Navegando por Assunto "Landsat"

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Acesso aberto (Open Access)
Análise temporal da cobertura vegetal de um fragmento da RPPN Seringal Triunfo, Ferreira Gomes - Amapá
(Universidade Federal do Pará, 2021-12-27) SCHNEIDER, Juliana Cristina; GODOY, Bruno Spacek; http://lattes.cnpq.br/4036516695601666; https://orcid.org/0000-0001-9751-9885
The construction of dams became necessary for national development, the Amazon region, for having a great hydro-energetic potential, was also used for the construction of these projects. River Araguari's hydrographic basin has three hydroelectric dams (Coaracy Nunes, Ferreira Gomes and Cachoeira Caldeirão) built in its middle course, in the municipality of Ferreira Gomes, however the construction generated several problems, such as loss of territoriality, difficulties in subsistence of villages and the environment modification. However, in 1998, there was the enactment of the Seringal Triunfo National Heritage Private Reserve, which aims to conserve biodiversity. Therefore, there is a need for studies aimed at improving the knowledge of vegetation cover, which have occurred since the enactment of the RPPN. In this sense, the present study sought to understand whether there were changes in the vegetation cover in the RPPN from 2000 to 2015, after its approval and with the construction of UHE Ferreira Gomes and Cachoeira Caldeirão. For this, remote sensing data were used. Twelve images obtained from the TM/Landsat-5, ETM+/Landsat 7 and OLI/Landsat-8 satellites were used, delimiting the study area with the creation of two polygons (buffer), one located within the RPPN and another adjacent with approximately the same size. Digital processing techniques were applied to these images with the aid of pixel counting software. The Normalized Difference Vegetation Index (NDVI) was calculated, making it possible to obtain the median. The obtained results show that the image processing allowed differentiate its constituent elements (vegetal cover and exposed soil). The calculation of the NDVI medians, for the scenes between the years 2000 to 2015, in the area located within the RPPN ranged from 0,37 to 0,64 and the medians of the adjacent area ranged from 0,29 to 0,63, thus, the statistical analysis showed no relationship with the years (F1,10 = 0,02 and P = 0,87), indicating that during the analyzed period there was a stability in the vegetation cover, the same occurred for the adjacent area (F1,10 = 0,11 and P = 0,74). This stability in the area of the RPPN may be related to the role it plays in nature conservation and in the adjacent area to the stagnation of population growth in the municipality. The use of images from remote sensors proved to be a very valuable tool for the present research, even without carrying out an on-site visit, it was possible to calculate the NDVI. Therefore, it is recommended for future work to analyze the NDVI from years prior to 2000, that is, years prior to the approval of the RPPN, as well as on-site visits, for the validation of the components observed in the NDVI, for the NDVI classification to the studied locality.
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.