Persistent Scatterer interferometry (PSI) represents a powerful tool for the detection and monitoring of tiny surface deformations in vast areas, allowing a better understanding of its triggering mechanisms, planning of mitigation measures, as well as to find better solutions for social and environmental issues. However, there is no record hitherto of its use in active open pit mine in tropical rainforest environment. In this paper we evaluate the use of the PSI technique for the detection and monitoring of mine slope deformations in the N4W iron mine and its surroundings, Pará State, Northern Brazil. The PSI processing was performed with 18 ascending SAR scenes of the TerraSAR-X satellite acquired in the dry season of 2012. The results showed a significant number of widely distributed persistent scatterers. It was observed that most of the study area was stable during the time span. Nevertheless, high deformation rates (312 mm/year) were mapped over the mine waste piles, but do not offer any hazard, since they are expected displacements of meters in magnitude for these manmade land structures. Additionally, it was mapped tiny deformation rates in both the east and west flanks of pits 1 and 2. The main underlying reasons can be assigned to the accommodation phenomena of very poor rock masses, to the local geometric variations of the slope cuts, to the geological contact between ironstones and the country rocks, to the exploitation activities, as well as to the major geological structures. This study showed the applicability of the PSI technique using TerraSAR-X scenes in active open pit mines in tropical moist environment. However, the PSI technique is not capable in providing real-time warnings, and faces limitations due to SAR viewing geometry. In this sense, we strongly recommend the use of radar scenes acquired in both ascending and descending orbits, which would also provide a more complete understanding of the deformation patterns.

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.

Many researchers have shown the potential of Synthetic Aperture Radar (SAR) images for agricultural applications, particularly for monitoring regions with limitations in terms of acquiring cloud free optical images. Recently, Brazil and Germany began a feasibility study on the construction of an orbital L-band SAR sensor referred to as MAPSAR (Multi-Application Purpose SAR). This sensor provides L-band images in three spatial resolutions and polarimetric, interferometric and stereoscopic capabilities. Thus, studies are needed to evaluate the potential of future MAPSAR images. The objective of this study was to evaluate multipolarized MAPSAR images simulated by the airborne SAR-R99B sensor to distinguish coffee, cotton and pasture fields in Brazil. Discrimination among crops was evaluated through graphical and cluster analysis of mean backscatter values, considering single, dual and triple polarizations. Planting row direction of coffee influenced the backscatter and was divided into two classes: parallel and perpendicular to the sensor look direction. Single polarizations had poor ability to discriminate the crops. The overall accuracies were less than 59 %, but the understanding of the microwave interaction with the crops could be explored. Combinations of two polarizations could differentiate various fields of crops, highlighting the combination VV-HV that reached 78 % overall accuracy. The use of three polarizations resulted in 85.4 % overall accuracy, indicating that the classes pasture and parallel coffee were fully discriminated from the other classes. These results confirmed the potential of multipolarized MAPSAR images to distinguish the studied crops and showed considerable improvement in the accuracy of the results when the number of polarizations was increased

This paper describes the methodology applied to generate simulated multipolarized L-band SAR images of the MAPSAR (Multi-Application Purpose SAR) satellite from the airborne SAR R99B sensor (SIVAM System). MAPSAR is a feasibility study conducted by INPE (National Institute for Space Research) and DLR (German Aerospace Center) targeting a satellite L-band SAR innovative mission for assessment, management and monitoring of natural resources. Examples of simulated products and their applications are briefly discussed.

In the last two decades, the advent of Differential Interferometric Synthetic Aperture Radar (DInSAR) technique has opened new perspectives in the use of orbital imaging radar for quantitative surface deformation measurements. In the last few years this trend was considerably expanded through the use of large stacks of SAR images collected over the same area, instead of the classical two interferometric acquisitions used in the standard configurations. Advanced DInSAR techniques are nowadays more quantitative geodetic tools rather than simple qualitative tools available for land deformation detection. The paper reviews the main SAR and INSAR concepts, the current availability of orbital SAR data, and addresses PSinSAR (Persistent Scatterer InSAR) and BAS (Small Baseline Subset), two innovative advanced forms of DInSAR for the detection of millimetric ground displacements in various application fields. Finally, perspectives on the use of these technologies in Brazil are emphasized.

A produção mineral brasileira encontra-se entre as maiores do mundo, atuando como um dos pilares da sustentação econômica. O processo minerador envolve, entre outras etapas, a retirada do material sólido sem valor comercial agregado ao minério, denominado estéril. Após sua separação do minério, os estéreis são transportados e dispostos sob a forma de pilhas (PDEs), que sofrem assentamentos durante e após esta operação. A possibilidade de ocorrência de acidentes nessas estruturas e seus impactos ambientais requerem ferramentas eficientes para o planejamento e prevenção ou minimização de eventuais danos. Neste contexto o Sensoriamento Remoto, em especial o Radar de Abertura Sintética e suas técnicas são ferramentas eficientes para o monitoramento de deformações superficiais por permitir uma visão sinóptica de grandes áreas, imageamento periódico e pouca influência atmosférica. Assim, o objetivo deste trabalho consistiu em verificar a aplicabilidade da técnica DInSAR Time-Series associada à Intensity Tracking para a detecção de deformações superficiais nos taludes das PDEs NWI, W e SIV da Província Mineral de Carajás utilizando imagens TerraSAR-X. As técnicas mostraram potencial na detecção e estimativa do comportamento superficial das PDEs. Enquanto DInSAR-TS apresentou medidas quantitativas com precisão centimétrica, Intensity Tracking forneceu resultados de inferência acerca do comportamento superficial, recobrindo também regiões com ausência de resultados DInSAR-TS, embora com menor precisão.