http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/4307 Sun, 12 Jul 2026 01:43:31 GMT 2026-07-12T01:43:31Z http://tede2.ufrpe.br:8080/tede/retrieve/13041/pbea.png http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/4307 http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/9856 Título: Análise topológica em imagens 3D de otólitos de peixes: explorando padrões de densidade e de morfologia Autor: SOUZA NETO, João Valério de Primeiro orientador: DUARTE NETO, Paulo José Abstract: In this thesis, we present a comparative study of otolith density variations using Topological Data Analysis (TDA). Otoliths are calcium carbonate structures found in the inner ears of fish and are commonly used to study age and growth patterns in fish populations. Traditionally, the analysis of otolith density variations has been a computationally intensive task due to the high-dimensional nature of the data. However, TDA offers a promising approach to reduce the data dimensionality and extract meaningful topological information from otolith images. We applied the Ball Mapper algorithm to a dataset of 3D otolith images from different fish species and ages. The algorithm allowed us to construct topological graphs representing the density variations in otoliths. We also explored the use of probabilistic sampling techniques to reduce the data and found that a sample size of 5% provided accurate representations of otolith density variations compared to the full dataset, after a Sample Topological Validation procedure developed here to ensure the efficiency and reliability of the sampling process. Topological invariants of the graphs, such as average clustering, node connectivity, assortativity, shortest path length, efficiency, and others, were used to comparizon between graphs. The comparizon of the topological properties of the full dataset with those of the 5% sample found a high degree of similarity, indicating that TDA with a reduced dataset can capture essential density information. Ball Mapper further allowed us to identify and eliminate dirt or anomalies present in otolith images, further enhancing the accuracy of our analysis. Overall, our study demonstrates the efficacy of TDA in studying otolith density variations with significant computational gains over traditional methods. The reduced data size using probabilistic sampling and the robustness of topological invariants provide valuable insights into the density patterns of otoliths. Another TDA technique, Persistent Homology (PH), was applied to the 3D image data with the expectation of unveiling a new classifier for otolith shape. PH demonstrated prominence even in a small sample by effectively separating otolith classes and revealing accurate quantitative separation results, showcasing potential use for otolith classification based on their 3D structure. Finally, a regression analysis demonstrated the possibility of estimating age, length, and radiodensity of otoliths based on the topological features resulting from the classification. Instituição: Universidade Federal Rural de Pernambuco Tipo do documento: Tese Fri, 23 Feb 2024 00:00:00 GMT http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/9856 2024-02-23T00:00:00Z http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/9832 Título: Correlações entre as séries temporais de queimadas e variáveis climáticas nos biomas brasileiros Autor: PESSOA, Ruben Vivaldi Silva Carneiro Primeiro orientador: STOSIC, Tatijana Abstract: Forest fires are complex phenomena, influenced by a set of climatic factors, in addition to human interference. In Brazil, these fires affect all biomes. Therefore, the study of these fires is necessary due to their negative effects, including not only environmental damage, but also greenhouse gas emissions and economic losses. In this scenario, understanding the temporal and spatial distribution of these fires is challenging, due to the variation in their natural behavior. This study seeks to address this issue, using fractal techniques to analyze the long-term temporal and spatial correlations between fires in Brazilian biomes during the period from 2002 to 2022. The results for the Amazon, Caatinga, Cerrado, and Atlantic Forest biomes showed that in the daily series of fire anomalies and climate variables (relative humidity, maximum temperature, rainfall, and wind speed), there are persistent long-range correlations, in which the persistence of fires was strongest in the Amazon biome and weakest in the Atlantic Forest. Climate variables are more persistent in the Caatinga biome and less persistent in the Atlantic Forest. Furthermore, persistent long-range cross-correlations were observed between the series of climate variables and fires in the four biomes. For the Amazon, Caatinga and Cerrado biomes, the DCCA correlation coefficient values indicated positive correlations between fires and the maximum temperature and wind speed variables, and negative correlations between fires and the relative humidity and rainfall variables. For the Atlantic Forest biome, the correlations between fires and the maximum temperature variable were positive and negative for the other climate variables. Instituição: Universidade Federal Rural de Pernambuco Tipo do documento: Tese Thu, 16 Jan 2025 00:00:00 GMT http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/9832 2025-01-16T00:00:00Z http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/9731 Título: Análise de tendências de índices de mudanças climáticas na precipitação do estado de Pernambuco Autor: GOMES, Vanessa Karoline Inacio Primeiro orientador: SILVA, Antonio Samuel Alves da Abstract: Many studies shown that the increase in the planet’s average temperature causes the hydrological cycle to intensify. This could cause changes in rainfall patterns, such as an increase in the frequency and intensity of extreme events resulting in severe and prolonged droughts in some locations and excessive rainfall in others, which would significantly impact the hydrological availability of a region and the quality of life of its inhabitants. Thus, it is necessary to study the variability and impacts of climate change, enabling a better understanding of the area’s climate in order to adapt and mitigate these climatic conditions. In this context, the present work aimed to analyze the trends and magnitudes of 11 extreme weather indices recommended by the Expert Team on Climate Change Detection Monitoring and Indices for the state of Pernambuco. For this, 809 grid points were used, which contain information regarding daily rainfall from 1961 to 2020 and three non-parametric methods were employed: the Mann-Kendall test for trend detection, sen’s slope for estimating the magnitude of the trend, and the Mann-Whitney-Wilcoxon test to assess whether there are significant differences in the index values for each region of Pernambuco: Zona da Mata, Agreste, and Sertão. In addition, the Inverse Distance Weighting interpolator was used to perform the spatial analysis of precipitation and extreme weather indices. The results indicated an intensification of drought over much of the state, with significant reductions in total annual precipitation, consecutive wet days, and an increase in consecutive dry days. The trends show an acceleration in the desertification process in the Sertão region, which is part of the semi-arid Northeast and already suffers from scarce and poorly distributed rainfall. In relation to the Zona da Mata, the extreme rainfall indices showed significant increases, alerting us to the natural disasters that affect this region. The Agreste region showed similar results to the Zona da Mata, but with less intensity. Based on the results obtained it is possible to infer that the study area tends to become drier, with rainfall increasingly concentrated in shorter periods of time, and the dry periods interspersed between these rainfall events are becoming longer. Instituição: Universidade Federal Rural de Pernambuco Tipo do documento: Dissertação Mon, 27 Feb 2023 00:00:00 GMT http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/9731 2023-02-27T00:00:00Z http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/8768 Título: Análise de séries temporais de focos de calor nos biomas brasileiros utilizando gráfico de recorrência Autor: BARROS, Vaniele da Silva Primeiro orientador: STOSIC, Tatijana Abstract: The scientific interest in studies that use recurrence analysis to approach the transitions between regular and chaotic behaviors, as well as, in the identification of structures of dynamic systems, has spread over the years. Among the main tools of this analysis, we highlight the Recurrence Graph method and the Recurrence Quantification Analysis, which are widely used in the analysis of time series supposedly coming from non-linear and even non-stationary dynamic systems. In particular, this work analyzed or evaluated the large and small scale patterns in the Recurrence Graphs of the series of hot pixels in the Amazon, Cerrado, Caatinga and Atlantic Forest biomes and to obtain the quantitative measures by the method of Recurrence Quantification Analysis. Daily series of hot pixels derived from data provided by National Institute of Space Research – INPE, of the biomes were analyzed for the period from July 4, 2002 to December 31, 2019. In Brazil, the annual average of number of hot pixels, between 2002 and 2019, is approximately 241,866 detections, being these most frequent events between the months of July to October. Considering the absolute values referring to the number of hot pixels in each biome, the highest concentration occurs in the Amazon biome, as it has the largest territorial extension, however, considering the number of hot pixels and the area of each biome, the Cerrado has the highest record per 𝑘𝑚2. The structures present in the Recurrence Graphs of the daily series of hot pixels of the biomes indicate low predictability, while for the series of anomalies, they indicate high predictability, in addition to presenting abrupt changes in the dynamics of the systems in both cases. The values of the various indices that serve as measures of process quantification confirm these results, were obtained through the application of the Recurrence Quantification Analysis method. Instituição: Universidade Federal Rural de Pernambuco Tipo do documento: Dissertação Mon, 15 Feb 2021 00:00:00 GMT http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/8768 2021-02-15T00:00:00Z