@Article{PereiraPLOWMMC:2017:BuArMa,
author = "Pereira, Allan A. and Pereira, Jos{\'e} M. C. and Libonati,
Renata and Oom, Duarte and Waingort, Setzer Alberto and Morelli,
Fabiano and Machado-Silva, Fausto and Carvalho, Luis Marcelo
Tavares de",
affiliation = "{Instituto Federal de Ci{\^e}ncia e Tecnologia do Sul de Minas
Gerais} and {Universidade de Lisboa} and {Universidade Federal do
Rio de Janeiro (UFRJ)} and {Universidade de Lisboa} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)} and {Universidade Federal do Rio de
Janeiro (UFRJ)} and {Universidade Federal de Lavras (UFLA)}",
title = "Burned area mapping in the brazilian savanna using a one-class
support vector machine trained by active fires",
journal = "Remote Sensing",
year = "2017",
volume = "9",
pages = "1--21",
keywords = "support vector machine one class, burned area, active fire,
Cerrado, PROBA-V, VIIRS.",
abstract = "We used the Visible Infrared Imaging Radiometer Suite (VIIRS)
active fire data (375 m spatial resolution) to automatically
extract multispectral samples and train a One-Class Support Vector
Machine for burned area mapping, and applied the resulting
classification algorithm to 300-m spatial resolution imagery from
the Project for On-Board Autonomy-Vegetation (PROBA-V). The active
fire data were screened to prevent extraction of unrepresentative
burned area samples and combined with surface reflectance
bi-weekly composites to produce burned area maps. The procedure
was applied over the Brazilian Cerrado savanna, validated with
reference maps obtained from Landsat images and compared with the
Collection 6 Moderate Resolution Imaging Spectrometer (MODIS)
Burned Area product (MCD64A1) Results show that the algorithm
developed improved the detection of small-sized scars and
displayed results more similar to the reference data than MCD64A1.
Unlike active fire-based region growing algorithms, the proposed
approach allows for the detection and mapping of burn scars
without active fires, thus eliminating a potential source of
omission error. The burned area mapping approach presented here
should facilitate the development of operational-automated burned
area algorithms, and is very straightforward for implementation
with other sensors.",
doi = "10.3390/rs9111161",
url = "http://dx.doi.org/10.3390/rs9111161",
issn = "2072-4292",
language = "en",
targetfile = "pereira_burned.pdf",
urlaccessdate = "27 abr. 2024"
}