scholarly journals Accuracy Assessments of MTBS and AFS 30m Resolution Burned area Products

2018 ◽  
Author(s):  
Zhaoming Zhang ◽  
Guojin He ◽  
Tengfei Long ◽  
Mengmeng Wang ◽  
Guizhou Wang ◽  
...  
Keyword(s):  
Burned Area ◽  
Accuracy Assessments

scholarly journals AEGIS: a wildfire prevention and management information system

2016 ◽  
Vol 16 (3) ◽  
pp. 643-661 ◽  
Author(s):  
Kostas Kalabokidis ◽  
Alan Ager ◽  
Mark Finney ◽  
Nikos Athanasis ◽  
Palaiologos Palaiologou ◽  
...  
Keyword(s):  
Fire Hazard ◽  
Fire Behavior ◽  
End Users ◽  
Burned Area ◽  
Fire Control ◽  
Web Based ◽  
Ignition Point ◽  
Weather Information ◽  
Management Platform ◽  
Burn Probability

Abstract. We describe a Web-GIS wildfire prevention and management platform (AEGIS) developed as an integrated and easy-to-use decision support tool to manage wildland fire hazards in Greece (http://aegis.aegean.gr). The AEGIS platform assists with early fire warning, fire planning, fire control and coordination of firefighting forces by providing online access to information that is essential for wildfire management. The system uses a number of spatial and non-spatial data sources to support key system functionalities. Land use/land cover maps were produced by combining field inventory data with high-resolution multispectral satellite images (RapidEye). These data support wildfire simulation tools that allow the users to examine potential fire behavior and hazard with the Minimum Travel Time fire spread algorithm. End-users provide a minimum number of inputs such as fire duration, ignition point and weather information to conduct a fire simulation. AEGIS offers three types of simulations, i.e., single-fire propagation, point-scale calculation of potential fire behavior, and burn probability analysis, similar to the FlamMap fire behavior modeling software. Artificial neural networks (ANNs) were utilized for wildfire ignition risk assessment based on various parameters, training methods, activation functions, pre-processing methods and network structures. The combination of ANNs and expected burned area maps are used to generate integrated output map of fire hazard prediction. The system also incorporates weather information obtained from remote automatic weather stations and weather forecast maps. The system and associated computation algorithms leverage parallel processing techniques (i.e., High Performance Computing and Cloud Computing) that ensure computational power required for real-time application. All AEGIS functionalities are accessible to authorized end-users through a web-based graphical user interface. An innovative smartphone application, AEGIS App, also provides mobile access to the web-based version of the system.

scholarly journals Uni-Temporal Multispectral Imagery for Burned Area Mapping with Deep Learning

2021 ◽  
Vol 13 (8) ◽  
pp. 1509
Author(s):  
Xikun Hu ◽  
Yifang Ban ◽  
Andrea Nascetti
Keyword(s):  
Deep Learning ◽  
Large Scale ◽  
Multiple Scales ◽  
Detection Methods ◽  
Burned Area ◽  
Landsat 8 ◽  
Multispectral Imagery ◽  
Burned Areas ◽  
Local Climate Zones ◽  
Sentinel 2

Accurate burned area information is needed to assess the impacts of wildfires on people, communities, and natural ecosystems. Various burned area detection methods have been developed using satellite remote sensing measurements with wide coverage and frequent revisits. Our study aims to expound on the capability of deep learning (DL) models for automatically mapping burned areas from uni-temporal multispectral imagery. Specifically, several semantic segmentation network architectures, i.e., U-Net, HRNet, Fast-SCNN, and DeepLabv3+, and machine learning (ML) algorithms were applied to Sentinel-2 imagery and Landsat-8 imagery in three wildfire sites in two different local climate zones. The validation results show that the DL algorithms outperform the ML methods in two of the three cases with the compact burned scars, while ML methods seem to be more suitable for mapping dispersed burn in boreal forests. Using Sentinel-2 images, U-Net and HRNet exhibit comparatively identical performance with higher kappa (around 0.9) in one heterogeneous Mediterranean fire site in Greece; Fast-SCNN performs better than others with kappa over 0.79 in one compact boreal forest fire with various burn severity in Sweden. Furthermore, directly transferring the trained models to corresponding Landsat-8 data, HRNet dominates in the three test sites among DL models and can preserve the high accuracy. The results demonstrated that DL models can make full use of contextual information and capture spatial details in multiple scales from fire-sensitive spectral bands to map burned areas. Using only a post-fire image, the DL methods not only provide automatic, accurate, and bias-free large-scale mapping option with cross-sensor applicability, but also have potential to be used for onboard processing in the next Earth observation satellites.

scholarly journals CNN-based burned area mapping using radar and optical data

2021 ◽  
Vol 260 ◽  
pp. 112468
Author(s):  
Miguel A. Belenguer-Plomer ◽  
Mihai A. Tanase ◽  
Emilio Chuvieco ◽  
Francesca Bovolo
Keyword(s):  
Optical Data ◽  
Burned Area ◽  
Burned Area Mapping

scholarly journals Assessing Wood and Soil Carbon Losses from a Forest-Peat Fire in the Boreo-Nemoral Zone

Forests ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 880
Author(s):  
Andrey Sirin ◽  
Alexander Maslov ◽  
Dmitry Makarov ◽  
Yakov Gulbe ◽  
Hans Joosten
Keyword(s):  
Soil Carbon ◽  
Stand Structure ◽  
Peat Soil ◽  
Burned Area ◽  
Tree Biomass ◽  
Carbon Loss ◽  
Forest Stand Structure ◽  
Peat Fire ◽  
Peat Fires ◽  
Carbon Losses

Forest-peat fires are notable for their difficulty in estimating carbon losses. Combined carbon losses from tree biomass and peat soil were estimated at an 8 ha forest-peat fire in the Moscow region after catastrophic fires in 2010. The loss of tree biomass carbon was assessed by reconstructing forest stand structure using the classification of pre-fire high-resolution satellite imagery and after-fire ground survey of the same forest classes in adjacent areas. Soil carbon loss was assessed by using the root collars of stumps to reconstruct the pre-fire soil surface and interpolating the peat characteristics of adjacent non-burned areas. The mean (median) depth of peat losses across the burned area was 15 ± 8 (14) cm, varying from 13 ± 5 (11) to 20 ± 9 (19). Loss of soil carbon was 9.22 ± 3.75–11.0 ± 4.96 (mean) and 8.0–11.0 kg m−2 (median); values exceeding 100 tC ha−1 have also been found in other studies. The estimated soil carbon loss for the entire burned area, 98 (mean) and 92 (median) tC ha−1, significantly exceeds the carbon loss from live (tree) biomass, which averaged 58.8 tC ha−1. The loss of carbon in the forest-peat fire thus equals the release of nearly 400 (soil) and, including the biomass, almost 650 tCO2 ha−1 into the atmosphere, which illustrates the underestimated impact of boreal forest-peat fires on atmospheric gas concentrations and climate.

scholarly journals Understanding the Impact of Different Landscape-Level Fuel Management Strategies on Wildfire Hazard in Central Portugal

Forests ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 522
Author(s):  
Akli Benali ◽  
Ana C. L. Sá ◽  
João Pinho ◽  
Paulo M. Fernandes ◽  
José M. C. Pereira
Keyword(s):  
Management Strategies ◽  
Treatment Strategies ◽  
Fire Season ◽  
Burned Area ◽  
Treatment Area ◽  
Fuel Treatment ◽  
The North ◽  
Wildfire Hazard ◽  
Central Portugal ◽  
The Impact

The extreme 2017 fire season in Portugal led to widespread recognition of the need for a paradigm shift in forest and wildfire management. We focused our study on Alvares, a parish in central Portugal located in a fire-prone area, which had 60% of its area burned in 2017. We evaluated how different fuel treatment strategies may reduce wildfire hazard in Alvares through (i) a fuel break network with different extents corresponding to different levels of priority and (ii) random fuel treatments resulting from a potential increase in stand-level management intensity. To assess this, we developed a stochastic wildfire simulation system (FUNC-SIM) that integrates uncertainties in fuel distribution over the landscape. If the landscape remains unchanged, Alvares will have large burn probabilities in the north, northeast and center-east areas of the parish that are very often associated with high fireline intensities. The different fuel treatment scenarios decreased burned area between 12.1–31.2%, resulting from 1–4.6% increases in the annual treatment area and reduced the likelihood of wildfires larger than 5000 ha by 10–40%. On average, simulated burned area decreased 0.22% per each ha treated, and cost-effectiveness decreased with increasing area treated. Overall, both fuel treatment strategies effectively reduced wildfire hazard and should be part of a larger, holistic and integrated plan to reduce the vulnerability of the Alvares parish to wildfires.

scholarly journals Demographic Effects of Severe Fire in Montane Shrubland on Tasmania’s Central Plateau

Fire ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 32
Author(s):  
Judy A. Foulkes ◽  
Lynda D. Prior ◽  
Steven W. J. Leonard ◽  
David M. J. S. Bowman
Keyword(s):  
Woody Species ◽  
Fire Frequency ◽  
Fire Season ◽  
Burned Area ◽  
Large Area ◽  
Seedling Regeneration ◽  
Central Plateau ◽  
Conservation Area ◽  
Severe Fire ◽  
Representative Area

Australian montane sclerophyll shrubland vegetation is widely considered to be resilient to infrequent severe fire, but this may not be the case in Tasmania. Here, we report on the vegetative and seedling regeneration response of a Tasmanian non-coniferous woody montane shrubland following a severe fire, which burned much of the Great Pine Tier in the Central Plateau Conservation Area during the 2018–2019 fire season when a historically anomalously large area was burned in central Tasmania. Our field survey of a representative area burned by severe crown fire revealed that more than 99% of the shrubland plants were top-killed, with only 5% of the burnt plants resprouting one year following the fire. Such a low resprouting rate means the resilience of the shrubland depends on seedling regeneration from aerial and soil seedbanks or colonization from plants outside the burned area. Woody species’ seedling densities were variable but generally low (25 m−2). The low number of resprouters, and reliance on seedlings for recovery, suggest the shrubland may not be as resilient to fire as mainland Australian montane shrubland, particularly given a warming climate and likely increase in fire frequency.

scholarly journals Using the Landsat Burned Area Products to Derive Fire History Relevant for Fire Management and Conservation in the State of Florida, Southeastern USA

Fire ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 26
Author(s):  
Casey Teske ◽  
Melanie K. Vanderhoof ◽  
Todd J. Hawbaker ◽  
Joe Noble ◽  
John Kevin Hiers
Keyword(s):  
Prescribed Fire ◽  
Spatial Data ◽  
Fire History ◽  
Fire Management ◽  
Fire Behavior ◽  
Fire Risk ◽  
Behavior Modeling ◽  
Burned Area ◽  
Burned Areas ◽  
Burn Probability

Development of comprehensive spatially explicit fire occurrence data remains one of the most critical needs for fire managers globally, and especially for conservation across the southeastern United States. Not only are many endangered species and ecosystems in that region reliant on frequent fire, but fire risk analysis, prescribed fire planning, and fire behavior modeling are sensitive to fire history due to the long growing season and high vegetation productivity. Spatial data that map burned areas over time provide critical information for evaluating management successes. However, existing fire data have undocumented shortcomings that limit their use when detailing the effectiveness of fire management at state and regional scales. Here, we assessed information in existing fire datasets for Florida and the Landsat Burned Area products based on input from the fire management community. We considered the potential of different datasets to track the spatial extents of fires and derive fire history metrics (e.g., time since last burn, fire frequency, and seasonality). We found that burned areas generated by applying a 90% threshold to the Landsat burn probability product matched patterns recorded and observed by fire managers at three pilot areas. We then created fire history metrics for the entire state from the modified Landsat Burned Area product. Finally, to show their potential application for conservation management, we compared fire history metrics across ownerships for natural pinelands, where prescribed fire is frequently applied. Implications of this effort include increased awareness around conservation and fire management planning efforts and an extension of derivative products regionally or globally.

scholarly journals Short-Term Effects of Fire Severity on Vegetation Based on Sentinel-2 Satellite Data

2021 ◽  
Vol 13 (1) ◽  
pp. 432
Author(s):  
Aru Han ◽  
Song Qing ◽  
Yongbin Bao ◽  
Li Na ◽  
Yuhai Bao ◽  
...  
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Vegetation Change ◽  
Fire Severity ◽  
Dynamic Change ◽  
Burned Area ◽  
Fire Event ◽  
Vegetation Dynamic ◽  
Area Index ◽  
Sentinel 2

An important component in improving the quality of forests is to study the interference intensity of forest fires, in order to describe the intensity of the forest fire and the vegetation recovery, and to improve the monitoring ability of the dynamic change of the forest. Using a forest fire event in Bilahe, Inner Monglia in 2017 as a case study, this study extracted the burned area based on the BAIS2 index of Sentinel-2 data for 2016–2018. The leaf area index (LAI) and fractional vegetation cover (FVC), which are more suitable for monitoring vegetation dynamic changes of a burned area, were calculated by comparing the biophysical and spectral indices. The results showed that patterns of change of LAI and FVC of various land cover types were similar post-fire. The LAI and FVC of forest and grassland were high during the pre-fire and post-fire years. During the fire year, from the fire month (May) through the next 4 months (September), the order of areas of different fire severity in terms of values of LAI and FVC was: low > moderate > high severity. During the post fire year, LAI and FVC increased rapidly in areas of different fire severity, and the ranking of areas of different fire severity in terms of values LAI and FVC was consistent with the trend observed during the pre-fire year. The results of this study can improve the understanding of the mechanisms involved in post-fire vegetation change. By using quantitative inversion, the health trajectory of the ecosystem can be rapidly determined, and therefore this method can play an irreplaceable role in the realization of sustainable development in the study area. Therefore, it is of great scientific significance to quantitatively retrieve vegetation variables by remote sensing.

scholarly journals Hot and cold flavors of southern California’s Santa Ana winds: their causes, trends, and links with wildfire

2021 ◽  
Author(s):  
Alexander Gershunov ◽  
Janin Guzman Morales ◽  
Benjamin Hatchett ◽  
Kristen Guirguis ◽  
Rosana Aguilera ◽  
...  
Keyword(s):  
Great Basin ◽  
Heat Waves ◽  
Early Warning Systems ◽  
High Amplitude ◽  
Warming Trend ◽  
Snow Accumulation ◽  
Burned Area ◽  
Rossby Wave Breaking ◽  
Santa Ana ◽  
Santa Ana Winds

AbstractSanta Ana winds (SAWs) are associated with anomalous temperatures in coastal Southern California (SoCal). As dry air flows over SoCal’s coastal ranges on its way from the elevated Great Basin down to sea level, all SAWs warm adiabatically. Many but not all SAWs produce coastal heat events. The strongest regionally averaged SAWs tend to be cold. In fact, some of the hottest and coldest observed temperatures in coastal SoCal are linked to SAWs. We show that hot and cold SAWs are produced by distinct synoptic dynamics. High-amplitude anticyclonic flow around a blocking high pressure aloft anchored at the California coast produces hot SAWs. Cold SAWs result from anticyclonic Rossby wave breaking over the northwestern U.S. Hot SAWs are preceded by warming in the Great Basin and dry conditions across the Southwestern U.S. Precipitation over the Southwest, including SoCal, and snow accumulation in the Great Basin usually precede cold SAWs. Both SAW flavors, but especially the hot SAWs, yield low relative humidity at the coast. Although cold SAWs tend to be associated with the strongest winds, hot SAWs tend to last longer and preferentially favor wildfire growth. Historically, out of large (> 100 acres) SAW-spread wildfires, 90% were associated with hot SAWs, accounting for 95% of burned area. As health impacts of SAW-driven coastal fall, winter and spring heat waves and impacts of smoke from wildfires have been recently identified, our results have implications for designing early warning systems. The long-term warming trend in coastal temperatures associated with SAWs is focused on January–March, when hot and cold SAW frequency and temperature intensity have been increasing and decreasing, respectively, over our 71-year record.

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