African burned area and fire carbon emissions are strongly impacted by small fires undetected by coarse resolution satellite data.
Rubén Ramo,Ekhi Roteta,Ioannis Bistinas,Ioannis Bistinas,Dave van Wees,Aitor Bastarrika,Emilio Chuvieco,Guido R. van der Werf +7 more
TLDR
In this paper, the relevance of small fires was estimated by comparing a BA product generated from Sentinel-2 MSI images (20m spatial resolution) with a widely used global BA product based on MODIS images (500 m) focusing on sub-Saharan Africa.Abstract:
Fires are a major contributor to atmospheric budgets of greenhouse gases and aerosols, affect soils and vegetation properties, and are a key driver of land use change. Since the 1990s, global burned area (BA) estimates based on satellite observations have provided critical insights into patterns and trends of fire occurrence. However, these global BA products are based on coarse spatial-resolution sensors, which are unsuitable for detecting small fires that burn only a fraction of a satellite pixel. We estimated the relevance of those small fires by comparing a BA product generated from Sentinel-2 MSI (Multispectral Instrument) images (20-m spatial resolution) with a widely used global BA product based on Moderate Resolution Imaging Spectroradiometer (MODIS) images (500 m) focusing on sub-Saharan Africa. For the year 2016, we detected 80% more BA with Sentinel-2 images than with the MODIS product. This difference was predominately related to small fires: we observed that 2.02 Mkm2 (out of a total of 4.89 Mkm2) was burned by fires smaller than 100 ha, whereas the MODIS product only detected 0.13 million km2 BA in that fire-size class. This increase in BA subsequently resulted in increased estimates of fire emissions; we computed 31 to 101% more fire carbon emissions than current estimates based on MODIS products. We conclude that small fires are a critical driver of BA in sub-Saharan Africa and that including those small fires in emission estimates raises the contribution of biomass burning to global burdens of (greenhouse) gases and aerosols.read more
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Journal ArticleDOI
Global and Regional Trends and Drivers of Fire Under Climate Change
Matthew W. Jones,John T. Abatzoglou,Sander Veraverbeke,Niels Andela,Gitta Lasslop,Matthias Forkel,Adam J. P. Smith,Chantelle Burton,Richard Betts,Guido R. van der Werf,Stephen Sitch,Josep G. Canadell,Cristina Santín,Crystal A. Kolden,Stefan H. Doerr,Corinne Le Quéré +15 more
TL;DR: In this article , the authors present a stocktake of regional trends in fire weather and burned area during recent decades, and examine how fire activity relates to its bioclimatic and human drivers.
Journal ArticleDOI
The role of fire in global forest loss dynamics.
Dave van Wees,Guido R. van der Werf,James T. Randerson,Niels Andela,Yang Chen,Douglas C. Morton +5 more
TL;DR: In this paper, the authors analyzed the relationship between forest loss and fire at 500m resolution based on satellite-derived data for the 2003-2018 period and found that on average, 38% of global forest loss was associated with fire, and this fraction remained relatively stable throughout the study period.
Journal ArticleDOI
Doubling of annual forest carbon loss over the tropics during the early twenty-first century
Yu Feng,Zhenzhong Zeng,Tim Searchinger,Alan D. Ziegler,Jie Wu,Dashan Wang,Xinyue He,Paul R. Elsen,Philippe Ciais,Rongrong Xu,Zhilin Guo,Liqing Peng,Yiheng Tao,Dominick V. Spracklen,Joseph Holden,Xiaoming Liu,Yi Zheng,Peng Xu,Xin Jiang,Xiaozhou Song,Venkat Lakshmi,Eric F. Wood,Chunmiao Zheng +22 more
TL;DR: In this paper , the authors used different high-resolution satellite datasets to show a doubling of gross tropical forest carbon loss worldwide from 0.97 ± 0.16 PgC yr −1 in 2001, 2005, and 2015, 2019, respectively.
Journal ArticleDOI
Deep-learning-based burned area mapping using the synergy of Sentinel-1&2 data
TL;DR: In this article, a Siamese self-attention (SSA) classification strategy is proposed for the multi-sensor BA mapping and a multi-source dataset is constructed at the object level for the training and testing.
Journal ArticleDOI
CNN-based burned area mapping using radar and optical data
Miguel A. Belenguer-Plomer,Miguel A. Belenguer-Plomer,Mihai A. Tanase,Emilio Chuvieco,Francesca Bovolo +4 more
TL;DR: An in-depth analysis of the use of convolutional neural networks (CNN) for burned area (BA) mapping combining radar and optical datasets acquired by Sentinel-1 and Sentinel-2 on-board sensors, respectively significantly improves existing methods based on either sensor type.
References
More filters
Journal ArticleDOI
Interannual variability in global biomass burning emissions from 1997 to 2004
G. R. van der Werf,James T. Randerson,Louis Giglio,G. J. Collatz,Prasad S. Kasibhatla,Avelino F. Arellano,Avelino F. Arellano +6 more
TL;DR: In this paper, the authors investigated fire emissions during the 8 year period from 1997 to 2004 using satellite data and the CASA biogeochemical model, and found that on average approximately 58 Pg C year −1 was fixed by plants as NPP, and approximately 95% of this was returned back to the atmosphere via R h.
Journal ArticleDOI
Global fire emissions estimates during 1997–2016
Guido R. van der Werf,James T. Randerson,Louis Giglio,Thijs T. van Leeuwen,Yang Chen,Brendan M. Rogers,Mingquan Mu,Margreet J. E. van Marle,Douglas C. Morton,G. James Collatz,Robert J. Yokelson,Prasad S. Kasibhatla +11 more
TL;DR: The Global Fire Emissions Database (GFED) as mentioned in this paper has been used to quantify global fire emissions patterns during 1997-2016, with the largest impact on emissions in temperate North America, Central America, Europe, and temperate Asia.
Journal ArticleDOI
Global Percent Tree Cover at a Spatial Resolution of 500 Meters: First Results of the MODIS Vegetation Continuous Fields Algorithm
TL;DR: The first results of the MODIS vegetation continuous field algorithm's global percent tree cover are presented in this article, where a supervised regression tree algorithm is used to estimate tree cover per 500m MODIS pixel.
Journal ArticleDOI
The collection 6 MODIS active fire detection algorithm and fire products.
TL;DR: Improvements made to the fire detection algorithm and swath-level product that were implemented as part of the Collection 6 land-product reprocessing, which commenced in May 2015, indicated targeted improvements in the performance of the collection 6 activeFire detection algorithm compared to Collection 5, with reduced omission errors over large fires, and reduced false alarm rates in tropical ecosystems.
Journal ArticleDOI
A human-driven decline in global burned area
Niels Andela,Niels Andela,Douglas C. Morton,Louis Giglio,Yang Chen,G. R. van der Werf,Prasad S. Kasibhatla,Ruth DeFries,G. J. Collatz,Stijn Hantson,Silvia Kloster,Dominique Bachelet,Matthew Forrest,Gitta Lasslop,Fang Li,Stéphane Mangeon,Joe R. Melton,Chao Yue,James T. Randerson +18 more
TL;DR: Assessing long-term fire trends using multiple satellite data sets found that global burned area declined by 24.3 ± 8.8% over the past 18 years, and the estimated decrease in burned area remained robust after adjusting for precipitation variability and was largest in savannas.