Comunidades no DSpace
Selecione uma comunidade para navegar por suas coleções
- Campus Samambaia, Campus Colemar Natal e Silva, Campus Aparecida de Goiânia.
Submissões Recentes
Item type: Item , O mal, a vontade e a liberdade humana em Santo Agostinho(Universidade Federal de Goiás, 2026-07-09) Sousa, Guilherme Henrique Feitosa de; Korelc, Martina; Santoro, Thiago Suman; Rocha, Rafael Carneiro; Korelc, MartinaThe aim of this study is to analyze key themes in the thought of Saint Augustine (354–430)—such as evil, human freedom, and freedom of the will—and to examine how his ideas were, in certain respects, innovative for his time, exerting an influence that extends beyond theology into philosophy to the present day. Of the vast array of topics raised by Augustine, this study focuses specifically on evil, its effects on the will, and the possibility of the will's restoration. Primary sources will consist mainly of Books VII and VIII of the “Confessions” (400) and Book III of “On Free Choice of the Will” (388–395). Regarding secondary literature, the study draws upon commentaries by Étienne Gilson, Johannes Brachtendorf, Moacyr Novaes Filho, Walterson José Vargas, and Marcos Roberto Nunes Costa.Item type: Item , Future dynamics of land use and land cover in the Cerrado biome(2026) Frazão, Ana Paula; Ferreira, Manuel Eduardo; Sousa, Silvio Braz de; Santos, Sophia VictóriaThe Cerrado, recognized as a global biodiversity hotspot, is under intense pressure from agricultural expansion. To support public policy planning, this study projected future land use and land cover scenarios up to 2100 using a spatial modeling framework developed in Python, based on Markov Chains, Weights of Evidence, and neighborhood metrics. PRODES deforestation rates were used to define three scenarios: optimistic (6,512.6 km²/year), trend (8,140.8 km²/year), and pessimistic (11,551 km²/year). The results indicate that the optimistic scenario slows the loss of native vegetation, whereas the trend scenario maintains recent conversion patterns and the pessimistic scenario intensifies landscape fragmentation. The highest annual losses are concentrated between 2030 and 2050 (optimistic: –2,707 km²; trend: –6,342 km²; pessimistic: –15,711 km²), followed by a decline due to the scarcity of remaining natural areas. By 2100, native vegetation may be reduced to 1.3–1.7 million km², corresponding to 47–61% of its original extent. These findings indicate that maintaining current trajectories may compromise the biome’s ecological resilience, highlighting the need for stricter conservation and deforestation control policies.Item type: Item , Meta-analysis: efficiency of using remote sensing to monitor algal and cyanobacterial blooms in continental aquatic environments(2026) Rissate, Guilherme Luiz; Darim, Elisa Parreira; Ferreira Neto, Gilson de Souza; Ferreira, Manuel Eduardo; Carneiro, Fernanda MeloAlgae, including both eukaryotes and prokaryotes (cyanobacteria), play a crucial role in aquatic ecosystems. However, eutrophication caused by human activities has led to excessive algal blooms, degrading water quality. Traditional phytoplankton monitoring methods are limited in scale and cost, whereas remote sensing emerges as an efficient alternative, enabling broad and continuous analysis. Chlorophyll-a, a pigment found in algae and cyanobacteria, is a key indicator of phytoplankton biomass and can be quantified using remote sensing techniques. This study conducted a meta-analysis of 267 articles (1983-2021) to assess the effectiveness of remote sensing models in estimating chlorophyll-a in inland waters. The results demonstrated that these models are effective, with a mean effect size of 0.6776. High heterogeneity among studies was observed, primarily influenced by atmospheric correction methods. Group 4 corrections (simultaneous retrieval of atmospheric and water components) helped explain part of the model's heterogeneity. Hyperspectral imagery and semi-analytical algorithms showed higher accuracy, though they were less frequently used. Lotic environments (rivers) exhibited larger effect sizes than lentic ones (lakes), reflecting ecological differences. Arid and temperate climates yielded better results than tropical and cold climates. The study concludes that remote sensing is a viable tool for monitoring algal blooms, with the potential to enhance water quality management.Item type: Item , Potenciais riscos da mineração a céu aberto na dinâmica dos corpos hídricos: recorte no manancial da bacia do Córrego da Lagoa, Ouvidor(2026) Rodrigues, Lucas Ferreira; Matos, Jainer Diogo Viera; Ferreira, Manuel EduardoThe present study examines the landscape and transformations in the Cerrado biome, focusing on the city of Ouvidor (GO) and the Lagoa Stream Watershed. It highlights the characteristics of the biome, its phytophysiognomies, and the impact of socioeconomic activities such as livestock farming, agriculture, and mining on landscape changes. The analysis emphasizes the relationship between anthropogenic activities, water resources, and regional transformations. It incorporates landscape concepts, stressing the unique heritage of the landscape and the responsibility for its sustainable use. The choice of Ouvidor is justified by the need for hydrological information to improve resource management. The methodology includes a literature review, document research, geoprocessing, and field analyses. This study aims to understand local dynamics and contribute to water resource management in the region.Item type: Item , UAV multisensor data and GAMLSS improve forage biomass estimation in Cerrado integrated crop-livestock pastures(2026) Lima, Gabriella Santos Arruda de; Ferreira, Manuel Eduardo; Baumann, Luis Rodrigo Fernandes; Freitas, Fernanda Mara Cunha; Machado, Pedro Luiz Oliveira de Almeida; Silva, Antônio Vitor Resende; Koakuzu, Selma Nakamoto; Silva, Mellissa Ananias Soler da; Carvalho, Márcia Thaís Melo; Santos, Micael Moreira; Madari, Beata EmokeIntroduction: Accurate estimation of aboveground biomass (AGB) is essential for monitoring pasture productivity and supporting sustainable management of integrated crop–livestock (ICL) systems. We hypothesized that integrating multispectral, thermal, and canopy-structural information derived from unmanned aerial vehicles (UAVs) would improve AGB prediction relative to spectral information alone, and that Generalized Additive Models for Location, Scale and Shape (GAMLSS) would accommodate seasonal heteroscedasticity while maintaining predictive performance comparable to Random Forest (RF) and Support Vector Machine (SVM) models. Methods: We collected 280 destructive biomass samples from two ICL paddocks and one continuously grazed pasture in the Brazilian Cerrado between 2022 and 2024. Twenty-four UAV-derived predictors, including spectral bands, vegetation indices, canopy surface temperature, and canopy height, were evaluated using repeated five-fold cross-validation. Model transferability was assessed by withholding one management paddock at a time. Results and discussion: Under repeated five-fold cross-validation, GAMLSS achieved the lowest prediction error (R² = 0.69 ± 0.01; RMSE = 2.15 ± 0.04 Mg ha⁻¹), followed closely by SVM (R² = 0.68 ± 0.01; RMSE = 2.19 ± 0.03 Mg ha-1); RF showed lower accuracy (R2 = 0.53 ± 0.01; RMSE = 2.63 ± 0.02 Mg ha-1). In the paddock-transferability assessment, GAMLSS also showed the lowest error (R2 = 0.63 ± 0.04; RMSE = 2.34 ± 0.26 Mg ha-1). For GAMLSS, the complete multisensor configuration reduced RMSE by 6.2% compared with the spectral-only configuration. The selected model was used to generate spatially explicit maps of AGB and standing aboveground biomass carbon, estimated from the mean measured carbon concentration of forage biomass. Integrating multispectral, thermal, and structural UAV data with distributional regression improves AGB estimation and enables spatial monitoring of tropical pastures under contrasting management conditions.