha−1 and a low average estimation error of 7.5% at R2 = 0.81 in the validation. An additional exploratory analysis of the parallel polarimetric responses...
Mining
This article presents an investigation of ground movement measurements based on a combination of ... more This article presents an investigation of ground movement measurements based on a combination of TerraSAR-X and Sentinel-1 data, in opposite tracks, aiming to detect ground de-formation of the remaining dikes of Germano mine, after the Fundão dam collapse. The differential interferometry technique SBAS (Small Baseline Subset) was applied to obtain the deformation of the surface in different Line of Sight (LoS), in order to carry out the vector decomposition and generate the deformation measurements in the vertical and horizontal directions. A set of 37 single-look complex (SLC) images of TerraSAR-X (TSX), acquired during the period from 19 February 2016 to 15 May 2017, and 37 SLC images of Sentinel-1, acquired from 8 February 2016 to 15 May 2017, were used to perform this investigation. For the TerraSAR-X interferometric processing, a coherence threshold of 40%, 4 looks in range and 2 looks in azimuth, 1200 m of atmospheric filter, and 10 % of max normal baseline of the critical wer...
Remote Sensing, 2022
The monitoring of forest degradation in the Amazon through radar remote sensing methodologies has... more 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 ...
Remote Sensing, 2020
Differential Interferometric SAR (DInSAR) has been used to monitor surface deformations in open p... more Differential Interferometric SAR (DInSAR) has been used to monitor surface deformations in open pit mines and tailings dams. In this paper, ground deformations have been detected on the area of tailings Dam-I at the Córrego do Feijão Mine (Brumadinho, Brazil) before its catastrophic failure occurred on 25 January 2019. Two techniques optimized for different scattering models, SBAS (Small BAseline Subset) and PSI (Persistent Scatterer Interferometry), were used to perform the analysis based on 26 Sentinel-1B images in Interferometric Wide Swath (IW) mode, which were acquired on descending orbits from 03 March 2018 to 22 January 2019. A WorldDEM Digital Surface Model (DSM) product was used to remove the topographic phase component. The results provided by both techniques showed a synoptic and informative view of the deformation process affecting the study area, with the detection of persistent trends of deformation on the crest, middle, and bottom sectors of the dam face until its col...
Copernicus is the World’s largest single Earth Observation (EO) programme, whose satellite conste... more Copernicus is the World’s largest single Earth Observation (EO) programme, whose satellite constellations are planned to be launched between 2014 and 2025. Among the constellations, Sentinel-1 (S-1) is a C-band SAR able to support land cover mapping. Although optical data are commonly used for land cover monitoring, the low availability of cloud-free scenes along the year hinders the mapping process. In such a way, S-1 presents an important source of data, able of providing all-weather and day-and-night imagery of EO. In this study, we investigate the potential of using S-1 data to distinguish targets in Remote Sensing images in three different Brazilian biomes, Amazon, Cerrado, and Atlantic Forest. Based on that, we proposed a methodology to classify SAR images, which was validated considering a different area from the ones used for sampling purposes. The results showed that through S-1 data, it is possible to detect mainly water and urban area targets, with overall accuracy of 0.9...
Sandbanks represent a danger to river and sea navigation due to the significant damage they can c... more Sandbanks represent a danger to river and sea navigation due to the significant damage they can cause to ships, crews and passengers. This work aimed to develop a methodology for the automatic identification of sandbanks located in an Amazonian estuarine region (Baía do Guajará) using synthetic aperture radar (SAR) image and deep convolutional neural networks (Deep Learning) in order to assist the obstacles monitoring in the local navigation. The results demonstrated significant differences in the use of the SAR polarization for the monitoring of the sandbanks, as well as elevated accuracy (99,6%) for automatic identification through the convolutional neural network. Resumo. Bancos de areia representam um perigo à navegação fluvial e marítima devido aos danos significativos que podem gerar para as embarcações, tripulações e passageiros. Este trabalho buscou desenvolver uma metodologia para a identificação automática de bancos de areia situados em uma região estuarina Amazônica (Baía...
Anuário do Instituto de Geociências - UFRJ, 2020
A floresta amazônica é considerada um dos maiores reservatórios de carbono da Terra. No entanto, ... more A floresta amazônica é considerada um dos maiores reservatórios de carbono da Terra. No entanto, mudanças antrópicas indiscriminadas no uso e cobertura da terra, como a conversão da floresta em áreas agrícolas e pastagens, provocam grandes impactos ambientais na floresta. A utilização de técnicas que auxiliam o mapeamento do uso e cobertura da terra se torna cada vez mais necessária. Índices como o NDVI (Índice de Vegetação por Diferença Normalizada) e MLME (Modelo Linear de Mistura Espectral) são amplamente utilizados para estudos da vegetação, por permitirem analisar e realçar parâmetros e feições em imagens de sensoriamento remoto. Desse modo, o objetivo deste trabalho foi avaliar o desempenho do mapeamento do uso e cobertura da terra (LULC), utilizando dados do satélite Sentinel-2B, adicionado com o índice de vegetação NDVI e com o MLME, utilizando o classificador Random Forest (RF). Para a realização deste estudo, foram utilizadas imagens do sensor MSI do Sentinel-2B e calculad...
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020
This paper aims to map crops in two Brazilian municipalities, Luís Eduardo Magalhães (LEM) and Ca... more This paper aims to map crops in two Brazilian municipalities, Luís Eduardo Magalhães (LEM) and Campo Verde, using dualpolarimetric Sentinel-1A images. The specific objectives were: (1) to evaluate the accuracy gain in the crop classification using Sentinel-1A multitemporal data backscatter coefficients and ratio (σ 0 VH, σ 0 VV and, σ 0 VH/σ 0 VV, denominate BS group) in comparison to the addition of polarimetric attributes (σ 0 VH, σ 0 VV, σ 0 VH/σ 0 VV, H, and α, denominate BP group) and; (2) to assess the accuracy gain in the earliest crop classification, creating new scenarios with the addition of the new SAR data together with the previous images for each date and group (BS and BP) during the crop development. For BS and BP groups, 13 e 10 scenarios were analyzed in LEM and Campo Verde, respectively. For the classification process, we used the Random Forest (RF) algorithm. In the LEM site, the best results for BS and BP groups were equivalent (overall accuracy: ~82%), while for the Campo Verde site, the classification accuracy for the BP group (overall accuracy: ~80%) was 2% higher than the BS group. The addition of new images during the crop development period increased the earliest crop classification overall accuracy, stabilizing from mid-February in LEM and mid-December in Campo Verde, after 10 and 8 images, respectively. After these periods, the gain in classification accuracy was small with the addition of new images. In general, our results suggest the backscattering coefficients and polarimetric attributes extracted from the Sentinel-1A imagery exhibited a great performance to discriminate croplands.
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015
Now spanning five simultaneous open-pit operations with exploration carried out through open pit ... more Now spanning five simultaneous open-pit operations with exploration carried out through open pit benching, Carajás complex encompasses the world´s largest iron reserves. Open pit mining operations in the area can lead to slope instabilities with risks to personnel, equipment and production due to intense excavations in rock products of low geomechanical quality, blasting practices and heavy precipitation. Thus, an effective prediction and management of surface deformations should be a key concern for the mining operations. The ground displacement monitoring techniques in Carajás include surface measurement techniques at discrete points (total station/reflective prisms) and over area using SSR (Slope Stability Radar, a ground based radar). On the other hand, DInSAR techniques are receiving relevance in the mining industry for reasons such a synoptic and continuous coverage without the need for ground instrumentation and a point-to-point good accuracy of measuring displacements (millimeter to centimeter scale) over a dense grid. Using a stack of 33 StripMap TerraSAR-X images acquired over Carajás covering the time span from March 2012 to April 2013, a monitoring approach is discussed based on the complementary use of information provided by DInSAR (DInSAR Time-Series and Persistent Scatterer Interferometry) and surface measuring techniques (total station/prisms, ground-based radar).
IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477)
Fechar. Referência Completa. Tipo da Referência, Conference Proceedings. Repositório, sid.inpe.br... more Fechar. Referência Completa. Tipo da Referência, Conference Proceedings. Repositório, sid.inpe.br/marciana/2003/08.26.16.05. Metadados, sid.inpe.br/marciana/2003/08.26.16.05.12. Site, mtc-m12.sid.inpe.br. ISBN/ISSN, 0-7803-7929. Chave Secundária, INPE-9918-PRE/5480 ...
Remote Sensing - MDPI, 2022
The monitoring of forest degradation in the Amazon through radar remote sensing methodologies has... more 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.
Mining - MDPI, 2023
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Revista Brasileira de Cartografia, 2016
A producao mineral brasileira encontra-se entre as maiores do mundo, atuando como um dos pilares ... more A producao mineral brasileira encontra-se entre as maiores do mundo, atuando como um dos pilares da sustentacao economica. O processo minerador envolve, entre outras etapas, a retirada do material solido sem valor comercial agregado ao minerio, denominado esteril. Apos sua separacao do minerio, os estereis sao transportados e dispostos sob a forma de pilhas (PDEs), que sofrem assentamentos durante e apos esta operacao. A possibilidade de ocorrencia de acidentes nessas estruturas e seus impactos ambientais requerem ferramentas eficientes para o planejamento e prevencao ou minimizacao de eventuais danos. Neste contexto o Sensoriamento Remoto, em especial o Radar de Abertura Sintetica e suas tecnicas sao ferramentas eficientes para o monitoramento de deformacoes superficiais por permitir uma visao sinoptica de grandes areas, imageamento periodico e pouca influencia atmosferica. Assim, o objetivo deste trabalho consistiu em verificar a aplicabilidade da tecnica DInSAR Time-Series associ...
Remote Sensing, 2016
This work presents an investigation to determine ground deformation based on an integration of DI... more This work presents an investigation to determine ground deformation based on an integration of DInSAR Time-Series (DTS) and Persistent Scatterer Interferometry (PSI) techniques aiming at detecting high rates of linear and non-linear ground movement. The combined techniques were applied in an open pit iron mine located in Carajás Mineral Province (Brazilian Amazon region), using a set of 33 TerraSAR-X-1 images acquired from March 2012 to April 2013 when, due to a different deformation behavior during the dry and wet seasons in the Amazon region, a non-linear deformation was detected. The DTS analysis was performed on a stack of multi-look unwrapped interferograms using an extension of the SVD (Singular Value Decomposition), where a set of additional weighted constraints on the acceleration of the displacement was incorporated to control the smoothness of the time-series solutions, whose objective was to correct the atmospheric phase artifacts. The height errors and the deformation history provided by the DTS technique were used as previous information to perform the PSI analysis. This procedure improved the capability of the PSI technique to detect non-linear movement as well as to increase the numbers of point density of the final results. The results of the combined techniques are presented and compared with total station/prisms and ground-based radar (GBR) measurements.