Burned Area Mapping in the Brazilian Savanna Using a One-Class Support Vector Machine Trained by Active Fires

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 resolutio...

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Vydáno v:Remote sensing (Basel, Switzerland) Ročník 9; číslo 11; s. 1161
Hlavní autoři: Pereira, Allan, Pereira, José, Libonati, Renata, Oom, Duarte, Setzer, Alberto, Morelli, Fabiano, Machado-Silva, Fausto, De Carvalho, Luis
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.11.2017
Témata:
active fire
Algorithms
Autonomy
burned area
Cerrado
Fires
First aid
Image classification
Infrared imaging
Infrared radiometers
Landsat
Landsat satellites
Mapping
MODIS
PROBA-V
Radiometry
Reflectance
Remote sensing
Satellite imagery
Savannahs
Scars
Spatial data
Spatial discrimination
Spatial resolution
support vector machine one class
VIIRS
ISSN:2072-4292, 2072-4292
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Shrnutí: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.
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ISSN:2072-4292
2072-4292
DOI:10.3390/rs9111161