A Large-Scale Dataset for Active Fire Detection/Segmentation (Landsat-8)

Pereira, Gabriel Henrique de Almeida;Fusioka, Andre Minoro;Nassu, Bogdan Tomoyuki;Minetto, Rodrigo

Description

This dataset was created from all Landsat-8 images from South America in the year 2018. More than 31 thousand images were processed (15 TB of data), and approximately on half of them active fire pixels were found. The Landsat-8 sensor has 30 meters of spatial resolution (1 panchromatic band of 15m), 16 bits of radiometric resolution and 16 days of temporal resolution (revisit). The images in our dataset are in TIFF format with 10 bands (excluding the 15m panchromatic band). We cropped the original Landsat-8 scenes into image patches with 128 x 128 pixels by using a stride overlap of 64 pixels (vertical and horizontal). The masks are in binary format where True (1) represents fire and False (0) represents background and they were generated from the conditions set by Schroeder et al. (2016).

Citations (0)

Mentions (0)

Metrics

Dataset Index

0.7

FAIR Score

58%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

IEEE DataPort

License

Creative Commons Attribution 4.0 International

Assigned Domain

Subfield

Media Technology

Field

Engineering

Domain

Physical Sciences

Confidence Score

54%

Source

Scholar Data Model

Keywords

Artificial IntelligenceComputer VisionImage ProcessingMachine LearningRemote SensingGeoscience and Remote SensingEnvironmentalActive fire detection; Wildfire segmentation; Wildfire dataset; Landsat-8 images; South America

Normalization Factors

FT

26.92

CTw

1.00

MTw

1.00