Use of multitemporal ERS-2 SAR images for identification of burned scars in south-east Asian tropical rainforest

Siegert, Florian; Ruecker, Gernot

doi:10.1080/014311600210632

Cited by 58 publications

(34 citation statements)

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“…Moreover, research on forest fires in boreal forests has shown that the backscatter intensity from burned scars is stronger than that from unburned areas due to changes in moisture content [11,12,[15][16][17]. Siegert and Ruecker [18] and Huang and Siegert [19] made similar observations in a tropical rain forest environment, but found that fires caused a decrease in backscatter under dry weather conditions whereas under wet conditions burned areas could not be discriminated from unburned areas.…”

Section: Introductionsupporting

confidence: 58%

“…Specifically, very useful information could be extracted from optical data on the exact location of burned areas as well as from SAR data on areas of specific land-cover types that have been severely affected. Finally, the soil moisture parameter cannot be neglected as a cause of observed misclassifications: active microwave backscatter was found to be sensitive to variations in soil moisture in fire-related studies [14,18,35,54]. In particular for L-band, Ulaby et al [55] showed that backscatter of bare-soil fields was strongly correlated to soil moisture, whereas Kasischke et al [17] demonstrated that monitoring regrowth of low-biomass forests, requires to account for the soil moisture influence on L-band microwave backscatter.…”

Section: Classification Resultsmentioning

confidence: 99%

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Evaluation of ALOS PALSAR Imagery for Burned Area Mapping in Greece Using Object-Based Classification

et al. 2013

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Abstract:In this work, the potential of Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) imagery to map burned areas was evaluated in two study areas in Greece. For this purpose, we developed an object-based classification scheme to map the fire-disturbed areas using the PALSAR imagery acquired before and shortly after fire events. The advantage of employing an object-based approach was not only the use of the temporal variation of the backscatter coefficient, but also the incorporation in the classification of topological features, such as neighbor objects, and class related features, such as objects classified as burned. The classification scheme resulted in mapping the burned areas with satisfactory results: 0.71 and 0.82 probabilities of detection for the two study areas. Our investigation revealed that the pre-fire vegetation conditions and fire severity should be taken in consideration when mapping burned areas using PALSAR in Mediterranean regions. Overall, findings suggest that the developed scheme could be applied for rapid burned area assessment, especially to areas where cloud cover and fire smoke inhibit accurate mapping of burned areas when optical data are used.

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Section: Introductionsupporting

confidence: 58%

Section: Classification Resultsmentioning

confidence: 99%

Evaluation of ALOS PALSAR Imagery for Burned Area Mapping in Greece Using Object-Based Classification

et al. 2013

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“…Synthetic Aperture Radar (SAR) sensors can be used to overcome this problem because of their ability to penetrate clouds and haze [8,19]. High spatial resolution SAR data have been used together with coarse optical data in a few studies [19,20]. However, the use of SAR data in an operational way has been limited by the availability of time series of SAR acquisitions and the pre-processing requirements [21].…”

Section: Introductionmentioning

confidence: 99%

“…In tropical evergreen forests, an important challenge is the persistent cloud cover, requiring frequent acquisitions of optical data. Synthetic Aperture Radar (SAR) sensors can be used to overcome this problem because of their ability to penetrate clouds and haze [8,19]. High spatial resolution SAR data have been used together with coarse optical data in a few studies [19,20].…”

Section: Introductionmentioning

confidence: 99%

The Potential of Sentinel Satellites for Burnt Area Mapping and Monitoring in the Congo Basin Forests

et al. 2016

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Abstract:In this study, the recently launched Sentinel-2 (S2) optical satellite and the active radar Sentinel-1 (S1) satellite supported by active fire data from the MODIS sensor were used to detect and monitor forest fires in the Congo Basin. In the context of a very strong El Niño event, an unprecedented outbreak of fires was observed during the first months of 2016 in open forests formations in the north of the Republic of Congo. The anomalies of the recent fires and meteorological situation compared to historical data show the severity of the drought. Burnt areas mapped by the S1 SAR and S2 Multi Spectral Instrument (MSI) sensors highlight that the fires occurred mainly in Marantaceae forests, characterized by open tree canopy cover and an extensive tall herbaceous layer. The maps show that the origin of the fires correlates with accessibility to the forest, suggesting an anthropogenic origin. The combined use of the two independent and fundamentally different satellite systems of S2 and S1 captured an extent of 36,000 ha of burnt areas, with each sensor compensating for the weakness (cloud perturbations for S2, and sensitivity to ground moisture for S1) of the other.

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“…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%

Use of Remote Sensing in Wildfire Management

Leblon¹,

Bourgeau‐Chavez²,

San-Miguel-Ayanz³

2012

Sustainable Development - Authoritative and Leading Edge Content for Environmental Management

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Use of multitemporal ERS-2 SAR images for identification of burned scars in south-east Asian tropical rainforest

Cited by 58 publications

References 0 publications

Evaluation of ALOS PALSAR Imagery for Burned Area Mapping in Greece Using Object-Based Classification

Evaluation of ALOS PALSAR Imagery for Burned Area Mapping in Greece Using Object-Based Classification

The Potential of Sentinel Satellites for Burnt Area Mapping and Monitoring in the Congo Basin Forests

Use of Remote Sensing in Wildfire Management

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