nasa-gesdisc/es-publications-researchareas huggingface dataset:
Changing patterns of fire occurrence in proximity to forest edges, roads and rivers between NW Amazonian countries (2017)

Abstract. Tropical forests in NW Amazonia are highly threatened by the expansion of the agricultural frontier and subsequent deforestation. Fire is used, both directly and indirectly, in Brazilian Amazonia to propagate deforestation and increase forest accessibility. Forest fragmentation, a measure of forest degradation, is also attributed to fire occurrence in the tropics. However, outside the Brazilian Legal Amazonia the role of fire in increasing accessibility and forest fragmentation is less explored. In this study, we compared fire regimes in five countries that share this tropical biome in the most north-westerly part of the Amazon Basin (Venezuela, Colombia, Ecuador, Peru and Brazil). We analysed spatial differences in the timing of peak fire activity and in relation to proximity to roads and rivers using 12 years of MODIS active fire detections. We also distinguished patterns of fire in relation to forest fragmentation by analysing fire distance to the forest edge as a measure of fragmentation for each country. We found significant hemispheric differences in peak fire occurrence with the highest number of fires in the south in 2005 vs. 2007 in the north. Despite this, both hemispheres are equally affected by fire. We also found difference in peak fire occurrence by country. Fire peaked in February in Colombia and Venezuela, whereas it peaked in September in Brazil and Peru, and finally Ecuador presented two fire peaks in January and October. We confirmed the relationship between fires and forest fragmentation for all countries and also found significant differences in the distance between the fire and the forest edge for each country. Fires were associated with roads and rivers in most countries. These results can inform land use planning at the regional, national and subnational scales to minimize the contribution of road expansion and subsequent access to the Amazonian natural resources to fire occurrence and the associated deforestation and carbon emissions.

Research areas: Wildfires
Open data application to evaluate exposure of wildfire to water resources: A case study in Johor, Malaysia (2022)

Abstract
            Climate change impacts wildfire events as well as water availability. Exposure of water resources to wildfire can reduce water quality supplied to humans and resulting health problems. On the other hand, water resources such as rivers and ponds are essential in wildfire firefighting. This paper intended to assess spatially the exposure of water resources to wildfire. A case study in Johor, Malaysia is utilised to asses and determine locations of water bodies in an area which are vulnerable to wildfire. Post wildfire runoff water can contaminate water resources. Fire data collected by MODIS from 20002020 are used to create a hotspot map. Water resources and waterbody data originated from Department of Surveying and Mapping Malaysia used to identify the stream and dams that are exposed to wildfire. 5 class exposure level has been set to show the degree of closeness of water resources to wildfire hotspot area. Using the spatial analysis method, low to high level of potential wildfire-water exposures were able to be locate. Analysis shows, 7% of Johors water sources is exposed to medium levels of wildfire, while just 1% is exposed to the highest levels. The majority of the streams have very low levels of exposure. In addition, the wildfire-water exposure map aids in first respondent preparedness and planning.

Research areas: Wildfires
Global fire emissions buffered by the production of pyrogenic carbon (2019)

Landscape fires burn 35 million km2 of the Earths surface annually. They emit 2.2 Pg of carbon per year to the atmosphere, but also convert a significant fraction of the burned vegetation biomass into pyrogenic carbon. Pyrogenic carbon can be stored in terrestrial and marine pools for centuries to millennia and therefore its production can be considered a mechanism for long-term carbon sequestration. Pyrogenic carbon stocks and dynamics are not considered in global carbon cycle models, which leads to systematic errors in carbon accounting. Here we present a comprehensive dataset of pyrogenic carbon production factors from field and experimental fires and merge this with the Global Fire Emissions Database to quantify the global pyrogenic carbon production flux. We found that 256 (uncertainty range: 196340) Tg of biomass carbon was converted annually into pyrogenic carbon between 1997 and 2016. Our central estimate equates to 12% of the annual carbon emitted globally by landscape fires, which indicates that their emissions are buffered by pyrogenic carbon production. We further estimate that cumulative pyrogenic carbon production is 60 Pg since 1750, or 3340% of the global biomass carbon lost through land use change in this period. Our results demonstrate that pyrogenic carbon production by landscape fires could be a significant, but overlooked, sink for atmospheric CO2.

Research areas: Wildfires
Impact of Amazonian Fires on Atmospheric CO2 (2021)

Amazon rainforest fires have significant environmental and societal impacts, but the mechanism and impact of the fires on the regional and global carbon cycles have not been fully understood. Over the rainforest, less precipitation, higher surface temperature, and enhanced mid tropospheric sinking air over the eastern part of the Amazon characterized the fire/dry season. These meteorological conditions will facilitate more fires in the Amazon rainforest. Using the Orbiting Carbon Observatory 2 column CO<SUB>2</SUB>, we notice that there are ∼2 ppm more CO<SUB>2</SUB> over the Amazon compared with the surrounding area during the fire season. The higher concentrations of atmospheric CO<SUB>2</SUB> are related to the surface biomass burning, enhanced sinking air over the eastern part of the Amazon, and surface winds. Results from this study can help us better understand the carbon sources and sinks over the Amazon during the fire/dry season.

Research areas: Wildfires
Wildfire Damage Assessment over Australia Using Sentinel-2 Imagery and (2021)

Wildfires are major natural disasters negatively affecting human safety, natural ecosystems, and wildlife. Timely and accurate estimation of wildfire burn areas is particularly important for post-fire management and decision making. In this regard, Remote Sensing (RS) images are great resources due to their wide coverage, high spatial and temporal resolution, and low cost. In this study, Australian areas affected by wildfire were estimated using Sentinel-2 imagery and Moderate Resolution Imaging Spectroradiometer (MODIS) products within the Google Earth Engine (GEE) cloud computing platform. To this end, a framework based on change analysis was implemented in two main phases: (1) producing the binary map of burned areas (i.e., burned vs. unburned); (2) estimating burned areas of different Land Use/Land Cover (LULC) types. The first phase was implemented in five main steps: (i) preprocessing, (ii) spectral and spatial feature extraction for pre-fire and post-fire analyses; (iii) prediction of burned areas based on a change detection by differencing the pre-fire and post-fire datasets; (iv) feature selection; and (v) binary mapping of burned areas based on the selected features by the classifiers. The second phase was defining the types of LULC classes over the burned areas using the global MODIS land cover product (MCD12Q1). Based on the test datasets, the proposed framework showed high potential in detecting burned areas with an overall accuracy (OA) and kappa coefficient (KC) of 91.02% and 0.82, respectively. It was also observed that the greatest burned area among different LULC classes was related to evergreen needle leaf forests with burning rate of over 25 (%). Finally, the results of this study were in good agreement with the Landsat burned products.

Research areas: Wildfires
South American 2020 regional smoke plume: intercomparison with previous years,  impact on solar radiation, and the role of  Pantanal biomass burning season (2022)

Abstract. The 2020 biomass burning season in Brazil was marked by an atypical amount of fire across the Pantanal biome, which led to high levels of smoke within the biome and downwind areas. The present study analyzes fire counts and smoke over Pantanal in 2020, comparing this particular year's data with those from the previous 17 years (20032019). Taking as reference the most-polluted years in this period, the regional smoke plume and its impact on surface solar radiation were also evaluated. In 2020, the regional smoke plume core covered an area of  2.6106 km2 at the peak of the burning season, an area well above that of the previous 6 years but smaller than areas observed in a more remote past, as in 2007 and 2010 (> 5.0106 km2). The smoke loading was lower (mean aerosol optical depth, AOD, of 550 nm;  0.7) than that of 2007 and 2010 (mean AOD 550 nm;  1.0). The plume radiation absorption efficiency, when compared with the previous year's plumes, did not present significant differences. Regarding the Pantanal burning season, it revealed some atypical features. Fire counts were up to 3.0 times higher than for the years from 2003 to 2019. Smoke loading over Pantanal, which is typically a fraction of that over Amazonia, was higher in 2020 than that over Amazonia, an indication that local smoke surpassed the smoke advection from upwind regions. The observed intraseasonal variability in smoke over Pantanal revealed to be largely driven by the nature of the burned areas in the biome. From September on, there was a significant increase in fire count in conservation and indigenous areas, where higher biomass density is present, which would explain the larger smoke plumes over Pantanal, even during October when the fire count was reduced. In October, the biome was covered by a thick smoke layer, which resulted in a mean deficit of surface solar radiation up to 200 W m2. Despite the Pantanal biomes' massive burning in 2020, the regional smoke plume was not far from its climatological features. Nevertheless, the Pantanal 2020 burning season represents the worst combination of a climate extreme applied to a fire-prone environment, coupled with inadequately enforced environmental regulations, from which there is much to be learned.

Research areas: Wildfires
A New Picture of Fire Extent, Variability, and Drought Interaction in Prescribed Fire Landscapes: Insights From Florida Government Records (2018)

Florida, United States, government records provide a new resource for studying fire in landscapes managed with prescribed fire. In Florida, most fire area (92%) is prescribed. Current satellite fire products, which underpin most air pollution emission inventories, detect only 25% of burned area, which alters airborne emissions and environmental impacts. Moreover, these satellite products can misdiagnose spatiotemporal variability of fires. Overall fire area in Florida decreases during drought conditions as prescribed fires are avoided, but satellite data do not reflect this pattern. This pattern is consistent with prescribed fire successfully reducing overall fire risk and damages. Human management of prescribed fires and fuels can, therefore, break the conventional link between drought and wildfire and play an important role in mitigating rising fire risk in a changing climate. These results likely apply in other regions of the world with similar fire regimes.
Satellite-based estimation of global CO2 emissions from biomass burning (2021)

In this study, we estimate the global CO2 emissions from biomass burning using satellite data. A polynomial regression function calibrated the traditional vegetation index (NDVI) for assessing the aboveground biomass (AGB) using a process-based model (VISIT). Also, soil organic matter (SOM) modeled values from VISIT were also integrated into emissions calculation. MODISs finer spatial resolution at 1 km enabled to detect of small fires (in spatial scales of several m to km) than the Global Fire Emissions Database (GFED) 4.1s product at 25 km. Fire radiative power (FRP) of MODIS was used as a dynamic combustion completeness ratio since it provides variable values for every fire event. We delineated the monthly dynamics of fire emissions (FEs) in detail in terms of scale and strength. We addressed the following objectices: (1) estimate global FE considering dynamic combustion completeness by using FRP of MODIS, (2) characterize seasonal and regional patterns of wildfires, and (3) report uncertainties in GFED4.1s compared to our estimates. Our results on monthly time-series FEs agreed well with the GFED data. The annual averages of carbon (C) emissions from FEs were 1.25  0.12 PgC/year compared to 1.68  0.15 PgC/year from the GFED.

Research areas: Greenhouse Gases
Investigating dominant characteristics of fires across the Amazon during 2005-2014 through satellite data synthesis of combustion signatures (2016)

Estimates of fire emissions remain uncertain due to limited constraints on the variations in fire characteristics. Here we demonstrate the utility of space-based observations of smoke constituents in addressing this limitation. We introduce a satellite-derived smoke index (SI) as an indicator of the dominant phase of large-scale fires. This index is calculated as the ratio of the geometric mean of observed fractional enhancements (due to fire) in carbon monoxide and aerosol optical depth to that of nitrogen dioxide. We assess the usefulness of this index on fires in the Amazon. We analyze the seasonal, regional, and interannual joint distribution of SI and fire radiative power (FRP) in relation to fire hotspots, land cover, Drought Severity Index, and deforestation rate estimates. We also compare this index with an analogous quantity derived from field data or emission inventories. Our results show that SI changes from low (more flaming) to high (more smoldering) during the course of a fire season, which is consistent with the changes in observed maximum FRPs from high to low. We also find that flaming combustion is more dominant in areas where deforestation fires dominate, while smoldering combustion has a larger influence during drought years when understory fires are more likely enhanced. Lastly, we find that the spatiotemporal variation in SI is inconsistent with current emission inventories. Although we recognize some limitations of this approach, our results point to the utility of SI as a proxy for overall combustion efficiency in the parameterization of fire emission models.

Research areas: Wildfires
Investigation of the 2010 July–August fires impact on carbon monoxide atmospheric pollution in Moscow and its outskirts, estimating of emissions (2011)

We investigate the air pollution in the central European part of Russia during the 2010 summer fires. The results of ground-based (Institute of Atmospheric Physics (IAP), Moscow State University (MSU), and Zvenigorod Scientific Station (ZSS)) and satellite (MOPITT, AIRS, of Terra and Aqua satellites) measurements of the total content and concentration of carbon monoxide (CO), as well as MODIS data on the spatial and temporal distribution of forest and peat fires obtained from Terra and Aqua satellites, are presented. A comparison between similar situations in 2010 and 2002 revealed the causes of higher pollution levels in 2010. The use of trajectory analysis, detailed space imagery, and model calculations made it possible to reveal the location of peat fires and their contribution to the air pollution over the Moscow megalopolis. Fireemission estimates were obtained using two independent methods.

Research areas: Wildfires
Evaluation of a Bayesian Algorithm to Detect Burned Areas in the Canary (2018)

Burned Area (BA) is deemed as a primary variable to understand the Earth's climate system. Satellite remote sensing data have allowed for the development of various burned area detection algorithms that have been globally applied to and assessed in diverse ecosystems, ranging from tropical to boreal. In this paper, we present a Bayesian algorithm (BY-MODIS) that detects burned areas in a time series of Moderate Resolution Imaging Spectroradiometer (MODIS) images from 2002 to 2012 of the Canary Islands' dry woodlands and forests ecoregion (Spain). Based on daily image products MODIS, MOD09GQ (250 m), and MOD11A1 (1 km), the surface spectral reflectance and the land surface temperature, respectively, 10 day composites were built using the maximum temperature criterion. Variables used in BY-MODIS were the Global Environment Monitoring Index (GEMI) and Burn Boreal Forest Index (BBFI), alongside the NIR spectral band, all of which refer to the previous year and the year the fire took place in. Reference polygons for the 14 fires exceeding 100 hectares and identified within the period under analysis were developed using both post-fire LANDSAT images and official information from the forest fires national database by the Ministry of Agriculture and Fisheries, Food and Environment of Spain (MAPAMA). The results obtained by BY-MODIS can be compared to those by official burned area products, MCD45A1 and MCD64A1. Despite that the best overall results correspond to MCD64A1, BY-MODIS proved to be an alternative for burned area mapping in the Canary Islands, a region with a great topographic complexity and diverse types of ecosystems. The total burned area detected by the BY-MODIS classifier was 64.9% of the MAPAMA reference data, and 78.6% according to data obtained from the LANDSAT images, with the lowest average commission error (11%) out of the three products and a correlation (R<SUP>2</SUP>) of 0.82. The Bayesian algorithm—originally developed to detect burned areas in North American boreal forests using AVHRR archival data Long-Term Data Record—can be successfully applied to a lower latitude forest ecosystem totally different from the boreal ecosystem and using daily time series of satellite images from MODIS with a 250 m spatial resolution, as long as a set of training areas adequately characterising the dynamics of the forest canopy affected by the fire is defined.

Research areas: Wildfires
Radiative impacts of the Australian bushfires 20192020  Part 1: Large-scale radiative forcing (2022)

Abstract. As a consequence of extreme heat and drought, record-breaking wildfires developed and ravaged south-eastern Australia during the fire season 20192020. The fire strength reached its paroxysmal phase at the turn of the year 20192020. During this phase, pyrocumulonimbus clouds (pyroCb) developed and injected biomass burning aerosols and gases into the upper troposphere and lower stratosphere (UTLS). The UTLS aerosol layer was massively perturbed by these fires, with aerosol extinction increased by a factor of 3 in the visible spectral range in the Southern Hemisphere, with respect to a background atmosphere, and stratospheric aerosol optical depth reaching values as large as 0.015 in February 2020. Using the best available description of this event by observations, we estimate the radiative forcing (RF) of such perturbations of the Southern Hemispheric aerosol layer. We use offline radiative transfer modelling driven by observed information of the aerosol extinction perturbation and its spectral variability obtained from limb satellite measurements. Based on hypotheses on the absorptivity and the angular scattering properties of the aerosol layer, the regional (at three latitude bands in the Southern Hemisphere) clear-sky TOA (top-of-atmosphere) RF is found varying from small positive values to relatively large negative values (up to 2.0 W m2), and the regional clear-sky surface RF is found to be consistently negative and reaching large values (up to 4.5 W m2). We argue that clear-sky positive values are unlikely for this event, if the ageing/mixing of the biomass burning plume is mirrored by the evolution of its optical properties. Our best estimate for the area-weighted global-equivalent clear-sky RF is -0.350.21 (TOA RF) and -0.940.26 W m2 (surface RF), thus the strongest documented for a fire event and of comparable magnitude with the strongest volcanic eruptions of the post-Pinatubo era. The surplus of RF at the surface, with respect to TOA, is due to absorption within the plume that has contributed to the generation of ascending smoke vortices in the stratosphere. Highly reflective underlying surfaces, like clouds, can nevertheless swap negative to positive TOA RF, with global average RF as high as +1.0 W m2 assuming highly absorbing particles.

Research areas: Wildfires
Monthly Entomological Inoculation Rate Data for Studying the Seasonality of Malaria Transmission in Africa (2020)

A comprehensive literature review was conducted to create a new database of 197 field surveys of monthly malaria Entomological Inoculation Rates (EIR), a metric of malaria transmission intensity. All field studies provide data at a monthly temporal resolution and have a duration of at least one year in order to study the seasonality of the disease. For inclusion, data collection methodologies adhered to a specific standard and the location and timing of the measurements were documented. Auxiliary information on the population and hydrological setting were also included. The database includes measurements that cover West and Central Africa and the period from 1945 to 2011, and hence facilitates analysis of interannual transmission variability over broad regions.

Research areas: Public Health
Predicting future community-level ocular Chlamydia trachomatis infection prevalence using serological, clinical, molecular, and geospatial data (2022)

Trachoma is an infectious disease characterized by repeated exposures to Chlamydia trachomatis (Ct) that may ultimately lead to blindness. Efficient identification of communities with high infection burden could help target more intensive control efforts. We hypothesized that IgG seroprevalence in combination with geospatial layers, machine learning, and model-based geostatistics would be able to accurately predict future community-level ocular Ct infections detected by PCR. We used measurements from 40 communities in the hyperendemic Amhara region of Ethiopia to assess this hypothesis. Median Ct infection prevalence among children 05 years old increased from 6% at enrollment, in the context of recent mass drug administration (MDA), to 29% by month 36, following three years without MDA. At baseline, correlation between seroprevalence and Ct infection was stronger among children 05 years old ( = 0.77) than children 69 years old ( = 0.48), and stronger than the correlation between active trachoma and Ct infection (0-5y  = 0.56; 6-9y  = 0.40). Seroprevalence was the strongest concurrent predictor of infection prevalence at month 36 among children 05 years old (cross-validated R2 = 0.75, 95% CI: 0.580.85), though predictive performance declined substantially with increasing temporal lag between predictor and outcome measurements. Geospatial variables, a spatial Gaussian process, and stacked ensemble machine learning did not meaningfully improve predictions. Serological markers among children 05 years old may be an objective tool for identifying communities with high levels of ocular Ct infections, but accurate, future prediction in the context of changing transmission remains an open challenge.

Research areas: Public Health