Mapping canopy damage from understory fires in Amazon forests using annual time series of Landsat and MODIS data

Morton, Douglas C.; DeFries, Ruth; Nagol, Jyoteshwar; Souza, Carlos M.; Kasischke, Eric S.; Hurtt, George C.; Dubayah, R.

doi:10.1016/j.rse.2011.03.002

Cited by 107 publications

(88 citation statements)

References 61 publications

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“…The regional optimization of HESFIRE and its evaluation were performed using forest fire data derived from time series of MODIS data and the burned damage and recovery (BDR) algorithm (Morton et al, 2011a. The BDR approach detects the spectral trajectory of canopy damage from understory fires and recovery in subsequent years.…”

Section: Observation-derived Fire Datamentioning

confidence: 99%

“…The BDR approach detects the spectral trajectory of canopy damage from understory fires and recovery in subsequent years. The multiyear method discriminates understory fires from other disturbances such as deforestation or logging (Morton et al, 2011a).…”

Section: Observation-derived Fire Datamentioning

confidence: 99%

“…Understory fires are difficult to detect using satellite data because they do not burn the forest canopy, and only a few studies have inferred their extent in small regions to explore their dynamics and drivers (Alencar et al, 2004Ray et al, 2005). However, a method was recently developed to detect understory forest fires using multiyear satellite image time series (Morton et al, 2011a. These Amazon-wide observations provide a critical foundation to develop simulations of understory fire dynamics under future climate and land use scenarios.…”

Section: Introductionmentioning

confidence: 99%

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Synergy between land use and climate change increases future fire risk in Amazon forests

et al. 2017

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Abstract. Tropical forests have been a permanent feature of the Amazon basin for at least 55 million years, yet climate change and land use threaten the forest's future over the next century. Understory forest fires, which are common under the current climate in frontier forests, may accelerate Amazon forest losses from climatedriven dieback and deforestation. Far from land use frontiers, scarce fire ignitions and high moisture levels preclude significant burning, yet projected climate and land use changes may increase fire activity in these remote regions. Here, we used a fire model specifically parameterized for Amazon understory fires to examine the interactions between anthropogenic activities and climate under current and projected conditions. In a scenario of low mitigation efforts with substantial land use expansion and climate change -Representative Concentration Pathway (RCP) 8.5 -projected understory fires increase in frequency and duration, burning 4-28 times more forest in 2080-2100 than during 1990-2010. In contrast, active climate mitigation and land use contraction in RCP4.5 constrain the projected increase in fire activity to 0.9-5.4 times contemporary burned area. Importantly, if climate mitigation is not successful, land use contraction alone is very effective under low to moderate climate change, but does little to reduce fire activity under the most severe climate projections. These results underscore the potential for a fire-driven transformation of Amazon forests if recent regional policies for forest conservation are not paired with global efforts to mitigate climate change.

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Section: Observation-derived Fire Datamentioning

confidence: 99%

Section: Observation-derived Fire Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Synergy between land use and climate change increases future fire risk in Amazon forests

et al. 2017

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“…The former commonly uses image classification techniques to discriminate burned and unburned areas, such as supervised and unsupervised classification, decision trees and differencing and thresholding of spectral indices [64,65,[107][108][109]113,122]. However, in the two-phase approach, core burned areas are first defined from the most severe burn pixels based on active fire pixels or the threshold of vegetation indices, and then, contextual algorithms are employed to refine the classification of burn scars [121,125,142,147,148]. As shown in Table 3, the use of satellite data, such as AVHRR and MODIS, to detect hotspots during the period of interest has been widely applied to monitor burn areas in many studies in the boreal regions, since the hotspots represent burn activity.…”

Section: Remote Sensing Methods Results and Limitations For Burned Amentioning

confidence: 99%

Remote Sensing Techniques in Monitoring Post-Fire Effects and Patterns of Forest Recovery in Boreal Forest Regions: A Review

2013

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Abstract:The frequency and severity of forest fires, coupled with changes in spatial and temporal precipitation and temperature patterns, are likely to severely affect the characteristics of forest and permafrost patterns in boreal eco-regions. Forest fires, however, are also an ecological factor in how forest ecosystems form and function, as they affect the rate and characteristics of tree recruitment. A better understanding of fire regimes and forest recovery patterns in different environmental and climatic conditions will improve the management of sustainable forests by facilitating the process of forest resilience. Remote sensing has been identified as an effective tool for preventing and monitoring forest fires, as well as being a potential tool for understanding how forest ecosystems respond to them. However, a number of challenges remain before remote sensing practitioners will be able to better understand the effects of forest fires and how vegetation responds afterward. This article attempts to provide a comprehensive review of current research with respect to remotely sensed data and methods used to model post-fire effects and forest recovery patterns in boreal forest regions. The review reveals that remote sensing-based monitoring of post-fire effects and forest recovery patterns in boreal forest regions is not only limited by the gaps in both field data and remotely sensed data, but also the complexity of far-northern fire regimes, climatic conditions and environmental conditions. We expect that the integration of different remotely sensed data coupled with field campaigns can provide an important data source to support the monitoring of post-fire effects and forest recovery patterns. Additionally, the variation and stratification of pre-and post-fire vegetation and environmental conditions should be considered to achieve a reasonable, operational model for monitoring post-fire effects and forest patterns in boreal regions.

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“…Fire detection and burned area mapping are most typically performed with coarse spatial resolution (.250 m) satellite data which offer high temporal frequency enabling near real time monitoring of the development of the burning season (Setzer and Pereira 1991;Tansey et al 2008;Giglio et al 2009;Morton et al 2011). However, burned area monitoring limited to coarse spatial resolution data may distort both the overall burned area estimate and the spatial distribution of burned area (Laris 2005;Miettinen and Liew 2009).…”

Section: Introductionmentioning

confidence: 99%

On the extent of fire-induced forest degradation in Mato Grosso, Brazilian Amazon, in 2000, 2005 and 2010

Miettinen

Shimabukuro

Beuchle

et al. 2016

Int. J. Wildland Fire

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Abstract. In this paper we analyse the extent of fire-induced forest degradation in Mato Grosso State, Brazil. We utilise a sample based approach used in a previous pan-tropical deforestation survey to derive information on land cover and burned areas in the two major biomes of Mato Grosso: Amazon and Cerrado. Land cover and burned area are mapped for three years (2000-2005-2010) over 77 sample sites (10 000 ha each) distributed systematically throughout the state which covers 90.337 Mha. Our results indicate continuing forest degradation by fires in the state and potentially increasing fire susceptibility of the Amazon forests, regardless of the decrease in deforestation. 2010 witnessed the most extensive fireinduced forest degradation (,300 000 ha) in the forests of the Amazon biome among the study years, regardless of the fact that the fire season was less severe than in 2005. Deforestation in the Amazon biome in Mato Grosso dropped from 590 000 ha year À1 in the 2000-2005 period to 190 000 ha year À1 in the second half of the decade. The findings of this study advocate the inclusion of forest fire effects into carbon accounting initiatives.

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Mapping canopy damage from understory fires in Amazon forests using annual time series of Landsat and MODIS data

Cited by 107 publications

References 61 publications

Synergy between land use and climate change increases future fire risk in Amazon forests

Synergy between land use and climate change increases future fire risk in Amazon forests

Remote Sensing Techniques in Monitoring Post-Fire Effects and Patterns of Forest Recovery in Boreal Forest Regions: A Review

On the extent of fire-induced forest degradation in Mato Grosso, Brazilian Amazon, in 2000, 2005 and 2010

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