Dataset
ESA Fire Climate Change Initiative (Fire_cci): MODIS Fire_cci Burned Area Pixel product, version 5.1
(see details tab for information on previous updates)
Abstract
The ESA Fire Disturbance Climate Change Initiative (CCI) project has produced maps of global burned area derived from satellite observations. These MODIS Fire_cci v5.1 pixel products are distributed as 6 continental tiles and are based upon data from the MODIS instrument onboard the TERRA satellite at 250m resolution for the period 2001-2020. This product supersedes the previously available MODIS v5.0 product. The v5.1 dataset was initially published for 2001-2017, and has later been periodically extended to include 2018 to 2020.
The Fire_cci v5.1 Pixel product described here includes maps at 0.00224573-degrees (approx. 250m) resolution. Burned area(BA) information includes 3 individual files, packed in a compressed tar.gz file: date of BA detection (labelled JD), the confidence level (CL, a probability value estimating the confidence that a pixel is actually burned), and the land cover (LC) information as defined in the Land_Cover_cci v2.0.7 product.
Files are in GeoTIFF format using a geographic coordinate system based on the World Geodetic System (WGS84) reference ellipsoid and using Plate Carrée projection with geographical coordinates of equal pixel size. For further information on the product and its format see the Fire_cci Product User Guide in the linked documentation.
Details
| Previous Info: |
2021-12-10
Data for 2020 have now been added to this dataset. 2020-09-08 New versions of the files for October to December 2019 have been added. (The original versions of these were previously withdr… Show More 2020-09-08 New versions of the files for October to December 2019 have been added. (The original versions of these were previously withdrawn due to an error in the processing) Show Less
2020-07-02
In July 2020 an error was found in the processing of the November 2019 dataset, causing the code to obtain much less burned are…
Show More
2020-07-02
In July 2020 an error was found in the processing of the November 2019 dataset, causing the code to obtain much less burned area that it should. This error also affects in a lesser extent the files corresponding to October and December 2019. 2020-04-22 2019 data has now been added to this dataset 2020-04-22 2019 data has now been added to this dataset 2019-07-08 2018 data has now been added to this dataset 2019-07-08 2018 data has now been added to this dataset 2019-01-17 Please note, an error was found affecting the 2007 Europe data (Area 3) - an updated version of this data is now available in … Show More 2019-01-17 Please note, an error was found affecting the 2007 Europe data (Area 3) - an updated version of this data is now available in the respective directory. Show Less |
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| Previously used record identifiers: |
No related previous identifiers.
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| Access rules: |
Public data: access to these data is available to both registered and non-registered users.
Use of these data is covered by the following licence(s): https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_fire_terms_and_conditions.pdf When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record. |
| Data lineage: |
Data was produced by the ESA Fire CCI team as part of the ESA Climate Change Initiative (CCI) and is being held on the CEDA (Centre for Environmental Data Analysis) archive as part of the ESA CCI Open Data Portal project. |
| Data Quality: |
See dataset associated documentation
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| File Format: |
Data are in GeoTiff format and is composed of 4 files:
...JD.tif: Day of first detection (Julian Day) of the burned area;
...CL.tif: Confidence level of burned area detection;
...LC.tif: Land cover of the pixel detected as burned as defined by the Land Cover CCI v2.0.7 product;
....xml: Metadata of the product.
The Coordinate Reference System (CRS) used is a geographic coordinate system (GCS) based on the World Geodetic System 84 (WGS84) reference ellipsoid and using a Plate Carrée projection with geographical coordinates of equal pixel size.
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Related Documents
| ESA Climate Change Initiative website |
| ESA CCI Fire project website |
| Product User Guide |
Citations: 9
The following citations have been automatically harvested from external sources associated with this resource where DOI tracking is possible. As such some citations may be missing from this list whilst others may not be accurate. Please contact the helpdesk to raise any issues to help refine these citation trackings.
| Boubekraoui, H., Maouni, Y., Ghallab, A., Draoui, M. & Maouni, A. (2024) Deforestation drivers in northern Morocco: an exploratory spatial data analysis. Environmental Research Communications 6, 071005. https://doi.org/10.1088/2515-7620/ad5ad6 https://doi.org/10.1088/2515-7620/ad5ad6 |
| Deshpande, M.V., Pillai, D. & Jain, M. (2022) Detecting and quantifying residue burning in smallholder systems: An integrated approach using Sentinel-2 data. International Journal of Applied Earth Observation and Geoinformation 108, 102761. https://doi.org/10.1016/j.jag.2022.102761 https://doi.org/10.1016/j.jag.2022.102761 |
| Gincheva, A., Pausas, J.G., Torres‐Vázquez, M.Á., et al. (2024) The Interannual Variability of Global Burned Area Is Mostly Explained by Climatic Drivers. Earth’s Future 12. https://doi.org/10.1029/2023ef004334 https://doi.org/10.1029/2023ef004334 |
| Li, S., Sparrow, S.N., Otto, F.E.L., Rifai, S.W., Oliveras, I., Krikken, F., Anderson, L.O., Malhi, Y. & Wallom, D. (2021) Anthropogenic climate change contribution to wildfire-prone weather conditions in the Cerrado and Arc of deforestation. Environmental Research Letters 16, 094051. https://doi.org/10.1088/1748-9326/ac1e3a https://doi.org/10.1088/1748-9326/ac1e3a |
| Lourenco, M., Woodborne, S. & Fitchett, J.M. (2022) Fire regime of peatlands in the Angolan Highlands. Environmental Monitoring and Assessment 195. https://doi.org/10.1007/s10661-022-10704-6 https://doi.org/10.1007/s10661-022-10704-6 |
| PNVR, K. & Bandaru, V. (2023) Mapping sugarcane residue burnt areas in smallholder farming systems using machine learning approaches. Smart Agricultural Technology 6, 100347. https://doi.org/10.1016/j.atech.2023.100347 https://doi.org/10.1016/j.atech.2023.100347 |
| Santi, E., Clarizia, M.P., Comite, D., Dente, L., Guerriero, L. & Pierdicca, N. (2021) On the Use of GNSS Reflectometry for Detecting Fire Disturbances in Forests: A Case Study in Angola. 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS. https://doi.org/10.1109/igarss47720.2021.9553090 https://doi.org/10.1109/igarss47720.2021.9553090 |
| Shi, K. & Touge, Y. (2023) Identifying the shift in global wildfire weather conditions over the past four decades: an analysis based on change-points and long-term trends. Geoscience Letters 10. https://doi.org/10.1186/s40562-022-00255-6 https://doi.org/10.1186/s40562-022-00255-6 |
| Shmuel, A. & Heifetz, E. (2022) Global Wildfire Susceptibility Mapping Based on Machine Learning Models. Forests 13, 1050. https://doi.org/10.3390/f13071050 https://doi.org/10.3390/f13071050 |
Process overview
Instrument/Platform pairings
| Moderate Resolution Imaging Spectroradiometer (MODIS) | Deployed on: Terra Satellite, part of the Earth Observation System Morning Constellation (EOS-AM) |
Mobile platform operations
| Mobile Platform Operation 1 | Terra Satellite orbit details |
Computation Element: 1
| Title | MODIS Fire_CCI Burned Area Computation |
| Abstract | The ESA Fire Disturbance Climate Change Initiative (CCI) project has produced maps of global burned areas developed from satellite observations. The Burned Area (BA) algorithm used for producing the final Fire_CCI BA product is a hybrid approach, combining information on active fires and temporal changes in relectance. The algorithm is described in the Fire_CCI Algorithm Theoretical Basis Document (Lizundia et al. 2018). |
| Input Description | None |
| Output Description | None |
| Software Reference | None |
| Output Description | None |
No variables found.
Temporal Range
2001-01-01T00:00:00
2020-12-31T23:59:59
Geographic Extent
90.0000° |
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-180.0000° |
180.0000° |
|
-90.0000° |