scholarly journals Influence of Satellite Sensor Pixel Size and Overpass Time on Undercounting of Cerrado/Savannah Landscape-Scale Fire Radiative Power (FRP): An Assessment Using the MODIS Airborne Simulator

Fire ◽  
2020 ◽  
Vol 3 (2) ◽  
pp. 11
Author(s):  
Samuel Sperling ◽  
Martin J. Wooster ◽  
Bruce D. Malamud
Keyword(s):  
Landscape Scale ◽  
Low Noise ◽  
Pixel Size ◽  
Ir Detectors ◽  
Fire Cycle ◽  
Early Afternoon ◽  
Radiative Power ◽  
Satellite Sensor ◽  
Fire Radiative Power ◽  
Wide Swath

The fire radiative power (FRP) of active fires (AFs) is routinely assessed with spaceborne sensors. MODIS is commonly used, and its 1 km nadir pixel size provides a minimum per-pixel FRP detection limit of ~5–8 MW, leading to undercounting of AF pixels with FRPs of less than around 10 MW. Since most biomes show increasing AF pixel frequencies with decreasing FRP, this results in MODIS failing to detect many fires burning when it overpasses. However, the exact magnitude of the landscape-scale FRP underestimation induced by this type of AF undercounting remains poorly understood, as does its sensitivity to sensor pixel size and overpass time. We investigate these issues using both 1 km spaceborne MODIS data and 50 m MODIS Airborne Simulator (MAS) observations of the Brazilian cerrado, a savannah-like environment covering 2 million km2 (>20%) of Brazil where fires are a frequent occurrence. The MAS data were collected during the 1995 SCAR-B experiment, and are able to be spatially degraded to simulate data from sensors with a wide variety of pixel sizes. We explore multiple versions of these MAS data to deliver recommendations for future satellite sensor design, aiming to discover the most effective sensor characteristics that provide negligible pixel-area related FRP underestimation whilst keeping pixels large enough to deliver relatively wide swath widths. We confirm earlier analyses showing 1 km MODIS-type observations fail to detect a very significant number of active fires, and find the degree of undercounting gets worse away from the early afternoon diurnal fire cycle peak (~ 15:00 local time). However, the effect of these undetected fires on the assessment of total landscape-scale FRP is far less significant, since they are mostly low FRP fires. Using two different approaches we estimate that the MODIS-type 1 km data underestimates landscape scale FRP by around a third, and that whilst the degree of underestimation worsens away from the diurnal fire cycle peak the effect of this maybe less important since there are far fewer fires present. MAS data degraded to a 200 m spatial resolution provides landscape-scale FRP totals almost indistinguishable from those calculated with the original 50 m MAS observations, and still provides a pixel size consistent with a wide swath imaging instrument. Our work provides a potentially useful guide for future mission developers aiming at active fire and FRP applications, and we conclude that such missions need operate at spatial resolutions no higher than 200 m if they rely on cooled, low-noise IR detectors. Further work confirming this for fire-affected biomes beyond the savannah-type environments studied here is recommended.

scholarly journals Daily global fire radiative power fields estimation from one or two MODIS instruments

2014 ◽  
Vol 14 (24) ◽  
pp. 13377-13390 ◽  
Author(s):  
S. Remy ◽  
J. W. Kaiser
Keyword(s):  
Dry Matter ◽  
Low Earth Orbit ◽  
Atmospheric Composition ◽  
Correction Algorithm ◽  
Fire Cycle ◽  
Fire Emissions ◽  
Radiative Power ◽  
Leo Satellite ◽  
Linear Regressions ◽  
Fire Radiative Power

Abstract. Fires are important emitters of aerosol and trace gases and as such need to be taken into account in any atmospheric composition modelling enterprise. One method to estimate these emissions is to convert fire radiative power (FRP) analysis into dry matter burnt and emissions of smoke constituents using land-cover-dependent conversion factors. Inventories like the Global Fire Assimilation System (GFAS) follow this approach by calculating daily global smoke emissions from FRP observed by the MODIS instruments onboard the Terra and Aqua satellites. Observations with different overpass times systematically sample fires at different stages in the strong diurnal fire cycle. For some time periods, observations are available from only one instrument, which leads to a bias in the observed average FRP. We develop a method to correct this bias in daily FRP observations from any low Earth orbit (LEO) satellite, so that the budget of daily smoke emissions remains independent of the number of satellites from which FRP observations are taken into account. This ensures the possibility of running, for example, GFAS in case of failure of one of the MODIS instruments. It also enables the extension GFAS to 2000–2002 and the inclusion of FRP observations from upcoming satellite missions. The correction combines linear and non-linear regressions and uses an adaptive regionalization algorithm. It decreases the bias in daily average FRP from Terra and Aqua by more than 95%, and RMSE by 75% for Aqua and 55% for Terra. The correction algorithm is applied to Terra observations from 25 February 2000 to 31 December 2002, when Aqua observations were not available. The database of fire emissions GFASv1.0 is extended correspondingly.

Inter-comparison of four operational satellite Fire Radiative Power (FRP) products: A spatial and temporal consistency assessment.

2020 ◽  
Author(s):  
Bernardo Mota ◽  
Nadine Gobron ◽  
Martin Wooster
Keyword(s):  
Grid Cell ◽  
Fire Effects ◽  
Temporal Consistency ◽  
Fire Cycle ◽  
Infrared Imager ◽  
Radiative Power ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Fire Radiative Power

<p> We inter-compare four remotely sensed Fire Radiative Power (FRP) products, the polar-orbiter products derived from active fires detected using the <span>Moderate Resolution Imaging Spectroradiometer data </span>(MCD14ML) and VIIRS (VNP14ML and VNP14IMGML), and geostationary products derived from data collected by Meteosat’s <span>Spinning Enhanced Visible and Infrared Imager (the LSA-SAF FRP-PIXEL product). We focus on seven years of data (January 2012 to December 2018), and </span>using the ability of the geostationary product to capture the daily fire cycle we quantify for each polar-orbiter FRP product the proportion of daily fire energy release that they capture and that which they miss, and also identify the areas where their overpass times successfully capture the diurnal fire activity peak, and where they do not. In addition, by analysing <span>frequency density (f-D) distributions of FRP at a 0.5° grid cell resolution we evaluate </span>each products minimum FRP detection limit, which typically precludes detection of a proportion of the highly numerous but individually relatively small and/or low intensity fires.<span> R</span><span>esults are summarized by biome type based on the ESA CCI Land Cover product. </span>Our inter-comparison allows for the identification and quantification of some of the key non-fire effects causing FRP underestimation in satellite FRP products: pixel size, pixel area growth off-nadir, and the low temporal resolution of polar-orbiting sensors. Our results and the methodology developed herein should serve to evaluate and cross-calibrate FRP estimates obtained by the future Copernicus Climate Change Services (C3S) FRP products, which initially at least will be based only on SLSTR data collected by the Sentinel-3 satellite.</p>

scholarly journals Annual and diurnal african biomass burning temporal dynamics

2009 ◽  
Vol 6 (5) ◽  
pp. 849-866 ◽  
Author(s):  
G. Roberts ◽  
M. J. Wooster ◽  
E. Lagoudakis
Keyword(s):  
Land Cover ◽  
Fuel Consumption ◽  
Biomass Burning ◽  
Land Surface ◽  
Temporal Dynamics ◽  
Biomass Combustion ◽  
Land Cover Types ◽  
Fire Cycle ◽  
Radiative Power ◽  
Fire Radiative Power

Abstract. Africa is the single largest continental source of biomass burning emissions. Here we conduct the first analysis of one full year of geostationary active fire detections and fire radiative power data recorded over Africa at 15-min temporal interval and a 3 km sub-satellite spatial resolution by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) imaging radiometer onboard the Meteosat-8 satellite. We use these data to provide new insights into the rates and totals of open biomass burning over Africa, particularly into the extremely strong seasonal and diurnal cycles that exist across the continent. We estimate peak daily biomass combustion totals to be 9 and 6 million tonnes of fuel per day in the northern and southern hemispheres respectively, and total fuel consumption between February 2004 and January 2005 is estimated to be at least 855 million tonnes. Analysis is carried out with regard to fire pixel temporal persistence, and we note that the majority of African fires are detected only once in consecutive 15 min imaging slots. An investigation of the variability of the diurnal fire cycle is carried out with respect to 20 different land cover types, and whilst differences are noted between land covers, the fire diurnal cycle characteristics for most land cover type are very similar in both African hemispheres. We compare the Fire Radiative Power (FRP) derived biomass combustion estimates to burned-areas, both at the scale of individual fires and over the entire continent at a 1-degree scale. Fuel consumption estimates are found to be less than 2 kg/m2 for all land cover types noted to be subject to significant fire activity, and for savanna grasslands where literature values are commonly reported the FRP-derived median fuel consumption estimate of 300 g/m2 is well within commonly quoted values. Meteosat-derived FRP data of the type presented here is now available freely to interested users continuously and in near real-time for Africa, Europe and parts of South America via the EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites) Land Surface Analysis Satellite Applications Facility (http://landsaf.meteo.pt/). Continuous generation of these products will allow the types of analysis presented in this paper to be improved and extended, and such multi-year records should allow relationships between climate, fire and fuel to be further examined.

scholarly journals Daily global fire radiative power fields estimation from one or two MODIS instruments

2014 ◽  
Vol 14 (14) ◽  
pp. 20805-20844 ◽  
Author(s):  
S. Remy ◽  
J. W. Kaiser
Keyword(s):  
Global Scale ◽  
Low Earth Orbit ◽  
Atmospheric Composition ◽  
Correction Algorithm ◽  
Fire Cycle ◽  
Fire Emissions ◽  
Radiative Power ◽  
Leo Satellite ◽  
Linear Regressions ◽  
Fire Radiative Power

Abstract. Fires are important emitters of aerosol and trace gases and as such need to be taken into account in any atmospheric composition modeling enterprise. One method to estimate these emissions is to convert Fire Radiative Power (FRP) analysis to dry matter burnt and emissions of smoke constituents using land cover dependent conversion factors. Inventories like the Global Fire Assimilation System (GFAS) follow this approach by calculating daily global smoke emissions from FRP observed by the MODIS instruments on-board of the Terra and Aqua satellites. Observations with different overpass times systematically sample fires at different stages in the strong diurnal fire cycle. For some time periods, observations are available from only one instrument, which leads to a bias in the observed average FRP. We develop a method to correct this bias in daily FRP observations from any Low Earth Orbit (LEO) satellite, so that the budget of daily smoke emissions remains independent of the number of satellites from which FRP observations are taken into account. This ensures the possibility of running, e.g., GFAS in case of a default of one of the MODIS instruments. It also enables the extension GFAS to 2000–2002 and the inclusion of FRP observations from upcoming satellite missions. The correction combines linear and non-linear regressions and uses an adaptive regionalization algorithm. It removes the bias in daily average FRP observations from Terra and Aqua nearly entirely. Errors are larger for Terra than for Aqua, are generally relatively small at a global scale, but can be important at a local scale. The correction algorithm is applied to Terra observations from 25 February 2000 to 31 December 2002, when Aqua observations were not available. The database of fire emissions GFASv1.0 is extended correspondingly.

scholarly journals A Bi-Spectral Microbolometer Sensor for Wildfire Measurement

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3690
Author(s):  
Denis Dufour ◽  
Loïc Le Noc ◽  
Bruno Tremblay ◽  
Mathieu N. Tremblay ◽  
Francis Généreux ◽  
...  
Keyword(s):  
Low Resource ◽  
Long Wave ◽  
Radiative Power ◽  
Infrared Radiances ◽  
Moderate Scale ◽  
Long Wave Infrared ◽  
Detector Type ◽  
Experimental Burns ◽  
Fire Radiative Power

This study describes the development of a prototype bi-spectral microbolometer sensor system designed explicitly for radiometric measurement and characterization of wildfire mid- and long-wave infrared radiances. The system is tested experimentally over moderate-scale experimental burns coincident with FLIR reference imagery. Statistical comparison of the fire radiative power (FRP; W) retrievals suggest that this novel system is highly reliable for use in collecting radiometric measurements of biomass burning. As such, this study provides clear experimental evidence that mid-wave infrared microbolometers are capable of collecting FRP measurements. Furthermore, given the low resource nature of this detector type, it presents a suitable option for monitoring wildfire behaviour from low resource platforms such as unmanned aerial vehicles (UAVs) or nanosats.

scholarly journals Real-Time Detection of Daytime and Night-Time Fire Hotspots from Geostationary Satellites

2021 ◽  
Vol 13 (9) ◽  
pp. 1627
Author(s):  
Chermelle B. Engel ◽  
Simon D. Jones ◽  
Karin J. Reinke
Keyword(s):  
Real Time ◽  
Infrared Imaging ◽  
Night Time ◽  
Clear Link ◽  
Radiative Power ◽  
Biogeographical Region ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Fire Radiative Power

This paper introduces an enhanced version of the Biogeographical Region and Individual Geostationary HHMMSS Threshold (BRIGHT) algorithm. The algorithm runs in real-time and operates over 24 h to include both daytime and night-time detections. The algorithm was executed and tested on 12 months of Himawari-8 data from 1 April 2019 to 31 March 2020, for every valid 10-min observation. The resulting hotspots were compared to those from the Visible Infrared Imaging Radiometer Suite (VIIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS). The modified BRIGHT hotspots matched with fire detections in VIIRS 96% and MODIS 95% of the time. The number of VIIRS and MODIS hotspots with matches in the coincident modified BRIGHT dataset was lower (at 33% and 46%, respectively). This paper demonstrates a clear link between the number of VIIRS and MODIS hotspots with matches and the minimum fire radiative power considered.

scholarly journals Combining fire radiative power observations with the fire weather index improves the estimation of fire emissions

2017 ◽  
Author(s):  
Francesca Di Giuseppe ◽  
Samuel Rémy ◽  
Florian Pappenberger ◽  
Fredrik Wetterhall
Keyword(s):  
Biomass Burning ◽  
Atmospheric Composition ◽  
Composition Analysis ◽  
Fire Weather ◽  
Atmospheric Conditions ◽  
Weather Index ◽  
Fire Weather Index ◽  
Fire Emissions ◽  
Radiative Power ◽  
Fire Radiative Power

Abstract. The atmospheric composition analysis and forecast for the European Copernicus Atmosphere Monitoring Services (CAMS) relies on biomass burning fire emission estimates from the Global Fire Assimilation System (GFAS). GFAS converts fire radiative power (FRP) observations from MODIS satellites into smoke constituents. Missing observations are filled in using persistence where observed FRP from the previous day are progressed in time until a new observation is recorded. One of the consequences of this assumption is an overestimation of fire duration, which in turn translates into an overestimation of emissions from fires. In this study persistence is replaced by modelled predictions using the Canadian Fire Weather Index (FWI), which describes how atmospheric conditions affect the vegetation moisture content and ultimately fire duration. The skill in predicting emissions from biomass burning is improved with the new technique, which indicates that using an FWI-based model to infer emissions from FRP is better than persistence when observations are not available.

First retrieval of fire radiative power from COMS data using the mid-infrared radiance method

2016 ◽  
Vol 8 (2) ◽  
pp. 116-125 ◽  
Author(s):  
Daesun Kim ◽  
Jaeil Cho ◽  
Sungwook Hong ◽  
Hanlim Lee ◽  
Myoungsoo Won ◽  
...  
Keyword(s):  
Mid Infrared ◽  
Infrared Radiance ◽  
Radiative Power ◽  
Radiance Method ◽  
Fire Radiative Power

scholarly journals The Use of Fire Radiative Power to Estimate the Biomass Consumption Coefficient for Temperate Grasslands in the Atlantic Forest Biome

2017 ◽  
Vol 32 (2) ◽  
pp. 255-260 ◽  
Author(s):  
Bibiana Salvador Cabral da Costa ◽  
Eliana Lima da Fonseca
Keyword(s):  
Atlantic Forest ◽  
Field Data ◽  
Consumption Rate ◽  
Radiant Energy ◽  
Important Variable ◽  
Remotely Sensed Data ◽  
Radiative Power ◽  
Consumption Coefficient ◽  
Forest Biome ◽  
Fire Radiative Power

Abstract Every year, many active fire spots are identified in the satellite images of the southern Brazilian grasslands in the Atlantic Forest biome and Pampa biome. Fire Radiative Power (FRP) is a technique that uses remotely sensed data to quantify burned biomass. FRP measures the radiant energy released per time unit by burning vegetation. This study aims to use satellite and field data to estimate the biomass consumption rate and the biomass consumption coefficient for the southern Brazilian grasslands. Three fire points were identified in satellite FRP products. These data were combined with field data, collected through literature review, to calculate the biomass consumption coefficient. The type of vegetation is an important variable in the estimation of the biomass consumption coefficient. The biomass consumption rate was estimated to be 2.237 kg s-1 for the southern Brazilian grasslands in Atlantic Forest biome, and the biomass consumption coefficient was estimated to be 0.242 kg MJ-1.

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