NDLI: Time series components and breakpoints in remote sensing image analysis = Componentes e pontos de quebra em séries temporais na análise de imagens de sensoriamento remoto

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Time series components and breakpoints in remote sensing image analysis = Componentes e pontos de quebra em séries temporais na análise de imagens de sensoriamento remoto

Content Provider	Semantic Scholar
Author	Almeida, Alexandre E.
Copyright Year	2017
Abstract	Detecting and characterizing temporal changes are crucial indicators in the process of understanding how complex mechanisms work and evolve. The use of remote sensing images and techniques has been broadly employed over the past decades in order to detect and investigate temporal changes on the Earth surface. Such change detection in time series data may be even further refined by isolating the additive long-term (trend) and cyclical (seasonal) components from the underlying noise. This work investigates the particular Breaks For Additive Season and Trend (BFAST) method for the analysis, decomposition, and breakpoint detection of time series associated with remote sensing data. The derived outputs from that method are, then, used in three distinct — but highly interconnected — research venues: in a better comprehension of climatic phenomena; in the correlation to human-induced disturbances data; and in data classification problems using time series dissimilarity functions discovered by a Genetic-Programming-(GP)-based evolutionary framework. Performed experiments show that decomposition and breakpoints produced insightful and effective results when applied to the ecological data studies, but could not further improve the classification results when compared to its raw time series counterpart. The achievements in those three contexts also led to the creation of two open-source web-based time series analysis tools. One of those tools was so well received by the target community, that it is currently integrated into a private cloud computing platform.
File Format	PDF HTM / HTML
Alternate Webpage(s)	http://repositorio.unicamp.br/bitstream/REPOSIP/325344/1/Almeida_AlexandreEsteves_M.pdf
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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