Applied Time Series—Natural Disasters Perspective of Use: Landslide and Flood

Alessandra C. Corsi (), Filipe A. M. Falcetta (), Marcela P. P. Guimarães () and Eduardo S. de Macedo ()
Additional contact information
Alessandra C. Corsi: Instituto de Pesquisas Tecnológicas do Estado de São Paulo - IPT, Centro de Tecnologias Geoambientais - CTGeo
Filipe A. M. Falcetta: Instituto de Pesquisas Tecnológicas do Estado de São Paulo - IPT, Centro de Tecnologias Geoambientais - CTGeo
Marcela P. P. Guimarães: Instituto de Pesquisas Tecnológicas do Estado de São Paulo - IPT, Centro de Tecnologias Geoambientais - CTGeo
Eduardo S. de Macedo: Instituto de Pesquisas Tecnológicas do Estado de São Paulo - IPT, Centro de Tecnologias Geoambientais - CTGeo

A chapter in Towards Mathematics, Computers and Environment: A Disasters Perspective, 2019, pp 145-162 from Springer

Abstract: Abstract Time series can be applied to understand the observed data and to fit a model to forecasting and monitoring. Historically, time series methods were applied to problems in the physical and environmental sciences, but they can also be used in several other areas of knowledge, like economy, social science, epidemiology, and medicine. In this chapter, we will use the time series method for landslide occurrences in Cubatão City (São Paulo State) and for flooding we present the study conducted in Lençóis Paulista City (São Paulo State).

Date: 2019
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-21205-6_8

Ordering information: This item can be ordered from
http://www.springer.com/9783030212056

DOI: 10.1007/978-3-030-21205-6_8

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().