Search

Heavy mineral deposits occur in several coastal areas of the world, formed over a long period due to variations in mean sea level, wave action, and winds. These are the main sources of ilmenite (FeTiO3), which in turn is the source of more than 80% of the TiO2 produced and applied in various industries, most recently in nanotechnology. The present study mapped heavy mineral deposits on the coast of Rio Grande do Sul in southern Brazil using integrated proximal and orbital thermal infrared (TIR) remote sensing techniques. Mineral groups, such as oxides and silicates, have spectral features in the TIR wavelengths. Using laboratory spectroscopy at TIR using Nicolet 6700 Thermo Scientific Spectrometer, we measured the spectral signature of the local sample of heavy minerals (between 8 and 14 μm) and identified a diagnostic spectral feature at 10.75 μm. The signature was resampled to be compatible with the Advanced Spaceborne Thermal Emission Radiometer (ASTER) sensor bandwidth values and used as a reference endmember for the Spectral Angle Mapper (SAM) and Linear Spectral Unmixing (LSU) digital image classification algorithms. Thus, we identified the presence of the reference endmember (heavy minerals) in the pixels of the ASTER scene. In pixels classified by SAM as the presence of heavy minerals, LSU was applied to estimate the surface concentration within the pixel. The results showed a concentration of up to 20% of heavy minerals, with the highest concentration on the beach and dune fields. Opaque minerals such as ilmenite do not have spectral reflectance features in visible, near-infrared, and short-wave infrared, which makes their identification by remote sensing difficult. The present study showed that the integration of proximal and orbital as well as hyperspectral and multispectral thermal data can be considered as an alternative for detecting and mapping heavy minerals in coastal areas.

This paper presents the validation of the End Point Rate (EPR) tool for QGIS (EPR4Q), a tool built-in QGIS graphical modeler for calculating the shoreline change with the end point rate method. The EPR4Q tries to fill the gaps in user-friendly and free open-source tools for shoreline analysis in a geographic information system environment since the most used software—Digital Shoreline Analysis System (DSAS)—although being a free extension, it is created for commercial software. Additionally, the best free, open-source option to calculate EPR is called Analyzing Moving Boundaries Using R (AMBUR); since it is a robust and powerful tool, the complexity can restrict the accessibility and simple usage. The validation methodology consists of applying the EPR4Q, DSAS, and AMBUR with different types of shorelines found in nature, extracted from the US Geological Survey Open-File. The obtained results of each tool were compared with Pearson’s correlation coefficient. The validation results indicate that the EPR4Q tool acquired high correlation values with DSAS and AMBUR, reaching a coefficient of 0.98 to 1.00 on linear, extensive, and non-extensive shorelines, proving that the EPR4Q tool is ready to be freely used by the academic, scientific, engineering, and coastal managers communities worldwide.

This article presents the application of a methodology with geoprocessing tools to verify the existence (or not) of spatial conflicts between land use organizing instruments in the Casino Beach region and surrounding areas in the municipality of Rio Grande-RS. Therefore, the following legal instruments were analyzed: Planning Units, the Master Plan component, Ecological Economic Zoning Municipal- ZEEM, the Municipal Environmental Plan component and Map of Environmental Legal Basis generated by the authors based on Permanent-APPs Preservation Areas, Units Conservation and other areas with legally defined usage restrictions. We used the software Geographic Information Systems QGIS; one satellite image RapidEye® and vector data for processing. They resulting products were: land cover map, the environmental legal basis map and maps of conflicts based on crossing data. It was found that the class with largest soil coverage areas are fields (50.5%), followed by swamps and marshland (25.2%). And that 34.55% of the mapped area correspond to legally protected areas. As for the data conflicts, we found scale problems especially at the edges because the Planning Units are in scale of 1: 10,000; while ZEEM is 1: 100,000 and the Environmental Legal Basis is in scale 1: 25.000. Another problem encountered was the failure of the Planning Units for most of the study area. It was also found the importance of delimiting the PPAs and that the overlap of these environments with the other two policies would solve much of the spatial conflicts found. The fact is that there are two instruments of public policy for the same territory that are in conflict, which highlights the importance of integrating public institutions and geospatial data in the regulation and management of the territory.

A caracterização da superfície de neve é indispensável para compreender a dinâmica da Criosfera na patagônia austral do Chile, e torna-se mais importante quando consideramos que esta é uma área de difícil acesso devido às condições geográficas e climáticas extremas. Através do processamento de imagens orbitais dos sensores TM e OLI/TIRS presentes nos satélites Landsat 5 e 8, respectivamente, e a sua posterior classificação através do algoritmo de Classificação Supervisionada de Máxima Verossimilhança (CSMV) e da aplicação de threshold sobre o índice de Neve por Diferença Normalizada (NDSI), foram obtidas imagens binárias com as classes 1 (neve) e 0 (não-neve). Essas imagens foram vetorizadas e, então, calculadas as áreas correspondentes à superfície de neve em quilômetros-quadrados (km2). Esses resultados foram analisados e relacionados com dados climáticos de reanálise para as variáveis meteorológicas de temperatura e precipitação, obtendo um padrão de comportamento climático para cordilheira Darwin na última década. Os resultados mostram uma importante diminuição da superfície de neve, próxima a 50%, entre junho de 2005 e junho de 2016. A variabilidade climática, devida a ocorrência do El Niño durante 2015 e 2016, e a diminuição da influência da Oscilação Antártica sobre a região afetou diretamente a superfície de neve no setor ocidental da cordilheira Darwin. Finalmente, a classificação por NDSI foi mais precisa na diferenciação entre neve e nuvens, enquanto que o em termos de quantidade de superfície de neve calculada tanto o NDSI quanto a CSMV mostraram resultados próximos.

O propósito deste artigo é discutir a evolução dos métodos de simulação do retroespalhamento radar/SAR em massas de neve e gelo, compreendendo as abordagens físicas e empíricas neste processo. O presente trabalho busca compilar os diversos modelos de retroespalhamento radar/SAR de neve e gelo na faixa de microondas compreendida pela banda X propostos na literatura, comparando seus resultados, contribuições e limitações a fim de promover um material de orientação para pesquisa e emprego dos diversos modelos de retroespalhamento atualmente disponíveis. Assim, os principais modelos de retroespalhamento atuais serão descritos, implementados e finalmente comparados. Como fonte de validação dos modelos, serão considerados dados comuns de entrada, constituídos de dados estratigráficos e de temperatura da neve em um perfil de 2m de profundidade e dados radar/SAR Cosmo-SkyMed na banda X coletados na região da geleira Union no verão antártico de 2011-2012.