Rodrigo Mikosz Gonçalves

When every drop counts: Analysis of Droughts in Brazil for the 1901-2013 period

To provide information useful in policy formulation and management of drought impacts in Brazil, in this study, a sequence of drought events based on monthly rainfall of 1901-2013 on ~25 km x 25 km grid are derived at 4 timescales that include short-timescales (3-month and 6-month) and medium to long-timescales (12-month and 24-month). Subsequently, probability of drought occurrences, intensity, duration and areal-extent are calculated. The probabilities of occurrence of severe and extreme droughts at short-timescales are 1 in 12 and 1 in 66 years, respectively, all over the country. At medium to long-timescales, the probability of severe droughts is about 1 in 20 years in northern Brazil, and 1 in 10 years in the south. The probabilities of extreme droughts are 1 in 9 and 1 in 12 years over northern Brazil and in the south, respectively. In general, no evidence of significant (α =0.05) trend is detected in drought frequency, intensity, and duration over the last 11 decades (since 1901) at all the 4 timescales. The drought areal-extent show increasing trends of 3.4%/decade over Brazil for both 3-month and 6-month timescales. However, the trend increases for the 12-month and 24-month timescales are relatively smaller, i.e., 2.4%/decade and 0.5%/decade, respectively.

MODELAGEM PREDITIVA DE LINHA DE COSTA UTILIZANDO REDES NEURAIS ARTIFICIAIS

Estudar modelagens atraves de dados geodesicos temporais com a possibilidade de predizer a posicao de linha de costa e uma tarefa importante e pode auxiliar significativamente na gestao costeira. A area de estudo neste trabalho se refere ao municipio de Matinhos no estado do Parana, Brasil. As linhas de costa temporais utilizadas para testar a modelagem preditiva sao provenientes respectivamente da fotogrametria analogica para anos 1954, 1963, 1980, 1991 e 1997 e de levantamentos geodesicos utilizando GPS (Global Position System) para 2001, 2002, 2005 e 2008 (como controle). Dois testes com as redes neurais artificiais foram organizados mudando alguns parâmetros como: arquitetura, numero de neuronios nas camadas ocultas e algoritmos de treinamentos. Quando comparados o valor dos residuos entre a predicao e a linha de costa de controle, os melhores resultados estatisticos indicam que o MAPE (mean absolute percentage error) sao 0,28% utilizando a rede neural parcialmente recorrente de Elman com o algoritmo de treinamento quase-Newton e 0,46% para o caso da rede neural perceptron multicamadas com o algoritmo de treinamento utilizando o metodo Bayesiano com regularizacao.

MODELAGEM FUZZY APLICADA NA DETECÇÃO DA VULNERABILDADE À EROSÃO COSTEIRA

O crescimento da urbanizacao vem provocando grandes transformacoes nas relacoes sociais e morfologica das areas costeiras. O presente trabalho tem como objetivo modelar massa de dados de diversas fontes como GNSS (Global Navigation Satellite Systems) e sensoriamento remoto para posteriormente prover a espacializacao da vulnerabilidade costeira a erosao utilizando a logica fuzzy. O metodo aplicado para analise da vulnerabilidade utilizou variaveis linguisticas, particoes fuzzy, intervalos e analises parametricas que caracterizam a modelagem fuzzy. Apos analise, os niveis de vulnerabilidade a erosao costeira ao longo da linha de costa nas cidades do Recife e Jaboatao dos Guararapes no litoral de Pernambuco apresentaram os seguintes resultados: 33,33% da linha de costa possuem vulnerabilidade baixa, 38,15% possui vulnerabilidade moderada, 14,26% vulnerabilidade alta e 14,26% muito alta.

Urbanização costeira e sombreamento na praia de Boa Viagem, Recife-PE, Brasil

Part of the urban concentration at Recife municipality, capital of Pernambuco State, in Northeastern Brazil is inserted into the coastal zone. Recife according to the census data from 2010 has a population of 1.536.934 inhabitants, distributed in an area of approximately 220 km 2 . This study aims to investigate the evolution of land use in an area located at Boa Viagem beach (Recife/Pernambuco/Brazil), where was realized a quantitative analysis of land use and urban zone evolution considering aspects of the years 1974, 2005, 2010 and 2011. For this purpose, were used satellite images of high spatial resolution, orthophotos and conducted a survey. The results are quantitative information that characterizes some temporal aspects of coastal zoning in Boa Viagem. Another important result was the identifi cation of shading in a stretch of beach and the determination of shoreline position in the selected area and the comparison with the Coastal Management Act of Pernambuco State.

TEMPORAL SHORELINE SERIES ANALYSIS USING GNSS

In recent decades, Boa Viagem beach located in the city of Recife-PE and Piedade in Jaboatao dos Guararapes-PE (Brazil) has seen urbanization near the coastline causing changes in social, economic and morphological aspects, where coastal erosion problems are observed. This study uses GNSS (global navigation satellite system) shoreline monitoring approach, which is quicker, and provides continuously updatable data at cm-level accuracy to analyze and determine temporal positional shifts of the shoreline as well as annual average rates through EPR (end point rate). To achieve this, kinematic GNSS survey data for the years 2007, 2009, 2010 and 2012 were used. The results show sectorial trends over the years, with the highest annual retreat rate of 8.16 m /year occurring during the period 2007-2009. Variety of differents patterns over the shoreline was also observed. These findings could be essential for decision making in coastal environments.

Classificação fuzzy da vulnerabilidade aos processos costeiros em Pontal do Paraná, Brasil

The classification of the vulnerability for coastal processes considering both natural factors and anthropogenic interference can contribute for Integrated Coastal Zone Management (ICZM). This contribution develops a fuzzy system to classify the vulnerability of coastal processes in the coastal zone of Pontal do Sul, PR, Brazil. The study area was divided into three sectors with different characteristics, which provided diverse inputs to test this fuzzy system. Considered input variables are set as the follows: anthropogenic interference, average wave height, tidal range and the influence of the estuary in the region. The output of the final classification presents three linguistic labels, which represents three levels of vulnerability as stable, moderate and unstable. The results by the defuzzification in the fuzzy system are numerical values in a scale ranging from 0 to 8. The following values have been obtained as 5.9, 6.7 and 1.3; for the three sectors indicating unstable, unstable and stable classification respectively. In order to corroborate the efficacy of modeling, the results were compared with existing classification of the study area. The method can be an alternative approach for the expert’s role in decision-making in related studies.

Sensoriamento remoto de alta resolução espacial na caracterização de assentamentos informais

The accelerated process of urban development in Brazil sometimes generates social and environmental vulnerability through spontaneous settlements, which are inhabited by low-income populations. Informal settlements are physical manifestations of urban poverty and intra-urban inequality. This generalization in underdeveloped countries is related to the process of “poverty urbanization”. Remote sensing provides a spatial view of the city and the temporal processes that impact the environment and degrade the quality of urban life. This kind of information is essential for providinge base-line information for urban decision makers. The present work aims to establish a methodology based on object-oriented analysis, applied to high spatial resolution satellite images (QuickBird) in order to characterize informal settlements. The introduction includes a theoretical discussion on urbanization and informal settlements. The study was conducted in the Ipes neighborhood in the Joao Pessoa district of the Paraiba State, Brazil. The total area classifi ed as substandard settlements was 29,342 m², which represents 1.6% of the total area of this neighborhood. The methodology proved to be effective in identifying irregular areas, and is an important tool for cadastral information updating and urban planning.

Highly Precise Positioning and Height Determination using GPS : Results of a PROBRAL project by Universidade Federal do Paraná (UFPR, Curitiba, Brazil) and Karlsruhe Institut für Technologie (KIT, Karlsruhe, Germany). (KIT Scientific Reports ; 7604)

This book presents some representatively selected results and experiences gained within the bilateral PROBRAL program funded by the academic exchange services CAPES and DAAD. During the time period 2006-2009 the joint international research project was established between the Postgraduate Programme in Geodetic Sciences of the Department of Geomatics of the Federal University of Parana (UFPR, Curitiba, Brazil) and the Geodetic Institute of Universitat Karlsruhe TH (now KIT, Karlsruhe, Germany).