Building a small fire database for Sub-Saharan Africa from Sentinel-2 high-resolution images

Chuvieco, Emilio; Roteta, Ekhi; Sali, Matteo; Stroppiana, Daniela; Boettcher, Martin; Kirches, Grit; Storm, Thomas; Khairoun, Amin; Pettinari, M. Lucrecia; Franquesa, Magí; Albergel, Clément

doi:10.1016/j.scitotenv.2022.157139

Cited by 40 publications

(36 citation statements)

References 41 publications

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“…The day for which the first burn was detected (day of the year 1–366) was extracted for each year in the time series and pixels with > 70% confidence level (probability that the classification of the burn area is correct) were retained. To provide an estimate of the burn area omission for the MODIS FireCCI51 fire product, we compared the burn area during 2016 and 2019 to the small fire database for sub-Saharan Africa from Sentinel-2 high-resolution images for 2016 (Roteta et al, 2019 ) and 2019 (Chuvieco et al, 2022 ) over the study region. For this comparison, we extracted pixels which had > 70% confidence level in each of the products.…”

Section: Methodsmentioning

confidence: 99%

Fire regime of peatlands in the Angolan Highlands

Lourenco

Woodborne

Fitchett

2022

Environ Monit Assess

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The Angolan Highlands region includes the Angolan miombo woodland ecoregion which supports miombo woodland, grasslands, subsistence agricultural land, and peatland deposits. Extensive fires, slash and burn agriculture, peat fuel extraction, and peatland drainage are among the anthropogenic practices that threaten these peatland deposits. Peat fires cause peatland degradation, release significant amounts of greenhouse gases, deteriorate air quality, and contribute towards climate change and biodiversity loss. This study presents an analysis of the fire regimes over the period 2001 to 2020 in an under-studied area of the Angolan Highlands. Moderate Resolution Imaging Spectroradiometer (MODIS) fire and vegetation data were used in combination with a land use/land cover (LULC) classification map to calculate fire frequency, burn area, and fire regimes. The fire patterns within the study site are comparable to those found in African woodland savannas. Across the study site, 6976 km 2 (11.31%) of the land surface area burned at least nine times from 2001 to 2020, occurring largely within in the river valley environment. Considering the different LULC classes, peatlands were calculated to (a) burn more frequently (average fire frequency from 2001 to 2020 = 9.12), (b) have the smallest proportion (4.11%) of area which remained unburnt over the fire archive, and (c) have the largest average proportion (45.65% or 746 km 2 ) of burnt area per year. Peatland burning occurred predominantly during drier months from May to September. The results of this study highlight the strong influence of LULC on the fire frequency and distribution in the study area, requiring unique fire management strategies. As has been documented for boreal and tropical peatlands across the globe, we stress the importance of peatland conservation and protection; continued unsustainable management practices may lead to the loss of these important peatland deposits. Supplementary Information The online version contains supplementary material available at 10.1007/s10661-022-10704-6.

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Section: Methodsmentioning

confidence: 99%

Fire regime of peatlands in the Angolan Highlands

Lourenco

Woodborne

Fitchett

2022

Environ Monit Assess

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“…Some researchers have developed algorithms for establishing fire database based on remote-sensing data. Chuvieco et al (2022) expanded the MODIS Burned Area Product fire database using the high resolution of Sentinel-2 data. Laurent et al (2018) used burned area from MODIS and MERIS sensors to build a global database of fire patch functional traits.…”

Section: Utility and Application Of The Technologymentioning

confidence: 99%

An improved spatio-temporal clustering method for extracting fire footprints based on MCD64A1 in the Daxing’anling Area of north-eastern China

2023

Int. J. Wildland Fire

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Background. Understanding the spatio-temporal dynamics associated with a wildfire event is essential for projecting a clear profile of its potential ecological influences. Aims. To develop a reliable framework to extract fire footprints from MODIS-based burn products to facilitate the understanding of fire event evolution. Methods. This study integrated the Jenks natural breaks classification method and the density-based spatial clustering of applications with noise (DBSCAN) algorithm to extract the fire footprints in Daxing'anling region of China between 2001 and 2006 from MCD64A1 burned area data. Key results. The results showed that the fire footprints extracted by the model gained an overall accuracy of 80% in spatial and temporal domains after an intensive validation by using the historical fire records provided by the local agency. The agreement of burned area between the extracted fire patches and the historical fire records for those matched fire points was characterised by an overall determination coefficient R 2 at 0.91. Conclusions. The proposed framework serves as an efficient and convenient wildfire management tool for areas requiring large-scale and long-term wildfire monitoring. Implications. The current framework can be used to create a reliable large-scale fire event database by providing an important alternative for the improvement of field investigation.

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“…This product, called FireCCISFD (SFD comes from Small Fire Dataset), uses surface reflectance from the Sentinel-2 MSI (MultiSpectral Instrument) sensor at 20 m spatial resolution, complemented with active fire information (Roteta et al 2019). Version 1.1 of this dataset (FireCCISFD11) covers the year 2016 and is based on Sentinel-2A data + MODIS active fires, while the newer version (FireCCISFD20) has been processed for the year 2019, and takes advantage of the additional data provided by Sentinel-2B, duplicating the input data amount and temporal resolution, and the improved spatial resolution of the VIIRS active fire detection (Chuvieco et al 2022). The grid version of this product has a spatial resolution of 0.05 degrees, as requested by climate researchers.…”

Section: Fireccisfdmentioning

confidence: 99%

Advances in burned area detection from remote sensing: The FireCCI products

Chuvieco¹,

Pettinari²,

Lizundia-Loiola³

et al. 2022

Advances in Forest Fire Research 2022

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The FireCCI project has developed, during the last decade, a suite of burned area products based on remote sensing tailored to the climate researchers and also useful for different fire applications. The different products span from 1982 to 2020, and include global products at 250 m, 300 m, and 0.05-degrees spatial resolution, with derived grid products at 0.25-degree resolution. An additional burned area product at 20 m spatial resolution is available for Sub-Saharan Africa for 2016 and 2019. All products include ancillary information related to the uncertainty of the detection, the observational limitations, and the land cover burned. This presentation describes the characteristics of these products, called FireeCCILT11, FireCCI51, FireCCIS310 and FireCCISFD, and summarizes their similarities and differences, as well as their intended applications.

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Building a small fire database for Sub-Saharan Africa from Sentinel-2 high-resolution images

Cited by 40 publications

References 41 publications

Fire regime of peatlands in the Angolan Highlands

Fire regime of peatlands in the Angolan Highlands

An improved spatio-temporal clustering method for extracting fire footprints based on MCD64A1 in the Daxing’anling Area of north-eastern China

Advances in burned area detection from remote sensing: The FireCCI products

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