Landsat-8 and Sentinel-2 burned area mapping - A combined sensor multi-temporal change detection approach

The free-availability of global coverage Landsat-8 and Sentinel-2 data provides the opportunity for systematic generation of medium spatial resolution land products. This paper presents a combined Landsat-8 Sentinel-2 burned area mapping algorithm. The data handling integrates recent research on Lan...

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Bibliographic Details
Published in:Remote sensing of environment 2019-09, Vol.231, p.111254, Article 111254
Main Authors: Roy, David P., Huang, Haiyan, Boschetti, Luigi, Giglio, Louis, Yan, Lin, Zhang, Hankui H., Li, Zhongbin
Format: Article
Language:English
Subjects:
Algorithms
Bias
Burned area
Burning
Change detection
Combustion
Correlation
Fire effects
Forest fires
Forests
Landsat
Landsat satellites
Mapping
MODIS
Pixels
PLANET
Reflectance
Regression
Remote sensing
Satellite observation
Sensors
Sentinel-2
Slopes
Spatial discrimination
Spatial resolution
Spectra
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Summary:The free-availability of global coverage Landsat-8 and Sentinel-2 data provides the opportunity for systematic generation of medium spatial resolution land products. This paper presents a combined Landsat-8 Sentinel-2 burned area mapping algorithm. The data handling integrates recent research on Landsat-8 and Sentinel-2 pre-processing to generate registered, surface nadir BRDF-adjusted reflectance (NBAR) sensor time series that are used as an input. The different sensor data are combined through a random forest change regression, trained with synthetic data built from laboratory and field spectra and using a spectral model of fire effects on reflectance. The random forest regression is applied independently at each gridded 30 m pixel location on a temporally rolling basis considering three months of sensor data to map the central month. Temporal consistency checks are used to reduce commission errors due to non-fire related spectral changes, and a region growing algorithm is used to reduce omission errors due to temporally sparse observations. In the resulting product, each 30 m pixel is labelled as burned, unburned or unmapped. At burned pixels the estimated day of burning, and a single value that provides an estimate of the product of the subpixel fraction burned (f) and the combustion completeness (cc), henceforth termed “f.cc”, and an associated quality measure, are defined. The algorithm is demonstrated using six months of every available Landsat-8 and Sentinel-2A acquisition over 10° × 10° of Southern Africa. Experiments comparing the mapped burned areas considering Sentinel-2A only and both Landsat-8 and Sentinel-2A data indicate a greater area burned and a smaller number of unmapped pixels when both sensors are used. The results are compared with contemporaneous NASA MODIS fire products to gain insights into their temporal and spatial reporting differences. Temporally, the Sentinel-2A and Landsat-8 30 m product reports the day of burning on average three days later than the MODIS 500 m burned area product, because of the lower revisit frequency of the Sentinel-2A and Landsat-8 observations. Spatially, the Sentinel-2A and Landsat-8 30 m product captures more detail than the MODIS 500 m burned area product, with systematically higher burned area estimates. Despite the areal differences, the spatial pattern of the two products is similar, as reflected by the correlation (r2 ~ 0.7) and slope (>0.8) of regressions of the proportions of area burned defin
ISSN:0034-4257
1879-0704
DOI:10.1016/j.rse.2019.111254