Navegando por Assunto "Zona Costeira"

Agora exibindo 1 - 5 de 5

Acesso aberto (Open Access)
Conflito e gestão ambiental na zona costeira amazônica: o caso da vila de Camará, reserva extrativista (RESEX) marinha mestre Lucindo, Marapanim-Pará-Amazônia-Brasil
(Universidade da Amazônia, 2019-11) SANTOS, Márcia Cristina; LOPES, Luis Otávio do Canto; BASTOS, Rodolpho Zahluth
Acesso aberto (Open Access)
Conflitos socioambientais e limites da gestão compartilhada em unidade de conservação na zona costeira amazônica
(Universidade de Santa Cruz do Sul, 2020) LOPES, Luís Otávio do Canto; VASCONCELLOS SOBRINHO, Mário; VASCONCELLOS, Ana Maria de Albuquerque; FERREIRA, Luciana Rodrigues; BARRETA, Ana Ialis
The paper discusses the emergence of socio-environmental conflicts and the limits of shared territory management in Brazilian Amazonian coastal zone. Particularly, the article debates socio-environmental conflicts and the limits of shared management in 3 (three) Conservation Units (UC) in the coastal zone of Pará state, precisely: RESEX Mãe Grande de Curuçá, RESEX Mestre Lucindo and APA Algodoal- Maiandeua. Theoretically, the paper is based on the concepts of socio-environmental conflict and shared management, the latter within the analytical field of social management. Methodologically, it is a study based on action research supported by method of participant observation and techniques of semi structured interviews. For data examination, it was used the method of network analysis. The article demonstrates the existence of four categories of conflicts: (1) first, conflicts related to economic enterprises, (2) second, those related to the degradation of the environment and natural resources, (3) third, conflicts that arise from local economic and occupational practices and (4) fourth, those resulting of legal and social inferences. The different categories and types of conflict demonstrate the complexity that management councils face in the shared management process. The research shows that shared management has limitations, however it is, so far, the best pattern for UC management. The article concludes that shared management is a process and practice and that it becomes more potent as the actors involved gain experience and increasingly promote dialogue and well-understood interest based on social participation.
Acesso aberto (Open Access)
Detecção de mudanças na costa de manguezais da Amazônia a partir da classificação de imagens multisensores orientada a objetos
(Universidade Federal do Pará, 2011-03-03) NASCIMENTO JÚNIOR, Wilson da Rocha; SOUZA FILHO, Pedro Walfir Martins e; http://lattes.cnpq.br/3282736820907252
Mangroves presents great importance to the ecological balance, and a nursery conducive to the development of various animals and plants. In recent years, degradation of mangroves has been occurring more frequently due to the plundering of their natural resources, land planning and poorly planned tourist activities. By remote sensors can map large areas of the area more quickly and efficiently. The objective is to map the distribution of mangrove areas to the east of the Amazon River into the Bay of San Marcos in 1996 and 2008 from remote sensing data. The mapping, change detection and quantification was performed by ALOS / PALSAR, JERS-1, SRTM and Landsat 5 TM. In order to classify the images, we used the software Definiens Ecognition 8, which uses the logic of object-oriented classification. In the classification of the mangrove was an elaborate process tree that stores all the elements or rules (segmentation, algorithms, classes and attributes) needed to obtain the final classification. The result of the quantification of the mangrove was 6705,05 km ² (1996) and 7423,60 km ² (2008) which shows a net increase in mangrove area of 718,55 km ². The change detection map allowed an overall increase of 1931,04 km ², a total erosion of 1212,49 km ², remaining an area of 5492,56 km ² of mangrove unchanged. To statistically validate the results, we elaborated two confusion matrices containing the rights and wrongs of the classification. The error matrix for validation of the classification of classes mangrove swamp, upland, water mass, secondary vegetation, fields and lakes showed an overall accuracy rate = 96.279%, Kappa = 90.572% and 92.558% = index Tau, which showed the classification efficiency of mangroves in relation to other classes used in processing. The error matrix for validation of classification and Non-Change Change of mangrove area showed high accuracy Global = 83.33%, Kappa = 66.10% and 66.66% = index Tau. Therefore, we conclude that the method of object-oriented classification logic is excellent for mapping mangroves and very good for the detection of changes in tropical coastal areas. Regarding the expansion of mangrove areas, it is observed only in the Amazon region, as opposed to what is observed in other large systems of mangroves, such as the Gulf of Papua New Guinea and the Sundarbans in Bangladesh and India. The results were used to compose a mosaic of regional and global mapping of mangrove and ratify the large expanse of mangrove forests in Amazonian Brazil as one of the best preserved of the planet.
Acesso aberto (Open Access)
Três décadas de mudanças na planície costeira brasileira: O status dos manguezais, da aquicultura e salicultura a partir de séries temporais Landsat e técnicas de aprendizado de máquina
(Universidade Federal do Pará, 2020-03-31) DINIZ, Cesar Guerreiro; SOUZA FILHO, Pedro Walfir Martins e; http://lattes.cnpq.br/3282736820907252
Since the 1980s, land-use and land-cover (LULC) mapping has become a common scientific task. However, the systematic and continuous identification of any terrestrial use or cover, whether on a global or regional scale, demands large storage and processing capacities. This thesis presents two cloud computing pipelines to analyze: 1) the annual status of Brazilian mangroves from 1985 to 2018, along with a new spectral index, the Modular Mangrove Recognition Index (MMRI), which has been specifically designed to better discriminate mangrove forests from the surrounding vegetation, and 2) the annual status of the aquaculture and salt-culture over the Brazilian coastal plains. The mangrove cover showed two distinct occupation periods, 1985-1998 and 1999-2018. The first period shows an upward trend, which seems to be related more to the uneven distribution of Landsat data than to the regeneration of Brazilian mangroves. In the second period, a mangrove loss trend was registered, reaching up to 2% of the mangrove forest. On a regional scale, ~80% of Brazil's mangrove cover is located in the Amazon, Maranhao, Para, Amapa states. In terms of persistence, ~75% of the Brazilian mangroves remained unchanged for two decades or more, especially in the Brazilian Amazon. As for item 2, aquaculture and salt-culture are two of the most classical coastal land-uses worldwide. It isn't different in Brazil, where both land-uses are related to relevant economic activities in the Brazilian Coastal Zone (BCZ). However, to automatically discriminate such activities from other water-related covers/uses is not an easy task. Spectrally speaking, water is water and, unless it presents a high concentration of optically active compounds, not much can be done to dissociate a variety of water-related targets. In this sense, convolutional neural networks (CNN) have the advantage of predicting a given pixel's label by providing as input a local region (named patches or chips) around that pixel. Both the convolutional nature and the semantic segmentation capability allow the U-Net classifier, a type of CNN, to access the "context domain" instead of solely isolated pixel values. Backed by the context domain, the results obtained show that the BCZ aquaculture/saline ponds occupied ~356 km² in 1985 and ~544 km² in 2019, reflecting an area expansion of 52% (~185 km²), a rise of 1.5x in 35 years. From 1997 to 2015, the saline/aquaculture area grew by a factor of ~ 1.7, jumping from 349 km2 to 583 km2, a 67% increase. In 2019, the northeast sector concentrated 93% of the coastal aquaculture/salt-culture surface, 6% in Southeast and 1% in South. Interestingly, despite presenting extensive coastal zones and suitable conditions for developing different aquaculture products, the Amazon coast shows no relevant aquaculture infrastructure sign.
Acesso aberto (Open Access)
Vulnerabilidade costeira em uma comunidade tradicional amazônica: estudo de caso na vila de Jubim, Salvaterra - PA
(Universidade Federal do Pará, 2025-04-16) FIGUEIREDO, Fabrício de Sousa; RANIERI, Leilanhe Almeida; http://lattes.cnpq.br/3129401501809850; https://orcid.org/0000-0002-9870-4879
Coastal vulnerability is a topic of great relevance on a global scale due to current climate issues and rising ocean levels. Understanding the degree of coastal vulnerability is essential to prevent socioeconomic and environmental losses, such as those resulting from erosive processes. This study aimed to quantitatively assess the conditions of vulnerability to coastal erosion in a traditional community on Marajó Island: Jubim, located in the municipality of Salvaterra, state of Pará. To achieve this objective, a Coastal Vulnerability Index (CVI) was used, considering two projections of sea-level rise proposed by the Intergovernmental Panel on Climate Change (IPCC): one with a rise of 4 mm/year and the other with 15 mm/year until 2100. To identify coastal vulnerability under the two sea-level rise scenarios, they were associated with geomorphological and physical characteristics along the estuarine coast of Jubim. Oceanographic variables (tidal range, significant wave height, and sea-level variation) and geological variables (coastal geomorphology, beach slope, and shoreline erosion/accretion rate) were analyzed and classified, with vulnerability indices ranging from very low to very high. The determination of the shoreline erosion/accretion rate was carried out through multispectral and multitemporal analysis (33 years) using Landsat satellite images and the Digital Shoreline Analysis System (DSAS) tool. The spatialization and integration of the data, based on the CVI, were performed using Geographic Information System (GIS) software. The study area was segmented into three sectors: North (Salazar Beach), Central (Meninas Beach), and South (Baleia and Curuanã Beaches). Between 1990 and 2023, the average linear retreat recorded for the entire study area was -35.24 m (NSM), while the average linear advance was 15.10 m (NSM), highlighting the predominance of coastal erosion. The North sector, with the lowest topographic gradient, showed a maximum retreat of 170 meters and an average retreat of 1.99 m/year (EPR), revealing the retreat of mangrove vegetation and the overlapping of Salazar Beach over this ecosystem. The CVI revealed that, under both sea-level rise projections, Jubim's coastline tends to present moderate to high vulnerability (30.3% and 27.3%) in areas with cliffs and extensive sandy stretches, respectively. The map developed based on the CVI proved to be a useful tool to support coastal management on the Amazonian coast and decision-making in the face of advancing erosion caused by estuarine hydrodynamics, associated with rising sea levels.