Forest fires, a major factor threatening the existence every type of forest ecosystem, have been getting worse in recent years. According to a report by the WWF, the duration of fire seasons across the globe has increased by 19% on average. In California, Oregon and Washington, emissions related to forest fires in 2020 were three times higher than the 21st century average. The peak days of wildfire in California were reported to generate emissions approximately 4 to 8 times higher than the average daily emissions reported from all the economic activities across the state. In Australia, the fire season has been starting early in places, with an increase in the duration of the fire season over extensive areas, according to the State of the Global Climate Report 2020.
Forest fires exhibit a compounded connection between weather, climate conditions and ecosystem processes. This is exemplified by regional differences observed during the 2020 Arctic fires in which the northern region reported the most active wildfire season in the last 18 years, evaluated in terms of fire radiative power and released carbon dioxide (CO2) emissions. Burning of vegetation due to forest fires leads to combustion of carbon stored in trees which is released in the atmosphere. Potent and detrimental gases like CO2and methane (CH4) escape into the atmosphere. Utilizing CAMS data analysis and Global Fire Assimilation data, it was reported that the Arctic Circle Fires have added to global CO2 emissions. Similarly throughout 2019 and 2020 increased emissions were observed in Russia’s Sakha Republic, India, and California, amongst others.
Satellite remote sensing data has played a decisive role in studying forest fires. Optical, RADAR and high resolution satellite imagery have provided insight into several dimensions of forest fires. New generations of satellites help to comprehend the scientific processes of forest fires. Several satellites owned by NASA, NOAA, and COPERNICUS provide open data which can quantify emissions like Aerosol Optical Depth (AOD) and Greenhouse gases. Increased availability of open source data have facilitated near real time monitoring and development of user-friendly interfaces for tracking and monitoring fires.
Estimating the emissions over different geographic locations in different time periods would provide insights into their role in the changing global climate scenario. The use of various models in geospatial environments would help to extract information, predict, and forecast forest fire emissions. Such knowledge would help policymakers in mitigating the forest fire as it is a major contributor to the global climate change. With these aims in mind, this Research Topic is focused on various satellite remote sensing data and sensors available for the study of forest fire emissions and welcomes article submissions covering, but not limited to, the following topics:
• Assessing the emission of gases caused by forest fires (at Global, Regional and Local scales).
• Changes in AOD to assess the air quality and its impact on weather/climate.
• Analyzing the trends in Land Surface Temperature (MODIS/LANDSAT/SENTINEL).
• Use of models and algorithms to study the long-term emissions as result of forest fire using Moderate-Resolution Imaging Spectroradiometer (MODIS) and Multi-Angle Imaging Spectroradiometer (MISR)
• Long-term trend analysis of forest fire emissions (in various forest types).
• Role and intensity of precursors of forest fires and subsequent emissions
• Prediction of spread of fire/transport of various GHG gases based on weather/climatic conditions.
• Algorithm/Apps developments in cloud platforms like Google Earth Engine studying forest fires.
• Utilizing Python packages and Jupyter notebooks to analyze satellite data (in NetCDF and other formats)for deriving results from satellites such as TROPOMI/OMI/VIIRS/SNPP/GOES.
Forest fires, a major factor threatening the existence every type of forest ecosystem, have been getting worse in recent years. According to a report by the WWF, the duration of fire seasons across the globe has increased by 19% on average. In California, Oregon and Washington, emissions related to forest fires in 2020 were three times higher than the 21st century average. The peak days of wildfire in California were reported to generate emissions approximately 4 to 8 times higher than the average daily emissions reported from all the economic activities across the state. In Australia, the fire season has been starting early in places, with an increase in the duration of the fire season over extensive areas, according to the State of the Global Climate Report 2020.
Forest fires exhibit a compounded connection between weather, climate conditions and ecosystem processes. This is exemplified by regional differences observed during the 2020 Arctic fires in which the northern region reported the most active wildfire season in the last 18 years, evaluated in terms of fire radiative power and released carbon dioxide (CO2) emissions. Burning of vegetation due to forest fires leads to combustion of carbon stored in trees which is released in the atmosphere. Potent and detrimental gases like CO2and methane (CH4) escape into the atmosphere. Utilizing CAMS data analysis and Global Fire Assimilation data, it was reported that the Arctic Circle Fires have added to global CO2 emissions. Similarly throughout 2019 and 2020 increased emissions were observed in Russia’s Sakha Republic, India, and California, amongst others.
Satellite remote sensing data has played a decisive role in studying forest fires. Optical, RADAR and high resolution satellite imagery have provided insight into several dimensions of forest fires. New generations of satellites help to comprehend the scientific processes of forest fires. Several satellites owned by NASA, NOAA, and COPERNICUS provide open data which can quantify emissions like Aerosol Optical Depth (AOD) and Greenhouse gases. Increased availability of open source data have facilitated near real time monitoring and development of user-friendly interfaces for tracking and monitoring fires.
Estimating the emissions over different geographic locations in different time periods would provide insights into their role in the changing global climate scenario. The use of various models in geospatial environments would help to extract information, predict, and forecast forest fire emissions. Such knowledge would help policymakers in mitigating the forest fire as it is a major contributor to the global climate change. With these aims in mind, this Research Topic is focused on various satellite remote sensing data and sensors available for the study of forest fire emissions and welcomes article submissions covering, but not limited to, the following topics:
• Assessing the emission of gases caused by forest fires (at Global, Regional and Local scales).
• Changes in AOD to assess the air quality and its impact on weather/climate.
• Analyzing the trends in Land Surface Temperature (MODIS/LANDSAT/SENTINEL).
• Use of models and algorithms to study the long-term emissions as result of forest fire using Moderate-Resolution Imaging Spectroradiometer (MODIS) and Multi-Angle Imaging Spectroradiometer (MISR)
• Long-term trend analysis of forest fire emissions (in various forest types).
• Role and intensity of precursors of forest fires and subsequent emissions
• Prediction of spread of fire/transport of various GHG gases based on weather/climatic conditions.
• Algorithm/Apps developments in cloud platforms like Google Earth Engine studying forest fires.
• Utilizing Python packages and Jupyter notebooks to analyze satellite data (in NetCDF and other formats)for deriving results from satellites such as TROPOMI/OMI/VIIRS/SNPP/GOES.
