The process of coastal erosion is a global problem that impacts approximately 70% of coastal regions of the Earth. It causes loss of property, infrastructure, and biodiversity, besides generating major economic impacts. Therefore, the analysis and monitoring of coastal erosion is an issue that needs to be addressed. In this sense, remotesensing data have been widely used in studies that evaluate the spatial and temporal changes of land use. In addition, the use of time series of satellite imagery applied in the investigation of changes in the Earth's coverage and its spatio-temporal pattern has been proven as an extremely efficient approach. Thus, remote sensing and geoprocessing are effective techniques to obtain continuous and dynamic information from coastal regions at different levels and scales. In this context, the main objective of this work was to create a prognostic model for the generation of future scenarios, based on the analysis of the spatialtemporal changes of the shorelines from past decades to the present, having as the pilot area the coast of the municipality of Icapuí, in the State of Ceará, Northeastern Brazil. For that, Statistical Regression technique was used. In addition, the techniques of Digital Image Processing and the extraction of the modified normalized difference water index were used. As a result, the prognosis of coastal erosion was generated for the year 2021, based on the time series of the years 1985, 1991, 1997, 2003, 2009, and 2015. After the extrapolation process, the results were validated through the mean absolute error. Furthermore, through the Python programming language and the OpenCV library, a computational solution was implemented to be executed in a Geographic Information Systems environment that automated the process of generating future prognostic and the extraction of the shoreline in a shapefile format.
Desertification is one of the world's direst environmental and ecological issue. However, the absence of reliable methods of identifying the processes of desertification is one of the main factors related to the critical study of this topic. This work has a goal to present a model capable of carrying out this task, by using estimation methods on temporal series of images. In this sense, a Landsat TM images were used to evaluate the degradation in Ouricuri, located in the State of Pernambuco, through the techniques of PDI (Image Processing), using the Normalized Difference Vegetation Index (NDVI) and the implementation of methods tendency estimation of temporal series. Thematic maps were produced of the degraded area between the years 1989 and 2009 to evaluate the evolution of this period of desertification, plus the estimation of soil degradation in the year 2019.
Atualmente, a agricultura moderna no Brasil, que antes era concentrada na região Centro-Sul, difundiu-se nos estados do Nordeste. O Piauí vivenciou uma rápida ocupação do Cerrado, devido a introdução de grandes projetos de agricultura e o município de Uruçuí se destaca na produção de grãos, principalmente a soja. O objetivo dessa pesquisa foi analisar a mudança da vegetação nativa ocasionada pela expansão agrícola do município de Uruçuí por meio do sensoriamento remoto. O processo foi dividido em fases, tais como: aquisição de dados, pré-processamento, extrapolação e classificação de imagens. Foram utilizadas imagens dos anos de 2003 do satélite Landsat 5 TM e de 2013 do Landsat 8 TM. As imagens desses dois anos foram georreferenciadas e fundidas através da técnica de mosaico com o programa QGIS. Por fim, foi produzido um mapa temático área degradada, para avaliar a evolução do processo de substituição da vegetação. Os dados obtidos nesse estudo indicaram que ocorreu a evolução das áreas de lavouras de grãos no município de Uruçuí. A análise das figuras revelou a substituição da vegetação nativa da região ocasionada principalmente pela crescente expansão agrícola. É de extrema importância o monitoramento dessas grandes áreas, para que seja possível quantificar o nível de exploração e reduzir os impactos ambientais.
A importância das zonas costeiras implica na necessidade de contínuos estudos relacionados ao monitoramento de seus processos. Neste contexto, a linha de costa representa uma das feições mais dinâmicas, e sua variabilidade é um indicador da erosão ou deposição costeira. A fim de avaliar as tendências de mudança da linha de costa do município de Icapuí, localizado no extremo leste do estado do Ceará, este trabalho envolveu a utilização de imagens orbitais do satélite Landsat, compondo uma série temporal de 30 anos com intervalos de cinco anos entre cada cena. Foram aplicados o Método de Mudança do Polígono e o Digital Shoreline Analysis System (DSAS) na caracterização da linha de costa, quantificando suas taxas de variação e balanço sedimentar em área. A área total foi setorizada em quatro porções, utilizando a morfologia costeira como critério de segmentação. Os resultados indicaram a existência de três hotspots de erosão e deposição, relacionados à desembocadura do riacho Arrombado, no setor leste; à desembocadura do estuário Barra Grande, que separa os setores centrais leste e oeste; e ao promontório de Ponta Grossa, que condiciona uma inflexão da linha de costa no setor oeste. Cada um destes setores apresenta dinâmica de deposição a barlamar e erosão a sotamar, com destaque para os processos acentuados de retrogradação entre as praias de Barreiras de Baixo e Barrinhas, no setor central oeste, e a forte dinâmica deposicional da praia de Ponta Grossa, no setor oeste. Identification of the erosive and depositional sectors of the Icapuí (CE) shoreline based on remote sensing products and geoprocessing techniques A B S T R A C TThe importance of coastal zones implies the need for continuous studies related to the monitoring of their processes. In this context, the shoreline represents one of the most dynamic features, and its variability is an indicator of erosion or coastal deposition. In order to evaluate the changing trends of the coast of the Icapuí city, located in the far east of the state of Ceará, this work involved the use of Landsat satellite orbital images, composing a 30-year time series with five-year intervals between each scene. The Polygon Change Method and the Digital Shoreline Analysis System (DSAS) were applied to characterize the shoreline, quantifying its variation rates and sedimentary balance in area. The total area was divided into four portions, using coastal morphology as a segmentation criterion. The results indicated the existence of three erosion and deposition hotspots, related to the Arrombado stream inlet, in the eastern sector; the Barra Grande estuary inlet, which separates the central east and west sectors; and the Ponta Grossa promontory, which conditions a shoreline inflection in the western sector. Each of these sectors has a deposition dynamic to updrift and erosion to downdrift, with prominence to the accentuated processes of retrogradation between the Barreiras de Baixo and Barrinhas beaches, in the central west sector, and the strong depositional dynamics of Ponta Grossa beach, in the west sector.Keywords: coastal erosion; shoreline change; temporal analysis.
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