scholarly journals A New Application of the Disturbance Index for Fire Severity in Coastal Dunes

2021 ◽  
Vol 13 (23) ◽  
pp. 4739
Author(s):  
Marcio D. DaSilva ◽  
David Bruce ◽  
Patrick A. Hesp ◽  
Graziela Miot da Silva
Keyword(s):  
Vegetation Index ◽  
Fire Severity ◽  
Coastal Dune ◽  
Burn Severity ◽  
Soil Conditions ◽  
Initiation Mechanism ◽  
Disturbance Index ◽  
Dune Systems ◽  
Normalised Difference Vegetation Index ◽  
Vegetation Loss

Fires are a disturbance that can lead to short term dune destabilisation and have been suggested to be an initiation mechanism of a transgressive dune phase when paired with changing climatic conditions. Fire severity is one potential factor that could explain subsequent coastal dune destabilisations, but contemporary evidence of destabilisation following fire is lacking. In addition, the suitability of conventional satellite Earth Observation methods to detect the impacts of fire and the relative fire severity in coastal dune environments is in question. Widely applied satellite-derived burn indices (Normalised Burn Index and Normalised Difference Vegetation Index) have been suggested to underestimate the effects of fire in heterogenous landscapes or areas with sparse vegetation cover. This work assesses burn severity from high resolution aerial and Sentinel 2 satellite imagery following the 2019/2020 Black Summer fires on Kangaroo Island in South Australia, to assess the efficacy of commonly used satellite indices, and validate a new method for assessing fire severity in coastal dune systems. The results presented here show that the widely applied burn indices derived from NBR differentially assess vegetation loss and fire severity when compared in discrete soil groups across a landscape that experienced a very high severity fire. A new application of the Tasselled Cap Transformation (TCT) and Disturbance Index (DI) is presented. The differenced Disturbance Index (dDI) improves the estimation of burn severity, relative vegetation loss, and minimises the effects of differing soil conditions in the highly heterogenous landscape of Kangaroo Island. Results suggest that this new application of TCT is better suited to diverse environments like Mediterranean and semi-arid coastal regions than existing indices and can be used to better assess the effects of fire and potential remobilisation of coastal dune systems.

scholarly journals Urban Fire Severity and Vegetation Dynamics in Southern California

2020 ◽  
Vol 13 (1) ◽  
pp. 19
Author(s):  
Lauren E. H. Mathews ◽  
Alicia M. Kinoshita
Keyword(s):  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Current Knowledge ◽  
Fire Severity ◽  
Satellite Image ◽  
Burn Severity ◽  
Native Vegetation ◽  
Riparian Areas ◽  
The Impact

A combination of satellite image indices and in-field observations was used to investigate the impact of fuel conditions, fire behavior, and vegetation regrowth patterns, altered by invasive riparian vegetation. Satellite image metrics, differenced normalized burn severity (dNBR) and differenced normalized difference vegetation index (dNDVI), were approximated for non-native, riparian, or upland vegetation for traditional timeframes (0-, 1-, and 3-years) after eleven urban fires across a spectrum of invasive vegetation cover. Larger burn severity and loss of green canopy (NDVI) was detected for riparian areas compared to the uplands. The presence of invasive vegetation affected the distribution of burn severity and canopy loss detected within each fire. Fires with native vegetation cover had a higher severity and resulted in larger immediate loss of canopy than fires with substantial amounts of non-native vegetation. The lower burn severity observed 1–3 years after the fires with non-native vegetation suggests a rapid regrowth of non-native grasses, resulting in a smaller measured canopy loss relative to native vegetation immediately after fire. This observed fire pattern favors the life cycle and perpetuation of many opportunistic grasses within urban riparian areas. This research builds upon our current knowledge of wildfire recovery processes and highlights the unique challenges of remotely assessing vegetation biophysical status within urban Mediterranean riverine systems.

scholarly journals Effects of Soil Abiotic and Biotic Factors on Tree Seedling Regeneration Following a Boreal Forest Wildfire

Ecosystems ◽  
2021 ◽  
Author(s):  
Theresa S. Ibáñez ◽  
David A. Wardle ◽  
Michael J. Gundale ◽  
Marie-Charlotte Nilsson
Keyword(s):  
Boreal Forest ◽  
Betula Pendula ◽  
Fire Severity ◽  
Tree Regeneration ◽  
Soil Biota ◽  
Fire Disturbance ◽  
Burn Severity ◽  
Soil Conditions ◽  
Tree Seedling ◽  
Seedling Regeneration

AbstractWildfire disturbance is important for tree regeneration in boreal ecosystems. A considerable amount of literature has been published on how wildfires affect boreal forest regeneration. However, we lack understanding about how soil-mediated effects of fire disturbance on seedlings occur via soil abiotic properties versus soil biota. We collected soil from stands with three different severities of burning (high, low and unburned) and conducted two greenhouse experiments to explore how seedlings of tree species (Betula pendula, Pinus sylvestris and Picea abies) performed in live soils and in sterilized soil inoculated by live soil from each of the three burning severities. Seedlings grown in live soil grew best in unburned soil. When sterilized soils were reinoculated with live soil, seedlings of P. abies and P. sylvestris grew better in soil from low burn severity stands than soil from either high severity or unburned stands, demonstrating that fire disturbance may favor post-fire regeneration of conifers in part due to the presence of soil biota that persists when fire severity is low or recovers quickly post-fire. Betula pendula did not respond to soil biota and was instead driven by changes in abiotic soil properties following fire. Our study provides strong evidence that high fire severity creates soil conditions that are adverse for seedling regeneration, but that low burn severity promotes soil biota that stimulates growth and potential regeneration of conifers. It also shows that species-specific responses to abiotic and biotic soil characteristics are altered by variation in fire severity. This has important implications for tree regeneration because it points to the role of plant–soil–microbial feedbacks in promoting successful establishment, and potentially successional trajectories and species dominance in boreal forests in the future as fire regimes become increasingly severe through climate change.

scholarly journals Pinus halepensis regeneration after a wildfire in a semiarid environment: assessment using multitemporal Landsat images

2011 ◽  
Vol 20 (2) ◽  
pp. 195 ◽  
Author(s):  
Sergio M. Vicente-Serrano ◽  
Fernando Pérez-Cabello ◽  
Teodoro Lasanta
Keyword(s):  
Spatial Pattern ◽  
Vegetation Index ◽  
Pinus Halepensis ◽  
Strong Relationship ◽  
Burn Severity ◽  
Spatial And Temporal Patterns ◽  
Landsat Images ◽  
Normalised Difference Vegetation Index ◽  
Spatial Differences ◽  
Terrain Elevation

We studied the spatial and temporal patterns of forest regeneration using a 24-year time series of Landsat images and the normalised difference vegetation index (NDVI) in a homogeneous Pinus halepensis forest, 3000 ha of which were extensively burned in 1995. We demonstrated a progressive slow and linear recovery in NDVI values, based on Landsat images between 1997 and 2007. The forest tended to recover to pre-disturbance conditions, both with respect to the magnitude of the NDVI and in terms of the spatial pattern. We found that the spatial differences in the rates of NDVI recovery were not affected by the burn severity. Moreover, burn severity did not affect the rates of NDVI recovery after the fire. Although highly homogeneous P. halepensis regeneration was the dominant pattern in the study area (more than the 70% of the burn area showed positive and significant trends), some spatial differences in the magnitude of change were observed. The forest tended to recover the spatial pattern corresponding to pre-fire conditions, although it was difficult to establish whether terrain elevation or previous tree size and density were the main governing factors, given the strong relationship between them.

Beyond Landsat: a comparison of four satellite sensors for detecting burn severity in ponderosa pine forests of the Gila Wilderness, NM, USA

2010 ◽  
Vol 19 (4) ◽  
pp. 449 ◽  
Author(s):  
Zachary A. Holden ◽  
Penelope Morgan ◽  
Alistair M. S. Smith ◽  
Lee Vierling
Keyword(s):  
Ponderosa Pine ◽  
Vegetation Index ◽  
Thermal Emission ◽  
Burn Severity ◽  
Future Research ◽  
Accurate Information ◽  
Ponderosa Pine Forests ◽  
Normalised Difference Vegetation Index ◽  
Satellite Sensors ◽  
Gila Wilderness

Methods of remotely measuring burn severity are needed to evaluate the ecological and environmental impacts of large, remote wildland fires. The challenges that were associated with the Landsat program highlight the need to evaluate alternative sensors for characterising post-fire effects. We compared statistical correlations between 55 Composite Burn Index field plots and spectral indices from four satellite sensors varying in spatial and spectral resolution on the 2003 Dry Lakes Fire in the Gila Wilderness, NM. Where spectrally feasible, burn severity was evaluated using the differenced Enhanced Vegetation Index (dEVI), differenced Normalised Difference Vegetation Index (dNDVI) and the differenced Normalised Burn Ratio (dNBR). Both the dEVI derived from Quickbird and the dNBR derived from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) showed similar or slightly improved correlations over the dNBR derived from Landsat Thematic Mapper data (R2 = 0.82, 0.84, and 0.78 respectively). The relatively coarse resolution MODIS-derived NDVI image was weakly correlated with ground data (R2 = 0.38). Our results suggest that moderately high-resolution satellite sensors like Quickbird and ASTER have potential for providing accurate information about burn severity. Future research should develop stronger links between higher-resolution satellite data and burn severity across a range of environments.

Mapping prescribed fire severity in south-east Australian eucalypt forests using modelling and satellite imagery: a case study

2017 ◽  
Vol 26 (6) ◽  
pp. 491 ◽  
Author(s):  
John Loschiavo ◽  
Brett Cirulis ◽  
Yingxin Zuo ◽  
Bronwyn A. Hradsky ◽  
Julian Di Stefano
Keyword(s):  
Satellite Imagery ◽  
Prescribed Fire ◽  
Vegetation Index ◽  
Fire Severity ◽  
Kappa Statistic ◽  
Fire Spread ◽  
Management Tool ◽  
Eucalypt Forest ◽  
Normalised Difference Vegetation Index ◽  
Eucalypt Forests

Accurate fire severity maps are fundamental to the management of flammable landscapes. Severity mapping methods have been developed and tested for wildfire, but need further refinement for prescribed fire. We evaluated the accuracy of two severity mapping methods for a low-intensity, patchy prescribed fire in a south-eastern Australian eucalypt forest: (1) the Normalised Difference Vegetation Index (NDVI) derived from RapidEye satellite imagery, and (2) PHOENIX RapidFire, a fire-spread simulation model. We used each method to generate a fire severity map (four-category: unburnt, low, moderate and severe), and then validated the maps against field-based data. We used error matrices and the Kappa statistic to assess mapping accuracy. Overall, the satellite-based map was more accurate (75%; Kappa±95% confidence interval 0.54±0.06) than the modelled map (67%; Kappa 0.40±0.06). Both methods overestimated the area of unburnt forest; however, the satellite-based map better represented moderately burnt areas. Satellite- and model-based methods both provide viable approaches for mapping prescribed fire severity, but refinements could further improve map accuracy. Appropriate severity mapping methods are essential given the increasing use of prescribed fire as a forest management tool.

The post-fire measurement of fire severity and intensity in the Christmas 2001 Sydney wildfires

2004 ◽  
Vol 13 (2) ◽  
pp. 227 ◽  
Author(s):  
Chris J. Chafer ◽  
Mark Noonan ◽  
Eloys Macnaught
Keyword(s):  
Vegetation Index ◽  
Fire Severity ◽  
Energy Levels ◽  
Satellite Image ◽  
Visual Assessment ◽  
Fuel Load ◽  
Fire Intensity ◽  
Simple Method ◽  
Affected Area ◽  
Normalised Difference Vegetation Index

Using pre- and post-fire satellite imagery from SPOT2, we examined the fire severity and intensity of the Christmas 2001 wildfires in the greater Sydney Basin, Australia. We computed a Normalised Difference Vegetation Index (NDVI) from the two satellite images captured before (November 2001) and after (January 2002) the wildfires, then subtracted the later from the former to produce a difference image (NDVIdiff) which was subsequently classified into six fire severity classes (unburnt, low, moderate, high, very high and extreme severity). We then tested the fire severity classification on 342 sample sites within the 225 000ha fire affected area using a qualitative visual assessment guide. We found that the NDVIdiff classification produced an accuracy of at least 88% (K hat = 0.86), with the greatest discrepancy being between the low and moderate classification. Knowledge of rate of spread over some of the affected area, coupled with a complete knowledge of fuel loads, was used to retrospectively model fire intensity, which in areas of extreme fire intensity, produced heat energy levels exceeding 70 000 kW m–1. Importantly, we found no positive effect of topography on fire severity, in fact finding an inverse relationship between slope and fire severity and no effect due to aspect. Further analysis showed that flat to moderate slopes less than 18° across all aspects suffered the greatest vegetal destruction, and there was no relationship between north-westerly aspects and fire severity. We also introduce a relatively simple method for estimating fuel load biomass using a combination of satellite image and rapid field assessment. We found 79% accuracy for this method based on 125 sample sites. It is postulated that this type of analysis can greatly improve our understanding of the spatial impact of fire, how natural areas within the fire ground were impacted, and how remote sensing and GIS technologies can be efficiently used in fire management planning and post-fire analysis.

Spectral analysis of charcoal on soils: implicationsfor wildland fire severity mapping methods

2010 ◽  
Vol 19 (7) ◽  
pp. 976 ◽  
Author(s):  
Alistair M. S. Smith ◽  
Jan U. H. Eitel ◽  
Andrew T. Hudak
Keyword(s):  
Spectral Analysis ◽  
Soil Type ◽  
Large Scale ◽  
Vegetation Index ◽  
Wildland Fire ◽  
Fire Severity ◽  
Mapping Method ◽  
Normalised Difference Vegetation Index ◽  
National Programs

Recent studies in the Western United States have supported climate scenarios that predict a higher occurrence of large and severe wildfires. Knowledge of the severity is important to infer long-term biogeochemical, ecological, and societal impacts, but understanding the sensitivity of any severity mapping method to variations in soil type and increasing charcoal (char) cover is essential before widespread adoption. Through repeated spectral analysis of increasing charcoal quantities on six representative soils, we found that addition of charcoal to each soil resulted in linear spectral mixing. We found that performance of the Normalised Burn Ratio was highly sensitive to soil type, whereas the Normalised Difference Vegetation Index was relatively insensitive. Our conclusions have potential implications for national programs that seek to monitor long-term trends in wildfire severity and underscore the need to collect accurate soils information when evaluating large-scale wildland fires.

Time series of high-resolution images enhances efforts to monitor post-fire condition and recovery, Waldo Canyon fire, Colorado, USA

2018 ◽  
Vol 27 (10) ◽  
pp. 699 ◽  
Author(s):  
Melanie K. Vanderhoof ◽  
Clifton Burt ◽  
Todd J. Hawbaker
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Vegetation Index ◽  
Burn Severity ◽  
Vegetation Recovery ◽  
Burned Area ◽  
Object Based ◽  
Fire Condition ◽  
Normalised Difference Vegetation Index ◽  
High Resolution Images

Interpretations of post-fire condition and rates of vegetation recovery can influence management priorities, actions and perception of latent risks from landslides and floods. In this study, we used the Waldo Canyon fire (2012, Colorado Springs, Colorado, USA) as a case study to explore how a time series (2011–2016) of high-resolution images can be used to delineate burn extent and severity, as well as quantify post-fire vegetation recovery. We applied an object-based approach to map burn severity and vegetation recovery using Worldview-2, Worldview-3 and QuickBird-2 imagery. The burned area was classified as 51% high, 20% moderate and 29% low burn-severity. Across the burn extent, the shrub cover class showed a rapid recovery, resprouting vigorously within 1 year, whereas 4 years post-fire, areas previously dominated by conifers were divided approximately equally between being classified as dominated by quaking aspen saplings with herbaceous species in the understorey or minimally recovered. Relative to using a pixel-based Normalised Difference Vegetation Index (NDVI), our object-based approach showed higher rates of revegetation. High-resolution imagery can provide an effective means to monitor post-fire site conditions and complement more prevalent efforts with moderate- and coarse-resolution sensors.

Evaluating the factors responsible for post-fire water quality response in forests of the western USA

2019 ◽  
Vol 28 (10) ◽  
pp. 769 ◽  
Author(s):  
Ashley J. Rust ◽  
Samuel Saxe ◽  
John McCray ◽  
Charles C. Rhoades ◽  
Terri S. Hogue
Keyword(s):  
Water Quality ◽  
Vegetation Index ◽  
Field Capacity ◽  
Phosphorus Loading ◽  
Burn Severity ◽  
Nitrogen And Phosphorus ◽  
Western Us ◽  
Normalised Difference Vegetation Index ◽  
Green Vegetation ◽  
Quality Response

Wildfires commonly increase nutrient, carbon, sediment and metal inputs to streams, yet the factors responsible for the type, magnitude and duration of water quality effects are poorly understood. Prior work by the current authors found increased nitrogen, phosphorus and cation exports were common the first 5 post-fire years from a synthesis of 159 wildfires across the western United States. In the current study, an analysis is undertaken to determine factors that best explain post-fire streamwater responses observed in those watersheds. Increased post-fire total nitrogen and phosphorus loading were proportional to the catchment extent of moderate and high burn severity. While post-fire dissolved metal concentrations were correlated with pre-fire soil organic matter. Total metal concentration increased where post-fire Normalised Difference Vegetation Index, a remote sensing indicator of live green vegetation, was low. When pre-fire soil field capacity exceeded 17%, there was a 750% median increase in total metals export to streams. Overall, the current analysis identified burn severity, post-fire vegetation cover and several soil properties as the key variables explaining extended post-fire water quality response across a broad range of conditions found in the western US.

Remote sensing of fire severity in the Blue Mountains: influence of vegetation type and inferring fire intensity

2006 ◽  
Vol 15 (2) ◽  
pp. 213 ◽  
Author(s):  
Kate A. Hammill ◽  
Ross A. Bradstock
Keyword(s):  
Vegetation Index ◽  
Forest Cover ◽  
Vegetation Type ◽  
Fire Severity ◽  
Image Resolution ◽  
Fire Intensity ◽  
Vegetation Types ◽  
Open Forest ◽  
Normalised Difference Vegetation Index ◽  
Severity Class

Fire intensity affects ecological and geophysical processes in fire-prone landscapes. We examined the potential for satellite imagery (Satellite Pour l’Observation de la Terre [SPOT2] and Landsat7) to detect and map fire severity patterns in a rugged landscape with variable vegetation near Sydney, Australia. A post-fire, vegetation-based indicator of fire intensity (burnt shrub branch tip diameters, representing the size of fuel consumed) was also used to explore whether fire severity patterns can be used to retrospectively infer patterns of fire intensity. Six severity classes (ranging from unburnt to complete crown consumption) were defined using aerial photograph interpretation and a field assessment across five vegetation types of varying height and complexity (sedge-swamp, heath, woodland, open forest, and tall forest). Using established Normalised Difference Vegetation Index (NDVI) differencing methodology, SPOT2 and Landsat7 imagery yielded similar broad-scale severity patterns across the study area. This was despite differences in image resolution (10 m and 30 m, respectively) and capture dates (2 months and 9 months apart, respectively). However, differences in the total areas mapped for some severity classes were found. In particular, there was reduced differentiation between unburnt and low-severity areas and between crown-scorched and crown-consumed areas when using the Landsat7 data. These differences were caused by fine-scale classification anomalies and were most likely associated with seasonal differences in vegetation condition (associated with time of image capture), post-fire movement of ash, resprouting of vegetation, and low sun elevation. Relationships between field severity class and NDVIdifference values revealed that vegetation type does influence the detection of fire severity using these types of satellite data: regression slopes were greater for woodland, forest, and tall forest data than for sedge-swamp and heath data. The effect of vegetation type on areas mapped in each fire severity class was examined but found to be minimal in the present study due to the uneven distribution of vegetation types in the study area (woodland and open forest cover 86% of the landscape). Field observations of burnt shrub branch tips, which were used as a surrogate for fire intensity, revealed that relationships between fire severity and fire intensity are confounded by vegetation type (mainly height). A method for inferring fire intensity from remotely sensed patterns of fire severity was proposed in which patterns of fire severity and vegetation type are combined.

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