Structural breaks detection in time series and its use in the definition of stability measures

• Grant number: 16/26170-8
• Support Opportunities: Scholarships in Brazil - Master
• Start date: November 01, 2017
• End date: February 28, 2019
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: Ricardo da Silva Torres
• Grantee: Nathália Menini Cardoso dos Santos
• Host Institution: Instituto de Computação (IC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated scholarship(s): 18/06918-3 - Quantifying Amazon's resilience through structural breaks associated with extreme climatic events, BE.EP.MS

Abstract

Studying the space-time dynamics of the environment in which we live is of extreme importance for decision-making and elaboration of public policies related to the changes of vegetation cover and land uses. One way to study these dynamics is to identify ecological characteristics of the regions of the planet, where man's interaction with nature is present. Pertaining that question, we intend to analyze the temporal dynamics of plant distribution in the tropical region of South America, mainly evaluating the temporal stability of natural and anthropic disturbances. Understanding how the environment behaves when subjected to some disturbance makes it possible to understand aspects about its capacity for recovery. For that task, we will use remote sensing techniques, time series analysis, classification methods, clustering, and detection of structural breaks with the objective of constructing a framework capable of identifying and measuring stability measures associated to a set of perturbations. In addition, we intend to develop part of the project at the University of Wageningen, in the Netherlands, under the supervision of Prof. Dr. Jan Verbesselt. (AU)

Scientific publications

(5)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

ALBARRACIN, JUAN F. H.; OLIVEIRA, RAFAEL S.; HIROTA, MARINA; DOS SANTOS, JEFERSSON A.; TORRES, RICARDO DA S.. A Soft Computing Approach for Selecting and Combining Spectral Bands. REMOTE SENSING, v. 12, n. 14, JUL 2020. (15/02105-0, 14/50715-9, 13/50169-1, 16/08085-3, 14/12236-1, 17/12646-3, 16/26170-8, 13/50155-0, 18/06918-3)

MENINI, NATHALIA; ALMEIDA, ALEXANDRE E.; LAMPARELLI, RUBENS; LE MAIRE, GUERRIC; DOS SANTOS, JEFERSSON A.; PEDRINI, HELIO; HIROTA, MARINA; TORRES, RICARDO DA S.. A Soft Computing Framework for Image Classification Based on Recurrence Plots. IEEE Geoscience and Remote Sensing Letters, v. 16, n. 2, p. 320-324, FEB 2019. (14/50715-9, 16/26170-8, 18/06918-3, 13/50155-0, 14/12236-1, 15/02105-0, 17/12646-3, 13/50169-1)

NOGUEIRA, KEILLER; DOS SANTOS, JEFERSSON A.; MENINI, NATHALIA; SILVA, THIAGO S. F.; MORELLATO, LEONOR PATRICIA C.; TORRES, RICARDO DA S.. Spatio-Temporal Vegetation Pixel Classification by Using Convolutional Networks. IEEE Geoscience and Remote Sensing Letters, v. 16, n. 10, p. 1665-1669, OCT 2019. (16/26170-8, 13/50155-0, 09/54208-6, 13/50169-1, 18/06918-3)

ALMEIDA, ALEXANDRE E.; MENINI, NATHALIA; VERBESSELT, JAN; TORRES, RICARDO DA S.; IEEE. BFAST EXPLORER: AN EFFECTIVE TOOL FOR TIME SERIES ANALYSIS. IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, v. N/A, p. 4-pg., 2018-01-01. (13/50169-1, 13/50155-0, 14/12236-1, 15/02105-0, 15/24494-8, 14/50715-9, 16/26170-8, 16/08085-3)

MENINI, NATHALIA; ALMEIDA, ALEXANDRE E.; LAMPARELLI, RUBENS; LE MAIRE, GUERRIC; OLIVEIRA, RAFAEL S.; VERBESSELT, JAN; HIROTA, MARINA; TORRES, RICARDO DA S.. Tucuma A toolbox for spatiotemporal remote sensing image analysis. IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE, v. 7, n. 3, p. 13-pg., 2019-09-01. (13/50169-1, 13/50155-0, 14/12236-1, 15/02105-0, 17/12646-3, 18/06918-3, 14/50715-9, 16/26170-8, 16/08085-3)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

SANTOS, Nathália Menini Cardoso dos. Ferramentas e estudos de caso para a caracterização de séries temporais de sensoriamento remoto. 2019. Master's Dissertation - Universidade Estadual de Campinas (UNICAMP). Instituto de Computação Campinas, SP.