Why is information on burned areas needed?
It is estimated, that about 25%-35% of Greenhouse gases (GHG) result from biomass burning and therefore they are considered an important factor in climate change (GTOS 68, T13 Fire Disturbance).
Aims of the Fire_cci project
Current global burned area products already exist, but the Fire_cci project aims to improve consistency, using better algorithms for both pre-processing and burned area detection while incorporating error characterisation in their product.
The project team, led by University of Alcala (Spain), focuses on the following issues relating to Fire disturbance:
- Analysis and specification of scientific requirements relating to climate
- Development and improvement of pre-processing and burned area algorithms
- Inter-comparison and selection of burned area algorithms
- System prototyping and production of burned area datasets
- Product validation and product assessment
More specifically, the project team aims to:
- Develop and validate algorithms to meet, as far as possible, GCOS Essential Climate Variable (ECV) requirements for (consistent, stable, error-characterized) global satellite data products from multi-sensor data archives
- Produce and validate, within a research and development context, the most complete and consistent possible time series of multi-sensor global satellite data products for climate research and modelling
- Optimise the impact of ESA Earth Observation (EO) missions data on climate data records
- Strengthen inter-disciplinary cooperation between international earth observation, climate research and modelling communities, in pursuit of scientific excellence.
The project focuses on the key variable "burned area". It will incorporate active fire observations as a supplemental variable to improve detection of burned area across varying biomes.
Global Burned Area products – Output of the Fire_cci Project
Two global burned area products are delivered as a result of the project:
- Pixel product, with a resolution of 250-300 metres, including the date of detection, the confidence level and the land cover corresponding to the burned pixel. Each dataset contains one month of information.
- Grid product, with a resolution of 0.25 degrees, and the following information in each grid cell: sum of burned area, standard error, fraction of burnable area, fraction of observed area, number of patches, and sum of burned area for each land cover class.
Complementary, a Small Fire Database (SFD) product has been generated, using Sentinel-2 information at 20-metre spatial resolution, and covering Sub-Saharan Africa for the year 2016, which will be followed by a new version for the year 2019. As additional information, burned area derived from Sentinel-1 has also been obtained for Tropical South America, and a new algorithm combining Sentinel-1 and S-2 is under development.