The effect of savanna fires on SAR backscatter in northern Australia

Menges, CH; Bartolo, Renée E.; Bell, Darren; Hill, Gordon A.

doi:10.1080/01431160410001712945

Cited by 43 publications

(31 citation statements)

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“…Furthermore, spectral overlaps between burnt areas and shadows, water bodies and unburnt canopies as well as vegetation regrowth in previously burnt areas can cause difficulties in discriminating between burnt and unburnt areas [5]. Therefore, burnt area mapping algorithms are generally focused on areas with uniform topography and vegetation characteristics [5].…”

Section: The Potential For Sar Data Analysis For Burn-scar Detectionmentioning

confidence: 99%

“…In particular, the removal of leaves and branches of vegetation due to fire would lead to a change in SAR backscatter [19]. Studies on the use of SAR data for burnt area detection generally rely on the analysis of SAR backscatter at various polarisations and its variation between burnt and unburnt areas [1,2,5] using single-pass [1,5] or multi-temporal analysis [3] approaches. In general, SAR backscatter was found to be affected by many factors including moisture conditions, surface roughness and biomass [4].…”

Section: The Potential For Sar Data Analysis For Burn-scar Detectionmentioning

confidence: 99%

“…Although the maturity of algorithms to derive burnt area from multispectral data has reached a level where it is operationally used in various fire management systems [10], data acquisition is frequently affected by the presence of cloud cover or smoke plumes in actively burning areas [3,5]. Furthermore, spectral overlaps between burnt areas and shadows, water bodies and unburnt canopies as well as vegetation regrowth in previously burnt areas can cause difficulties in discriminating between burnt and unburnt areas [5]. Therefore, burnt area mapping algorithms are generally focused on areas with uniform topography and vegetation characteristics [5].…”

Section: The Potential For Sar Data Analysis For Burn-scar Detectionmentioning

confidence: 99%

“…The effects of wildfires are severe and can include damage to infrastructure and the environment [1,2] as well as contributing to land degradation and affecting global warming due to an increase in CO 2 emissions [3][4][5][6][7][8]. Although fires can be disastrous events with significant impacts on infrastructure and the environment, in many ecosystems, periodic fires are vital for ecosystem functioning and keeping vegetation species in a healthy condition.…”

Section: Introductionmentioning

confidence: 99%

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A Simple Normalized Difference Approach to Burnt Area Mapping Using Multi-Polarisation C-Band SAR

Engelbrecht

Theron

Vhengani³

et al. 2017

Remote Sensing

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Abstract:In fire-prone ecosystems, periodic fires are vital for ecosystem functioning. Fire managers seek to promote the optimal fire regime by managing fire season and frequency requiring detailed information on the extent and date of previous burns. This paper investigates a Normalised Difference α-Angle (NDαI) approach to burn-scar mapping using C-band data. Polarimetric decompositions are used to derive α-angles from pre-burn and post-burn scenes and NDαI is calculated to identify decreases in vegetation between the scenes. The technique was tested in an area affected by a wildfire in January 2016 in the Western Cape, South Africa. The quad-pol H-A-α decomposition was applied to RADARSAT-2 data and the dual-pol H-α decomposition was applied to Sentinel-1A data. The NDαI results were compared to a burn scar extracted from Sentinel-2A data. High overall accuracies of 97.4% (Kappa = 0.72) and 94.8% (Kappa = 0.57) were obtained for RADARSAT-2 and Sentinel-1A, respectively. However, large omission errors were found and correlated strongly with areas of high local incidence angle for both datasets. The combined use of data from different orbits will likely reduce these errors. Furthermore, commission errors were observed, most notably on Sentinel-1A results. These errors may be due to the inability of the dual-pol H-α decomposition to effectively distinguish between scattering mechanisms. Despite these errors, the results revealed that burnt areas could be extracted and were in good agreement with the results from Sentinel-2A. Therefore, the approach can be considered in areas where persistent cloud cover or smoke prevents the extraction of burnt area information using conventional multispectral approaches.

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Section: The Potential For Sar Data Analysis For Burn-scar Detectionmentioning

confidence: 99%

Section: The Potential For Sar Data Analysis For Burn-scar Detectionmentioning

confidence: 99%

Section: The Potential For Sar Data Analysis For Burn-scar Detectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Simple Normalized Difference Approach to Burnt Area Mapping Using Multi-Polarisation C-Band SAR

Engelbrecht

Theron

Vhengani³

et al. 2017

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Most of the studies were carried out in boreal forest (Bourgeau-Chavez et al 1997, Kasische et al, 1994, French et al 1999, Siegert and Ruecker, 2000, Menges et al, 2004, but some examples for the Mediterranean area exist San-Miguel-Ayanz, 2004, Gimeno et al 2005). Rather than the changes in vegetation condition and structure, the detection of burnt areas from SAR is based on the changes on moisture content in the burnt surface with respect to the unburned areas.…”

Section: Burnt Area Mappingmentioning

confidence: 99%