Abstract:Open burning is illegal in Ukraine, yet Ukraine has, on average, 300 times more fire activity per year (2001–2019) than most European countries. In 2016 and 2017, 47% of Ukraine was identified as cultivated area, with a total of 70% of land area dedicated to agricultural use. Over 57% of all active fires in Ukraine detected using space-borne Visible Infrared Imaging Radiometer Suite (VIIRS) during 2016 and 2017 were associated with pre-planting field clearing and post-harvest crop residue removal, meaning that… Show more
“…We considered agricultural burns the croplands classified as BA by both RF algorithms, which means 5% of the burned areas will be underreported (Figure 6). These numbers are in line with previous studies that highlighted the importance of reporting the area burned in agricultural land (Hall et al, 2021) and of considering the implications of cropland expansion through burning (Noojipady et al, 2017).…”
Section: The Importance Of Agricultural and Small Burned Areassupporting
In January 2017, 114 active fires burned throughout Chile at the same time. These fires spread quickly due to high temperatures, fast dry winds, and low vegetation water content. The fire events burned more than 570,000 ha, from which 20% of the area was endangered native forest. Timely and accurate burned area mapping is crucial for the evaluation of damages and management of the affected areas. As Chile is a diverse country with many types of ecosystems and vegetation, the use of novel spectral indices may improve the accuracy of satellite data-based burned area mapping algorithms. In this study, we explored the contribution of band angle indices (BAnI) to burned area mapping. The BAnI are based on trigonometric equations that proved to be sensitive to moisture conditions. Then, we aimed to test their sensitivity to the burned area spectral signature. We used Sentinel-2 data at 20 m resolution to calibrate and implement a random forest (RF) classifier in Google Earth Engine (GEE) computing platform. We ran the RF classifier with and without BAnI to evaluate their potential to identify burned areas and performed two accuracy assessments comparing the results with visually digitized fire perimeters from (1) WorldView 3 (WV3) images, and (2) Sentinel at 10 m resolution. We determined that both BA classifications were more accurate than the perimeters created by the Chilean National Forest Corporation (CONAF), which overestimates the area burnt. The overestimation of CONAF perimeters is produced by considering as burned the inner unburned areas and omitting some small, burned areas. The first assessment showed no significant differences between the two RF classifications. However, the second validation showed lower omission and commission errors for the RF classifier with the BAnI (5 and 17.8%, respectively). On the other hand, comparing both BA classifications with and without BAnI, we observed differences in the spatial distribution of the errors. However, the RF classification with BAnI offered fewer commission errors located in agricultural areas. The burned area algorithms developed in GEE showed their potential to map the fire-affected area quickly, efficiently, and accurately, accounting for all the areas burned in the season, including the small and agricultural fires the official perimeters did not consider.
“…We considered agricultural burns the croplands classified as BA by both RF algorithms, which means 5% of the burned areas will be underreported (Figure 6). These numbers are in line with previous studies that highlighted the importance of reporting the area burned in agricultural land (Hall et al, 2021) and of considering the implications of cropland expansion through burning (Noojipady et al, 2017).…”
Section: The Importance Of Agricultural and Small Burned Areassupporting
In January 2017, 114 active fires burned throughout Chile at the same time. These fires spread quickly due to high temperatures, fast dry winds, and low vegetation water content. The fire events burned more than 570,000 ha, from which 20% of the area was endangered native forest. Timely and accurate burned area mapping is crucial for the evaluation of damages and management of the affected areas. As Chile is a diverse country with many types of ecosystems and vegetation, the use of novel spectral indices may improve the accuracy of satellite data-based burned area mapping algorithms. In this study, we explored the contribution of band angle indices (BAnI) to burned area mapping. The BAnI are based on trigonometric equations that proved to be sensitive to moisture conditions. Then, we aimed to test their sensitivity to the burned area spectral signature. We used Sentinel-2 data at 20 m resolution to calibrate and implement a random forest (RF) classifier in Google Earth Engine (GEE) computing platform. We ran the RF classifier with and without BAnI to evaluate their potential to identify burned areas and performed two accuracy assessments comparing the results with visually digitized fire perimeters from (1) WorldView 3 (WV3) images, and (2) Sentinel at 10 m resolution. We determined that both BA classifications were more accurate than the perimeters created by the Chilean National Forest Corporation (CONAF), which overestimates the area burnt. The overestimation of CONAF perimeters is produced by considering as burned the inner unburned areas and omitting some small, burned areas. The first assessment showed no significant differences between the two RF classifications. However, the second validation showed lower omission and commission errors for the RF classifier with the BAnI (5 and 17.8%, respectively). On the other hand, comparing both BA classifications with and without BAnI, we observed differences in the spatial distribution of the errors. However, the RF classification with BAnI offered fewer commission errors located in agricultural areas. The burned area algorithms developed in GEE showed their potential to map the fire-affected area quickly, efficiently, and accurately, accounting for all the areas burned in the season, including the small and agricultural fires the official perimeters did not consider.
“…Soil moisture content is furthermore the limiting vegetation growth factor in Ukraine and continental Eastern Europe that experiences a very strong decline in surface spectral greening trends over the past two decades. Recent results, however, have emphasized the strong effect of illegal vegetation burning prior and after crop cultivation in Ukraine, which could enhance the decline of spectral greening signals (Hall et al, 2021 ). Fig.…”
Europe witnessed a strong increase in climate variability and enhanced climate-induced extreme events, such as hot drought periods, mega heat waves, and persistent flooding and flash floods. Intensified land degradation, land use, and landcover changes further amplified the pressure on the environmental system functionalities and fuelled climate change feedbacks. On the other hand, global satellite observations detected a positive spectral greening trend—most likely as a response to rising atmospheric CO2 concentrations and global warming. But which are the engines behind such shifts in surface reflectance patterns, vegetation response to global climate changes, or anomalies in the environmental control mechanisms? This article compares long-term environmental variables (1948–2021) to recent vegetation index data (Normalized Difference Vegetation Index (NDVI), 2001–2021) and presents regional trends in climate variability and vegetation response across Europe. Results show that positive trends in vegetation response, temperature, rainfall, and soil moisture are accompanied by a strong increase in climate anomalies over large parts of Europe. Vegetation dynamics are strongly coupled to increased temperature and enhanced soil moisture during winter and the early growing season in the northern latitudes. Simultaneously, temperature, precipitation, and soil moisture anomalies are strongly increasing. Such a strong amplification in climate variability across Europe further enhances the vulnerability of vegetation cover during extreme events.
“…Groot Zwaaftink et al also investigated the episode of our E6 and mention forest fires in Ukraine and southern Russia as source regions. This region is also known for burning of crop land, such as wheat, which could explain the observed BB tracers hydroxybenzoic acid, nitrophenol, methylnitrophenol, and nitrocatechol (Section ). In addition, the mentioned forest fires by Groot Zwaaftink et al and the start of the heating season in Scandinavia during this event in October could explain the elevated levels of vanillic and homovanillic acid observed among the BB tracer compounds (Section ).…”
Emissions from biomass burning (BB) occurring at midlatitudes can reach the Arctic, where they influence the remote aerosol population. By using measurements of levoglucosan and black carbon, we identify seven BB events reaching Svalbard in 2020. We find that most of the BB events are significantly different to the rest of the year (nonevents) for most of the chemical and physical properties. Aerosol mass and number concentrations are enhanced by up to 1 order of magnitude during the BB events. During BB events, the submicrometer aerosol bulk composition changes from an organic-and sulfate-dominated regime to a clearly organic-dominated regime. This results in a significantly lower hygroscopicity parameter κ for BB aerosol (0.4 ± 0.2) compared to nonevents (0.5 ± 0.2), calculated from the nonrefractory aerosol composition. The organic fraction in the BB aerosol showed no significant difference for the O:C ratios (0.9 ± 0.3) compared to the year (0.9 ± 0.6). Accumulation mode particles were present during all BB events, while in the summer an additional Aitken mode was observed, indicating a mixture of the advected air mass with locally produced particles. BB tracers (vanillic, homovanillic, and hydroxybenzoic acid, nitrophenol, methylnitrophenol, and nitrocatechol) were significantly higher when air mass back trajectories passed over active fire regions in Eastern Europe, indicating agricultural and wildfires as sources. Our results suggest that the impact of BB on the Arctic aerosol depends on the season in which they occur, and agricultural and wildfires from Eastern Europe have the potential to disturb the background conditions the most.
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