Do you CBI what I see? The relationship between the Composite Burn Index and quantitative field measures of burn severity varies across gradients of forest structure

2022 ◽  
Author(s):  
Saba J. Saberi ◽  
Michelle C. Agne ◽  
Brian J. Harvey
Keyword(s):  
Forest Structure ◽  
Burn Severity ◽  
The Relationship

scholarly journals Assessing Wildfire Burn Severity and Its Relationship with Environmental Factors: A Case Study in Interior Alaska Boreal Forest

2021 ◽  
Vol 13 (10) ◽  
pp. 1966
Author(s):  
Christopher W Smith ◽  
Santosh K Panda ◽  
Uma S Bhatt ◽  
Franz J Meyer ◽  
Anushree Badola ◽  
...  
Keyword(s):  
Boreal Forest ◽  
Ground Truth ◽  
Burn Severity ◽  
Classification Methods ◽  
Spectral Indices ◽  
Ground Truth Data ◽  
Burn Scar ◽  
Interior Alaska ◽  
Remote Sensing Methods ◽  
The Relationship

In recent years, there have been rapid improvements in both remote sensing methods and satellite image availability that have the potential to massively improve burn severity assessments of the Alaskan boreal forest. In this study, we utilized recent pre- and post-fire Sentinel-2 satellite imagery of the 2019 Nugget Creek and Shovel Creek burn scars located in Interior Alaska to both assess burn severity across the burn scars and test the effectiveness of several remote sensing methods for generating accurate map products: Normalized Difference Vegetation Index (NDVI), Normalized Burn Ratio (NBR), and Random Forest (RF) and Support Vector Machine (SVM) supervised classification. We used 52 Composite Burn Index (CBI) plots from the Shovel Creek burn scar and 28 from the Nugget Creek burn scar for training classifiers and product validation. For the Shovel Creek burn scar, the RF and SVM machine learning (ML) classification methods outperformed the traditional spectral indices that use linear regression to separate burn severity classes (RF and SVM accuracy, 83.33%, versus NBR accuracy, 73.08%). However, for the Nugget Creek burn scar, the NDVI product (accuracy: 96%) outperformed the other indices and ML classifiers. In this study, we demonstrated that when sufficient ground truth data is available, the ML classifiers can be very effective for reliable mapping of burn severity in the Alaskan boreal forest. Since the performance of ML classifiers are dependent on the quantity of ground truth data, when sufficient ground truth data is available, the ML classification methods would be better at assessing burn severity, whereas with limited ground truth data the traditional spectral indices would be better suited. We also looked at the relationship between burn severity, fuel type, and topography (aspect and slope) and found that the relationship is site-dependent.

Utilising Airborne Multispectral Videography to Predict Habitat Complexity in Eucalypt Forests for Wildlife Management *Further information about this research can be found on the World Wide Web at http://www.ffp.csiro.au/nfm/mdq/

1997 ◽  
Vol 24 (6) ◽  
pp. 691 ◽  
Author(s):  
N. C. Coops ◽  
P. C. Catling
Keyword(s):  
Forest Structure ◽  
Habitat Complexity ◽  
Near Infrared ◽  
Ground Cover ◽  
Mammalian Fauna ◽  
Variable Response ◽  
Local Variance ◽  
Eucalypt Forests ◽  
Difficult Terrain ◽  
The Relationship

Airborne videographic remote sensing is a relatively recent technology thatcan provide inexpensive and high-spatial-resolution imagery for forestmanagement. This paper presents a methodology that allows videographic data tobe modelled to predict habitat complexity in eucalypt forests.Within the eucalypt forests of south-eastern New South Wales, plots werelocated on the imagery, and the local variance of the videography within eachplot was computed on the assumption that changes in local variance provided anindication of forest structure, and thus the habitat complexity of the site.The near- infrared (NIR) channel demonstrated the most variation, as thatchannel provided an indication of photosynthetic activity and, as a result,the variation between canopy, understorey, ground cover, soil and shadowprovided a highly variable response in the video imagery. Habitat-complexityscores were used to record forest structure, and the relationship between theNIR variance and field habitat-complexity scores was highly significant(P < 0·001)(r2 = 0·75;n = 29). From this relationship, maps of thehabitat-complexity scores were predicted from the videography at 2-m spatialresolution. The model was extrapolated across a 1 1 km subset of the videodata and field verification showed that the predicted scores correspondedclosely with the field scores.Studies have demonstrated the relationship between habitat-complexity scoresand the distribution and abundance of different mammalian fauna. This methodallows predictions of habitat-complexity scores to be spatially extrapolatedand used to stratify the landscape into regions for both the modelling offaunal habitat and to predict the composition, distribution and abundance ofsome faunal groups across the landscape. Ultimately, the management of foresthabitats for wildlife will depend on the availability of accurate maps of thediversity and extent of habitats over large areas and/or in difficult terrain.

scholarly journals Quantificação da Severidade das Queimadas e da Perda de Sequestro Florestal de Carbono em Unidades de Conservação do Distrito Federal (Measurement of Severity of Fires and Loss of Carbon Forest sink in the Conservation Units at Distrito Federal)

2016 ◽  
Vol 9 (1) ◽  
pp. 250
Author(s):  
Débora Teobaldo ◽  
Gustavo Macedo de Mello Baptista
Keyword(s):  
Carbon Sink ◽  
Severity Index ◽  
Burn Severity ◽  
Conservation Units ◽  
Differenced Normalized Burn Ratio ◽  
Before And After ◽  
Distrito Federal ◽  
Para Determinar ◽  
Normalized Burn Ratio ◽  
The Relationship

O objetivo desse trabalho foi avaliar o grau de severidade das queimadas e da perda do sequestro de carbono nas principais Unidades de Conservação do Distrito Federal nos anos de 2010 e 2011. Para determinar o grau de severidade utilizou-se índices espectrais antes e depois da queimada, como o índice de queimada por razão normalizada (NBR) e o índice relativo diferenciado de queimada por razão normalizada (RdNBR). O sequestro de carbono perdido pela queimada foi comparado antes, depois da queimada e na rebrota pelo índice espectral CO2flux. A relação entre a severidade e o sequestro de carbono também foi determinada por meio das imagens de pré-fogo, pós-fogo e da rebrota e a comparação temporal do CO2flux. As regressões obtidas para o ano de 2010 foram bastante de acordo com o esperado, com baixa relação antes da queimada, alta após, e menor na rebrota. Já para 2011, como ocorreram queimadas ao longo de todo o período, não foi possível verificar relações favoráveis.    A B S T R A C T The aim of this study was to assess the burn severity and carbon sink in the Conservation Units at Distrito Federal in the 2010 and 2011. For the burn severity index was used to quantify biomass before and after burning, such as a Normalized Burn Ratio - NBR and relative differenced Normalized Burn Ratio - RdNBR indices. Carbon sink lost by the burning was compared before and after fire by regrowth CO2flux spectral index. The relationship between the burn severity and carbon sink were also made by means the pre, post-fire and regrowth images, and temporal comparison of CO2flux. The regressions obtained for the 2010 were largely in agreement with expectations, with a low pre-fire, after high and low in regrowth. Already in 2011, as fires occurred throughout the period, it was not possible to verify favorable relationships. Keywords: Biomass, burn severity, RdNBR, carbon sink, CO2flux.  

scholarly journals Assessing the Relationship between Forest Structure and Fire Severity on the North Rim of the Grand Canyon

Fire ◽  
2019 ◽  
Vol 2 (1) ◽  
pp. 10 ◽  
Author(s):  
Valentijn Hoff ◽  
Eric Rowell ◽  
Casey Teske ◽  
LLoyd Queen ◽  
Tim Wallace
Keyword(s):  
Surface Roughness ◽  
Forest Structure ◽  
Fire Severity ◽  
Grand Canyon ◽  
Canopy Cover ◽  
Management Decisions ◽  
Component Structure ◽  
The North ◽  
The Relationship ◽  
North Rim

While operational fire severity products inform fire management decisions in Grand Canyon National Park (GRCA), managers have expressed the need for better quantification of the consequences of severity, specifically forest structure. In this study we computed metrics related to the forest structure from airborne laser scanning (ALS) data and investigated the influence that fires that burned in the decade previous had on forest structure on the North Rim of the Grand Canyon in Arizona. We found that fire severity best explains the occurrence of structure classes that include canopy cover, vertical fuel distribution, and surface roughness. In general we found that high fire severity resulted in structure types that exhibit lower canopy cover and higher surface roughness. Areas that burned more frequently with lower fire severity in general had a more closed canopy and a lower surface roughness, with less brush and less conifer regeneration. In a random forests modeling exercise to examine the relationship between severity and structure we found mean canopy height to be a powerful explanatory variable, but still proved less informative than the three-component structure classification. We show that fire severity not only impacts forest structure but also brings heterogeneity to vegetation types along the elevation gradient on the Kaibab plateau. This work provides managers with a unique dataset, usable in conjunction with vegetation, fuels and fire history data, to support management decisions at GRCA.

Evaluating the ability of the differenced Normalized Burn Ratio (dNBR) to predict ecologically significant burn severity in Alaskan boreal forests

2008 ◽  
Vol 17 (4) ◽  
pp. 490 ◽  
Author(s):  
Karen A. Murphy ◽  
Joel H. Reynolds ◽  
John M. Koltun
Keyword(s):  
Boreal Forest ◽  
Boreal Forests ◽  
Burn Severity ◽  
Fire Season ◽  
Vegetation Composition ◽  
Management Objectives ◽  
Differenced Normalized Burn Ratio ◽  
Normalized Burn Ratio ◽  
Processing Errors ◽  
The Relationship

During the 2004 fire season ~6.6 million acres (~2.7 million ha) burned across Alaska. Nearly 2 million of these were on National Wildlife Refuge System lands inaccessible from the state’s limited road system. Many fires burned through September, driven by unusually warm and dry temperatures throughout the summer. Using several fires from this season, we assessed the national burn severity methodology’s performance on refuge lands. Six fires, spanning 814 489 acres (329 613 ha), were sampled on five boreal forest refuges. In total, 347 sites were sampled for vegetation composition and ground-based burn severity estimates following the national protocols. The relationship between the differenced Normalized Burn Ratio (dNBR) and composite burn index (CBI) was unexpectedly weak (R2adjusted, 0.11–0.64). The weak relationship was not a result of data or image processing errors, nor of any biotic or abiotic confounding variable. The inconsistent results, and dNBR’s limited ability to discern the ecologically significant differences within moderate and high severity burn sites, indicate that the current methodology does not satisfy key Alaskan boreal forest management objectives.

scholarly journals Exploring the Relationship between Burn Severity Field Data and Very High Resolution GeoEye Images: The Case of the 2011 Evros Wildfire in Greece

2016 ◽  
Vol 8 (7) ◽  
pp. 566 ◽  
Author(s):  
Eleni Dragozi ◽  
Ioannis Gitas ◽  
Sofia Bajocco ◽  
Dimitris Stavrakoudis
Keyword(s):  
High Resolution ◽  
Field Data ◽  
Burn Severity ◽  
The Relationship ◽  
Very High

scholarly journals Structural, production and dynamic characteristics of the strict forest reserve “Racanska sljivovica“ on mt. Tara

2011 ◽  
pp. 93-114 ◽  
Author(s):  
Damjan Pantic ◽  
Milan Medarevic ◽  
Stanisa Bankovic ◽  
Snezana Obradovic ◽  
Biljana Sljukic ◽  
...  
Keyword(s):  
Forest Structure ◽  
Statistical Processing ◽  
Silver Fir ◽  
Forest Reserve ◽  
Stand Volume ◽  
High Productivity ◽  
Growing Stock ◽  
Dead Trees ◽  
Survival And Development ◽  
The Relationship

Mixed forests of broadleaves and conifers, thanks to their high productivity and high biodiversity, are the most valuable part of the growing stock in Serbia. The aim of this research was to analyze the mixed old-growth forests of fir, spruce and beech in the reserve ?Racanska Sljivovica? so as to define the laws which could be applied in the future forest management on Mt. Tara. The research was based on the data of six periodic complete inventories followed by standard dendrometric and statistical processing. Forest structure was similar to the typical selection structure. The recruitment dynamics (except beech) was relatively favourable, with the ratio to dead trees amounting to 1.72. The number of trees and the volume increased constantly, attaining 422.2 trees?ha-1, i.e. 800.3 m3?ha-1, and the volume increment was above 12 m3?ha-1, despite a slight drop. Silver fir was the protagonist of the selection structure and productivity. It is necessary to stimulate the survival and development of beech at the concrete site, to examine the balanced number of trees and volume, and to investigate the relationship between the number of recruited trees and the stand volume.

An evaluation of remotely sensed indices for quantifying burn severity in arid ecoregions

2019 ◽  
Vol 28 (12) ◽  
pp. 951
Author(s):  
Rob Klinger ◽  
Randy McKinley ◽  
Matt Brooks
Keyword(s):  
Remote Sensing ◽  
Mojave Desert ◽  
Remotely Sensed ◽  
High Elevation ◽  
Burn Severity ◽  
Elevation Gradients ◽  
Desert Regions ◽  
Woody Cover ◽  
The Difference ◽  
The Relationship

It is sometimes assumed the sparse and low statured vegetation in arid systems would limit the effectiveness of two remote-sensing derived indices of burn severity: the difference Normalised Burn Ratio (dNBR) and relativised difference Normalised Burn Ratio (RdNBR). We compared the relationship that dNBR, RdNBR and a ground-based index of burn severity (the Composite Burn Index, CBI) had with woody cover and woody density 1 year after burning in five fires that occurred in the Mojave Desert during 2005. Data were collected within 437 plots spanning geographic and elevation gradients representative of vegetation associations in low- (&lt;1200m), mid- (1200 to 1700m) and high-elevation (&gt;1700m) zones. Statistically, dNBR and RdNBR were both effective measures of severity in all three elevation zones; woody cover and density had steep exponential declines as the values of each remote-sensing index increased. We found though that dNBR was more ecologically interpretable than RdNBR and will likely be of most relevance in the Mojave Desert. It will be necessary though to test these, as well as other remote-sensing burn-severity indices, across more desert regions before inferences can be made of the generality of the patterns we observed.

Remote sensing of burn severity: experience from western Canada boreal fires

2008 ◽  
Vol 17 (4) ◽  
pp. 476 ◽  
Author(s):  
R. J. Hall ◽  
J. T. Freeburn ◽  
W. J. de Groot ◽  
J. M. Pritchard ◽  
T. J. Lynham ◽  
...  
Keyword(s):  
Burn Severity ◽  
Fuel Type ◽  
New Approach ◽  
Burned Areas ◽  
Field Assessment ◽  
Study Results ◽  
Mapping Process ◽  
Single Dataset ◽  
Normalized Burn Ratio ◽  
The Relationship

The severity of a burn for post-fire ecological effects has been assessed with the composite burn index (CBI) and the differenced Normalized Burn Ratio (dNBR). This study assessed the relationship between these two variables across recently burned areas located in the western Canadian boreal, a region not extensively evaluated in previous studies. Of particular interest was to evaluate the nature of the CBI–dNBR relationship from the perspectives of modelling, the influence of fire behaviour prediction (FBP) fuel type, and how field observations could be incorporated into the burn severity mapping process. A non-linear model form best represented the relationship between these variables for the fires evaluated, and a similar statistical performance was achieved when data from all fires were pooled into a single dataset. Results from this study suggest the potential to develop a single model for application over the western region of the boreal, but further evaluation is necessary. This evaluation could include stratification by FBP fuel type due to study results that document its apparent influence on dNBR values. A new approach for burn severity mapping was introduced by defining severity thresholds through field assessment of CBI, and from which development of new models could be incorporated directly into the mapping process.

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