@InProceedings{ArrudaJrLopeCamp:2015:EsCaMe,
author = "Arruda Junior, Elias Ribeiro de and Lopes, Eymar Silva Sampaio and
Campanha, Vinicius",
affiliation = "{} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
title = "An{\'a}lise do {\'{\i}}ndice de estabilidade de encostas a
partir do modelo SINMAP e de dados pluviom{\'e}tricos obtidos por
sat{\'e}lite: estudo de caso para o mega desastre de janeiro de
2011 no munic{\'{\i}}pio de Nova Friburgo-RJ",
booktitle = "Anais...",
year = "2015",
editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz
Eduardo Oliveira e Cruz de",
pages = "6203--6210",
organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 17. (SBSR)",
publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
address = "S{\~a}o Jos{\'e} dos Campos",
abstract = "This study aimed to contribute to reducing the human, social and
economic impacts caused by natural disasters in Brazil, such as
landslides triggered by heavy summer rains in mountainous regions.
Especially in the state of Rio de Janeiro, marked by the
mega-disaster occurred at January 2011.The current study developed
and calibrated the SINMAP model to predict areas susceptible to
shallow landslides using the platform for monitoring, analyzing
and alert to environmental extremes (TerraMA2). The
geoenvironmental input rainfall data was updated in real time and
had been adapted to model. The model was validated using real
inventory data raised scars of landslides in Nova Friburgo, Rio de
Janeiro. The results of this studywere: a rotine implemented in
the LUA language and calibrated in the TerraMA2 environment for
prediction of susceptible areas of landslide using the
mathematical model SINMAP; the landslide susceptibility maps
generated for each new entry data in the system during the period
of the the study; and the risk maps generated from each landslide
susceptibility map. The validation of the results showed a better
performance of the maps generated in TerraMA2 platform compared to
the original package and pointed out the possibility of improve
the results from input data of better quality. Further this study
showed the capability of the system to become operational in
forecasting and monitoring landslides in the study area and also
in other mountainous regions of Brazil.",
conference-location = "Jo{\~a}o Pessoa",
conference-year = "25-29 abr. 2015",
isbn = "978-85-17-0076-8",
label = "1299",
language = "pt",
organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
ibi = "8JMKD3MGP6W34M/3JM4HKD",
url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3JM4HKD",
targetfile = "p1299.pdf",
type = "Monitoramento e modelagem ambiental",
urlaccessdate = "27 abr. 2024"
}