Tools for Assessing the Impacts of Climate Variability and Change on Wildfire Regimes in Forests

Herawati, H.; Wijaya, Arief; Martius, Christopher; Purnomo, Herry; Andriani, R.

doi:10.3390/f6051476

Cited by 14 publications

(14 citation statements)

References 132 publications

(132 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Since they are designed to predict fire behavior at the landscape scale over the course of several days, they are not applicable to long‐term projections of future fire activity. However, output from behavior models could be used to validate or adjust longer‐term projections of fire activity …”

Section: Approaches Relevant To Understanding Future Fire Activitymentioning

confidence: 99%

“…However, output from behavior models could be used to validate or adjust longer-term projections of fire activity. 179…”

Section: Fire Behavior Modelsmentioning

confidence: 99%

“…IFVMs integrate fire and vegetation models to study shifts in fire regimes resulting from changing conditions, while DGVMs model changing vegetation dynamics. 179 When coupled with GCMs, IFVMs are powerful tools for understanding future climate interactions with vegetation dynamics and fire, although the same limitations in the parameterisation of mechanisms apply. Examples include Global FIRe Model (GlobFIRM) 202 and The Large-fire Simulator (FSim).…”

Section: Integrated Fire-vegetation Modelsmentioning

confidence: 99%

See 2 more Smart Citations

Climate–vegetation–fire interactions and feedbacks: trivial detail or major barrier to projecting the future of the Earth system?

Harris

Remenyi

Williamson³

et al. 2016

WIREs Climate Change

View full text Add to dashboard Cite

Fire is a complex process involving interactions and feedbacks between biological, socioeconomic, and physical drivers across multiple spatial and temporal scales. This complexity limits our ability to incorporate fire into Earth system models and project future fire activity under climate change. Conceptual, empirical, and process models have identified the mechanisms and processes driving fire regimes, and provide a useful basis to consider future fire activity. However, these models generally deal with only one component of fire regimes, fire frequency, and do not incorporate feedbacks between fire, vegetation, and climate. They are thus unable to predict the location, severity or timing of fires, the socioecological impacts of fire regime change, or potential non‐linear responses such as biome shifts into alternative stable states. Dynamic modeling experiments may facilitate more thorough investigations of fire–vegetation–climate feedbacks and interactions, but their success will depend on the development of dynamic global vegetation models (DGVMs) that more accurately represent biological drivers. This requires improvements in the representation of current vegetation, plant responses to fire, ecological dynamics, and land management to capture the mechanisms behind fire frequency, intensity, and timing. DGVMs with fire modules are promising tools to develop a globally consistent analysis of fire activity, but projecting future fire activity will ultimately require a transdisciplinary synthesis of the biological, atmospheric, and socioeconomic drivers of fire. This is an important goal because fire causes substantial economic disruption and contributes to future climate change through its influence on albedo and the capacity of the biosphere to store carbon. WIREs Clim Change 2016, 7:910–931. doi: 10.1002/wcc.428 This article is categorized under: Climate Models and Modeling > Model Components Assessing Impacts of Climate Change > Evaluating Future Impacts of Climate Change Climate, Ecology, and Conservation > Observed Ecological Changes

show abstract

Section: Approaches Relevant To Understanding Future Fire Activitymentioning

confidence: 99%

“…However, output from behavior models could be used to validate or adjust longer-term projections of fire activity. 179…”

Section: Fire Behavior Modelsmentioning

confidence: 99%

Section: Integrated Fire-vegetation Modelsmentioning

confidence: 99%

See 1 more Smart Citation

Climate–vegetation–fire interactions and feedbacks: trivial detail or major barrier to projecting the future of the Earth system?

Harris

Remenyi

Williamson³

et al. 2016

WIREs Climate Change

View full text Add to dashboard Cite

show abstract

“…Mediterranean ecosystems (Keeley et al 2011), but its intensity and frequency are altered by humans in many areas as a result of land use change (Bucini and Lambin 2002) or, as in the present study, of an accidental fire. Multispectral sensors have been used to monitor active fire, map burned area, or quantify fuel availability and flammability (Herawati et al 2015).…”

Section: Discussionmentioning

confidence: 99%

The potentiality of Sentinel-2 to assess the effect of fire events on Mediterranean mountain vegetation

Simone¹,

Musciano²,

Cecco³

et al. 2020

Plant Sociology

View full text Add to dashboard Cite

Wildfires are currently one of the most important environmental problems, as they cause disturbance in ecosystems generating environmental, economic and social costs. The Sentinel-2 from Copernicus Program (Sentinel satellites) offers a great tool for post-fire monitoring. The main objective of this study is to evaluate the potential of Sentinel-2 in a peculiar mountainous landscape by measuring and identifying the burned areas and monitor the short-term response of the vegetation in different ‘burn severity’ classes. A Sentinel-2 dataset was created, and pre-processing operations were performed. Relativized Burn Ratio (RBR) was calculated to identify ‘burn scar’ and discriminate the ‘burn severity’ classes. A two-year monitoring was carried out with areas identified based on different severity classes, using Normalized Difference Vegetation Index (NDVI) to investigate the short-term vegetation dynamics of the burned habitats; habitats refer to Annex I of the European Directive 92/43/EEC. The study area is located in ‘Campo Imperatore’ within the Gran Sasso – Monti della Laga National Park (central Italy). The first important result was the identification and quantification of the area affected by fire. The RBR allowed us to identify even the less damaged habitats with high accuracy. The survey highlighted the importance of these Open-source tools for qualitative and quantitative evaluation of fires and the short-term assessment of vegetation recovery dynamics. The information gathered by this type of monitoring can be used by decision-makers both for emergency management and for possible environmental restoration of the burned areas.

show abstract

“…The parameters such as temperature, precipitation, humidity, wind, slope, vegetation cover and soil types can greatly influence the intensity and spreading of fire [5]. Therefore, it is important to have adequate knowledge on those parameters to understand the fire risk assessment.…”

Section: Introductionmentioning

confidence: 99%

Risk assessment for forest fire in Brunei Darussalam

et al. 2019

View full text Add to dashboard Cite

The rise in global warming triggered by climate change and increased slush and burn activities particularly in Indonesia has been a major concern for deteriorating air pollution in Borneo regions in last two decades. Brunei Darussalam is facing increasing fire risk particularly during the dry season (February to April) of the year. The study is an effort to focus on the recent rise of fire events in Brunei Darussalam as fires can tremendously downgrade the quality of the country’s well-known forestry; affect the economy and most importantly, health of the people. Geographical Information System (GIS) have been widely used by researchers to study fire risk assessment. The ArcGIS software is used for Optimized Hot Spot Analysis, Inversed Distance Weighted (IDW), and Kriging to compare and analyse the data and prepare a map for identifications of hotspot areas. High temperatures due to the El Nino phenomenon and low precipitation contribute greatly to the forest fire outbreaks. Results show that the Brunei-Muara district is mostly affected compared to Tutong and Belait districts. From the hotspots identified, the percentages of forest areas affected are 53%, 64%, 25% in Brunei-Muara, Tutong and Belait districts respectively.

show abstract

Tools for Assessing the Impacts of Climate Variability and Change on Wildfire Regimes in Forests

Cited by 14 publications

References 132 publications

Climate–vegetation–fire interactions and feedbacks: trivial detail or major barrier to projecting the future of the Earth system?

Climate–vegetation–fire interactions and feedbacks: trivial detail or major barrier to projecting the future of the Earth system?

The potentiality of Sentinel-2 to assess the effect of fire events on Mediterranean mountain vegetation

Risk assessment for forest fire in Brunei Darussalam

Contact Info

Product

Resources

About