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.

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.

Temporal and spatial heterogeneity of drought impact on vegetation growth on the Inner Mongolian Plateau

2018 ◽  
Vol 40 (2) ◽  
pp. 113 ◽  
Author(s):  
Miao Bailing ◽  
Li Zhiyong ◽  
Liang Cunzhu ◽  
Wang Lixin ◽  
Jia Chengzhen ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Severity Index ◽  
Drought Severity ◽  
Summer Drought ◽  
Desert Steppe ◽  
Vegetation Types ◽  
Mongolian Plateau ◽  
Typical Steppe ◽  
Recent Climate ◽  
Normalised Difference Vegetation Index

Drought frequency and intensity have increased in recent decades, with consequences for the structure and function of ecosystems of the Inner Mongolian Plateau. In this study, the Palmer drought severity index (PDSI) was chosen to assess the extent and severity of drought between 1982 and 2011. The normalised difference vegetation index (NDVI) was used to analyse the responses of five different vegetation types (forest, meadow steppe, typical steppe, desert steppe and desert) to drought. Our results show that during the last 30 years, the frequency and intensity of droughts have increased significantly, especially in summer and autumn. The greatest decline in NDVI in response to drought was observed in typical steppe and desert steppe vegetation types. Compared with other seasons, maximum decline in NDVI was observed in summer. In addition, we found that NDVI in the five vegetation types showed a lag time of 1–2 months from drought in the spring and summer. Ancillary soil moisture conditions influenced the drought response, with desert steppe showing a stronger lag effect to spring and summer drought than the other vegetation types. Our results show that drought explains a high proportion of changes in NDVI, and suggest that recent climate change has been an important factor affecting vegetation productivity in the area.

scholarly journals Avian Response to Wildfire Severity in a Northern Boreal Region

Forests ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1330
Author(s):  
Michelle Knaggs ◽  
Samuel Haché ◽  
Scott E. Nielsen ◽  
Rhiannon F. Pankratz ◽  
Erin Bayne
Keyword(s):  
Climate Change ◽  
Species Richness ◽  
Functional Diversity ◽  
Vegetation Type ◽  
Fire Severity ◽  
Natural Disturbance ◽  
Burn Severity ◽  
Vegetation Types ◽  
Generalist Species ◽  
High Severity

Research Highlights: The effects of fire on birds in the most northern parts of the boreal forest are understudied. We found distinct differences in bird communities with increasing fire severity in two vegetation types with naturally different burn severity. The highest severity burns tended to have communities dominated by generalist species, regardless of the original vegetation type. Background and Objectives: Wildfire is the primary natural disturbance in the boreal ecosystems of northwestern Canada. Increased wildfire frequency, extent, and severity are expected with climate change in this region. In particular, the proportion of burns that are high severity and the area of peatlands burned are increasing, and how this influences birds is poorly understood. Materials and Methods: We quantified the effects of burn severity (low, moderate, and high severity) in uplands and peatlands on occupancy, density, richness, community composition, and functional diversity using point counts (n = 1158) from the first two years post-fire for two large fires in the Northwest Territories, Canada. Results: Burn severity had a significant effect on the occupancy and density of 86% of our focal species (n = 20). Responses to burn severity depended on vegetation type for four of the 18 species using occupancy and seven of the 18 using density, but were typically in a similar direction. Species richness and functional diversity were lower in areas of high severity burns than unburned areas and low severity burns in peatlands. Richness was not related to severity in uplands, but functional diversity was. Peatlands had higher species richness than uplands in all burn severities, but as burn severity increased the upland and peatland communities became more similar. Conclusions: Our results suggest that high severity burns in both vegetation types support five generalist species and two fire specialists that may benefit from alterations in vegetation structure as a result of climate induced changes to fire regimes. However, eight species avoided burns, particularly birds preferring peatlands, and are likely to be more susceptible to fire-driven changes to their habitat caused by climate change. Understanding the long-term risks to these species from climate change requires additional efforts that link fire to bird populations.

scholarly journals Latrine site selection of raccoon dogs in a hilly area in north-eastern Japan

2021 ◽  
pp. 79-85
Author(s):  
Kazuma Watanabe ◽  
Nami Kumagai ◽  
Masayuki U. Saito
Keyword(s):  
Vegetation Index ◽  
Vegetation Type ◽  
Slope Angle ◽  
Normalised Difference Vegetation Index ◽  
North Eastern ◽  
Position Index ◽  
Latrine Site ◽  
The Relationship ◽  
Eastern Japan ◽  
Raccoon Dogs

We evaluated the environment types of raccoon dog latrine sites in the hilly areas of north-eastern Japan. We conducted a route census in the spring and autumn of 2020 to record the latrine sites and analysed the relationship between the presence or absence of latrine sites and environmental factors, namely, topographic position index (TPI), slope, normalised difference vegetation index (NDVI), and vegetation type for each season. To investigate the space use of raccoon dogs, we also conducted camera trapping from July to November 2020 along the spring survey route. We analysed the relationship between the occurrence frequency of raccoon dogs and TPI, slope angle, NDVI, and vegetation type. The analysis showed that latrine sites tended to be located at sites with a high TPI (topography closer to the ridge) in both seasons. However, the occurrence of latrine sites in broadleaf forests was significantly higher in autumn. The frequency of raccoon dogs, based on camera-trap footage, was significantly higher at sites with gentle slopes; although the environment and space used by raccoon dogs at these sites differed. Raccoon dogs possibly select visually and olfactorily conspicuous sites on the ridge as latrine sites to facilitate odour dispersal. In addition, broadleaf forests in autumn are considered important feeding grounds for raccoon dogs, suggesting that the latrine sites were formed near foraging sites.

scholarly journals Predicting Soil Respiration from Plant Productivity (NDVI) in a Sub-Arctic Tundra Ecosystem

2021 ◽  
Vol 13 (13) ◽  
pp. 2571
Author(s):  
Olivia Azevedo ◽  
Thomas C. Parker ◽  
Matthias B. Siewert ◽  
Jens-Arne Subke
Keyword(s):  
Soil Respiration ◽  
Vegetation Index ◽  
Vegetation Type ◽  
Net Ecosystem Exchange ◽  
Plant Productivity ◽  
Ecosystem Monitoring ◽  
Vegetation Communities ◽  
Direct Measurements ◽  
Tundra Ecosystem ◽  
Normalised Difference Vegetation Index

Soils represent the largest store of carbon in the biosphere with soils at high latitudes containing twice as much carbon (C) than the atmosphere. High latitude tundra vegetation communities show increases in the relative abundance and cover of deciduous shrubs which may influence net ecosystem exchange of CO2 from this C-rich ecosystem. Monitoring soil respiration (Rs) as a crucial component of the ecosystem carbon balance at regional scales is difficult given the remoteness of these ecosystems and the intensiveness of measurements that is required. Here we use direct measurements of Rs from contrasting tundra plant communities combined with direct measurements of aboveground plant productivity via Normalised Difference Vegetation Index (NDVI) to predict soil respiration across four key vegetation communities in a tundra ecosystem. Soil respiration exhibited a nonlinear relationship with NDVI (y = 0.202e3.508 x, p < 0.001). Our results further suggest that NDVI and soil temperature can help predict Rs if vegetation type is taken into consideration. We observed, however, that NDVI is not a relevant explanatory variable in the estimation of SOC in a single-study analysis.

scholarly journals Identification and classification of cloud computing-based vegetation index values on several lands used in Bogor Regency, Indonesia

2021 ◽  
Vol 918 (1) ◽  
pp. 012011
Author(s):  
H S Aprilianti ◽  
R A Ari ◽  
A Ranti ◽  
M F Aslam
Keyword(s):  
Land Use ◽  
Cloud Computing ◽  
Oil Palm ◽  
Vegetation Index ◽  
Vegetation Type ◽  
Vegetation Indices ◽  
Threshold Value ◽  
Vegetation Types ◽  
Computing Platform ◽  
Use Studies

Abstract Understanding the threshold value classification from various vegetation types may help distinguish spectral reflectance differences in detailed land use studies. However, conducting all of the processes requires relatively large resources regarding manual computation, which could be surpassed by cloud computing. Unfortunately, in Bogor Regency, there is still a lack of research that studies the threshold value of various vegetation types related to forestry and plantation sectors. Land use categories were classified, and threshold values were determined, especially for selected vegetation types including teak, oil palm, rubber, pine, bamboo, and tea based on several vegetation indices in Bogor Regency using the Cloud-Computing platform. The data source was retrieved from 10-meters Sentinel-2 Satellite median imagery of January 2019 - June 2021. Land use maps were generated using Random Forest Algorithm from composite images. Meanwhile, the threshold value of each vegetation type was calculated from the average and standard deviation of NDVI, SAVI, EVI, ARVI, SLAVI, and GNDVI index. The result of the study showed forest and plantation area covers about 158,168.13 ha or 48.92 % of the study area. NDVI was found suitable to identify teak, SLAVI for rubber and pine, EVI for bamboo and tea, and GNDVI for oil palm vegetation.

A novel protocol for assessment of aboveground biomass in rangeland environments

2015 ◽  
Vol 37 (2) ◽  
pp. 157 ◽  
Author(s):  
Charity Mundava ◽  
Antonius G. T. Schut ◽  
Petra Helmholz ◽  
Richard Stovold ◽  
Graham Donald ◽  
...  
Keyword(s):  
Aboveground Biomass ◽  
Vegetation Index ◽  
Growth Models ◽  
Vegetation Type ◽  
Perennial Grasses ◽  
Heterogeneous Environments ◽  
Growing Seasons ◽  
Normalised Difference Vegetation Index ◽  
Bunch Grass ◽  
Non Destructive

Current methods to measure aboveground biomass (AGB) do not deliver adequate results in relation to the extent and spatial variability that characterise rangelands. An optimised protocol for the assessment of AGB is presented that enables calibration and validation of remote-sensing imagery or plant growth models at suitable scales. The protocol combines a limited number of destructive samples with non-destructive measurements including normalised difference vegetation index (NDVI), canopy height and visual scores of AGB. A total of 19 sites were sampled four times during two growing seasons. Fresh and dry matter weights of dead and green components of AGB were recorded. Similarity of responses allowed grouping into Open plains sites dominated by annual grasses, Bunch grass sites dominated by perennial grasses and Spinifex (Triodia spp.) sites. Relationships between non-destructive measurements and AGB were evaluated with a simple linear regression per vegetation type. Multiple regression models were first used to identify outliers and then cross-validated using a ‘Leave-One-Out’ and ‘Leave-Site-Out’ (LSO) approach on datasets including and excluding the identified outliers. Combining all non-destructive measurements into one single regression model per vegetation type provided strong relationships for all seasons for total and green AGB (adjusted R2 values of 0.65–0.90) for datasets excluding outliers. The model provided accurate assessments of total AGB in heterogeneous environments for Bunch grass and Spinifex sites (LSO-Q2 values of 0.70–0.88), whereas assessment of green AGB was accurate for all vegetation types (LSO-Q2 values of 0.62–0.84). The protocol described can be applied at a range of scales while considerably reducing sampling time.

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.

scholarly journals Habitat Mosaics of Sand Steppes and Forest-Steppes in the Ipoly Valley in Hungary

Forests ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 135
Author(s):  
Ildikó Járdi ◽  
Dénes Saláta ◽  
Eszter S.-Falusi ◽  
Ferenc Stilling ◽  
Gergely Pápay ◽  
...  
Keyword(s):  
Urban Areas ◽  
Vegetation Index ◽  
Vegetation Type ◽  
Calcareous Soils ◽  
Steppe Zone ◽  
Forest Steppe ◽  
Vegetation Types ◽  
Natural Habitats ◽  
Grassland Species ◽  
Vegetation Patches

The present study focuses on the mosaic-like occurrences of patches of steppes and fore-steppes in the Pannonian forest-steppe zone. We present the current vegetation, which is maintained including by human landscape use, i.e., grazing and mowing. The area is complex and for this reason it shows the changes in the landscape and differences in the vegetation more diversely. We wanted to answer the questions: Do sand steppes and forest-steppes occur in the Ipoly Valley and what location? What kind of environmental effects influence the species composition on these areas? Besides classic habitat mapping, are the satellite data from Sentinel-2A useful for distinction of different areas? Comparison of vegetation patches was based on the Hungarian habitat classification system (ÁNÉR). Based on satellite images, quantile data of the Normalized Vegetation Index (NDVI) were used for comparison. Based on the result, water bodies and urban areas are clearly distinguishable from other natural habitats. In some natural vegetation types, we found visible differences, such as grasslands, i.e., sandy steppe meadows and shrubby, woody vegetation patches. Sandy vegetation mainly grows on calcareous soils, which appear to be mosaic-like in the landscape on raised alluvials on the patches of past islands and reefs. From open to continuous closed grasslands, these vegetation types mainly grow on lithosoils. New occurrences of Pannonian sandy vegetation were discovered. In the sandy areas along the Ipoly Valley, open sandy grasslands were found, which is where the northernmost known occurrences of this vegetation type are. Besides common sandy grassland species, the vegetation also contains herbs that are typical in loess-grasslands and it is maintained by grazing, similarly to the eastern Pannonian area. This type of grazing can be useful when maintaining the mosaic-like appearance and diversity of the vegetation.

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.

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