FireCCI51: MODIS Fire_cci Burned Area Pixel Product, Version 5.1

ESA/CCI/FireCCI/5_1
Dataset Availability
2001-01-01T00:00:00Z–2020-12-01T00:00:00Z
Dataset Provider
Earth Engine Snippet
ee.ImageCollection("ESA/CCI/FireCCI/5_1")
Cadence
1 Month
Tags
burn climate-change copernicus esa fire fragmentation geophysical global human-modification landcover landscape-gradient modis monthly stressors
c3s
cci
firecci
firecci51
gcos

Description

The MODIS Fire_cci Burned Area pixel product version 5.1 (FireCCI51) is a monthly global ~250m spatial resolution dataset containing information on burned area as well as ancillary data. It is based on surface reflectance in the Near Infrared (NIR) band from the MODIS instrument onboard the Terra satellite, as well as active fire information from the same sensor of the Terra and Aqua satellites.

The burned area algorithm uses a two-phase hybrid approach. In a first step pixels with a high probability of being burned (called "seeds") are detected based on the active fires. In a second one, a contextual growing is applied to completely detect the fire patch. This growing phase is controlled by an adaptive thresholding, where thresholds are computed based on the specific characteristics of the area surrounding each seed. The variable used to guide the whole detection process is the NIR drop between pre- and post-fire images.

The dataset includes for each pixel the estimated day of the first detection of the fire, the confidence level of that detection, and the land cover that has been burned (extracted from the ESA CCI Land Cover dataset v2.0.7). In addition, an observation flag is provided to identify the pixels that were not processed due to the lack of valid observations or because they belong to a non-burnable land cover.

FireCCI51 was developed as part of the ESA Climate Change Initiative (CCI) Programme, and it is also part of the Copernicus Climate Change Service (C3S).

Bands

Pixel Size
250 meters

Bands

Name Units Min Max Description
BurnDate None 1 366

Estimated day of the year of the first detection of the burn

ConfidenceLevel % 1 100

Probability of detecting a pixel as burned, expressing the uncertainty of the detection for all pixels, even if they are classified as unburned.

LandCover None

Land cover category of the burned pixels, extracted from the CCI LandCover v2.0.7 product. See Defourny, P., Lamarche, C., Bontemps, S., De Maet, T., Van Bogaert, E., Moreau, I., Brockmann, C., Boettcher, M., Kirches, G., Wevers, J., Santoro, M., Ramoino, F., & Arino, O. (2017). Land Cover Climate Change Initiative - Product User Guide v2. Issue 2.0. [online] Available at: https://maps.elie.ucl.ac.be/CCI/viewer/download/ESACCI-LC-Ph2-PUGv2_2.0.pdf accessed: July 2020. © ESA Climate Change Initiative - Land Cover led by UCLouvain (2017).

ObservedFlag None

Flags indicating why a pixel was not processed.

  • -2: the pixel is not burnable (water bodies, bare areas, urban areas, permanent snow and ice)
  • -1: the pixel has not been observed during the month (due to clouds, cloud shadows or sensor failure)

LandCover Class Table

Value Color Description
0 #000000

No Data

10 #ffff64

Cropland, rainfed

20 #aaf0f0

Cropland, irrigated or post-flooding

30 #dcf064

Mosaic cropland (>50%) / natural vegetation (tree, shrub, herbaceous cover) (<50%)

40 #c8c864

Mosaic natural vegetation (tree, shrub, herbaceous cover) (>50%) / cropland (<50%)

50 #006400

Tree cover, broadleaved, evergreen, closed to open (>15%)

60 #00a000

Tree cover, broadleaved, deciduous, closed to open (>15%)

70 #003c00

Tree cover, needleleaved, evergreen, closed to open (>15%)

80 #285000

Tree cover, needleleaved, deciduous, closed to open (>15%)

90 #788200

Tree cover, mixed leaf type (broadleaved and needleleaved)

100 #8ca000

Mosaic tree and shrub (>50%) / herbaceous cover (<50%)

110 #be9600

Mosaic herbaceous cover (>50%) / tree and shrub (<50%)

120 #966400

Shrubland

130 #ffb432

Grassland

140 #ffdcd2

Lichens and mosses

150 #ffebaf

Sparse vegetation (tree, shrub, herbaceous cover) (<15%)

170 #009678

Tree cover, flooded, saline water

180 #00dc82

Shrub or herbaceous cover, flooded, fresh/saline/brackish water

Terms of Use

Terms of Use

This dataset is free and open to all users for any purpose, with the following terms and conditions:

  • Users of the data are required to acknowledge the ESA Climate Change Initiative and the Fire CCI project together with the individual data providers if the data are used in a presentation or publication. Please also cite any relevant dataset DOIs.

  • Intellectual property rights (IPR) in the CCI data lie with the researchers and organisations producing the data.

  • Liability: no warranty is given as to the quality or the accuracy of the CCI data or its suitability for any use. All implied conditions relating to the quality or suitability of the information, and all liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.

Citations

Citations:
  • Padilla Parellada, M. (2018): ESA Fire Climate Change Initiative (Fire_cci): MODIS Fire_cci Burned Area Pixel product, version 5.1. Centre for Environmental Data Analysis, 01 November 2018. https://doi.org/10.5285/58f00d8814064b79a0c49662ad3af537.

  • Related publication: Lizundia-Loiola, J., Otón, G., Ramo, R., Chuvieco, E. (2020): A spatio-temporal active-fire clustering approach for global burned area mapping at 250m from MODIS data. Remote Sensing of Environment, 236, 111493. https://doi.org/10.1016/j.rse.2019.111493

DOIs

Explore with Earth Engine

Code Editor (JavaScript)

// Visualize FireCCI51 for one year
var dataset = ee.ImageCollection('ESA/CCI/FireCCI/5_1')
                  .filterDate('2020-01-01', '2020-12-31');
var burnedArea = dataset.select('BurnDate');

// Use a circular palette to assign colors to date of first detection
var baVis = {
  min: 1,
  max: 366,
  palette: [
    'ff0000', 'fd4100', 'fb8200', 'f9c400', 'f2ff00', 'b6ff05',
    '7aff0a', '3eff0f', '02ff15', '00ff55', '00ff99', '00ffdd',
    '00ddff', '0098ff', '0052ff', '0210ff', '3a0dfb', '7209f6',
    'a905f1', 'e102ed', 'ff00cc', 'ff0089', 'ff0047', 'ff0004'
  ]
};
var maxBA = burnedArea.max();

Map.setCenter(0, 18, 2.1);
Map.addLayer(maxBA, baVis, 'Burned Area');
Open in Code Editor