Use of multitemporal SAR data for monitoring vegetation recovery of Mediterranean burned areas

Minchella, A.; Frate, Fabio Del; Capogna, Francesca; Anselmi, Silvia; Manes, Fausto

doi:10.1016/j.rse.2008.11.004

Cited by 51 publications

(29 citation statements)

References 14 publications

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“…Therefore, it can be used for landscape representation and analysis of vegetation [13,14], which are the first steps toward ES mapping and assessment [15]. Lately, more sophisticated satellite sensors have become available, providing opportunities for enhancing the accuracy of mapping and assessment of ecosystem goods and services [16].…”

Section: Introductionmentioning

confidence: 99%

Mapping and Assessment of PM10 and O3 Removal by Woody Vegetation at Urban and Regional Level

et al. 2017

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This study is the follow up of the URBAN-MAES pilot implemented in the framework of the EnRoute project. The study aims at mapping and assessing the process of particulate matter (PM 10 ) and tropospheric ozone (O 3 ) removal by various forest and shrub ecosystems. Different policy levels and environmental contexts were considered, namely the Metropolitan city of Rome and, at a wider level, the Latium region. The approach involves characterization of the main land cover and ecosystems using Sentinel-2 images, enabling a detailed assessment of Ecosystem Service (ES), and monetary valuation based on externality values. The results showed spatial variations in the pattern of PM 10 and O 3 removal inside the Municipality and in the more rural Latium hinterland, reflecting the spatial dynamics of the two pollutants. Evergreen species displayed higher PM 10 removal efficiency, whereas deciduous species showed higher O 3 absorption in both rural and urban areas. The overall pollution removal accounted for 5123 and 19,074 Mg of PM 10 and O 3 , respectively, with a relative monetary benefit of 161 and 149 Million Euro for PM 10 and O 3 , respectively. Our results provide spatially explicit evidence that may assist policymakers in land-oriented decisions towards improving Green Infrastructure and maximizing ES provision at different governance levels.

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Section: Introductionmentioning

confidence: 99%

Mapping and Assessment of PM10 and O3 Removal by Woody Vegetation at Urban and Regional Level

et al. 2017

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“…Furthermore, De Luís et al (2001) have observed that, in Eastern Spain, changes in the precipitation regime, such as decreases in rainfall volume and increases in rainfall concentration seem to be occurring in dry, inland areas, where most forests are located. Remote sensing has revealed to be a powerful tool to study the climatic influence on vegetation dynamics (Vicente-Serrano and Heredia-Laclaustra, 2004;Julien et al, 2006;Karnieli et al, 2006) as well as to monitor post-fire vegetation recovery over a variety of regions (Epting and Verbyla, 2005;Goetz et al, 2006) that include Mediterranean ecosystems Röder et al, 2008;Minchella et al, 2009). Approaches based on remote sensing have also been successfully used to assess fire risk (Chuvieco et al, 2010), burn severity (Epting and Verbyla, 2005;De Santis and Chuvieco, 2007;Kokaly et al, 2007;Miller and Thode, 2007;Fox et al, 2008;Miller et al, 2009) and erosion risk (Fox et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

Modelling post-fire vegetation recovery in Portugal

et al. 2011

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Abstract. Wildfires in Mediterranean Europe have been increasing in number and extension over the last decades and constitute one of the major disturbances of these ecosystems. Portugal is the country with more burnt area in the last decade and the years of 2003 and 2005 were particularly devastating, the total burned areas of 425 000 and 338 000 ha being several times higher than the corresponding average. The year of 2005 further coincided with one of the most severe droughts since early 20th century. Due to different responses of vegetation to diverse fire regimes and to the complexity of landscape structures, fires have complex effects on vegetation recovery. Remote sensing has revealed to be a powerful tool in studying vegetation dynamics and in monitoring post-fire vegetation recovery, which is crucial to landmanagement and to prevent erosion.The main goals of the present work are (i) to assess the accuracy of a vegetation recovery model previously developed by the authors; (ii) to assess the model's performance, namely its sensitivity to initial conditions, to the temporal length of the input dataset and to missing data; (iii) to study vegetation recovery over two selected areas that were affected by two large wildfire events in the fire seasons of 2003 and 2005, respectively.The study relies on monthly values of NDVI over 11 years (1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009), at 1 km×1 km spatial resolution, as obtained by the VEGETATION instrument. According to results from sensitivity analysis, the model is robust and able to provide good estimations of recovery times of vegetation when the regeneration process is regular, even when missing data is present. In respect to the two selected burnt scars, results indicate that fire damage is a determinant factor Correspondence to: A. Bastos (afbastos@fc.ul.pt) of regeneration, as less damaged vegetation recovers more rapidly, which is mainly justified by the high coverage of Pinus pinaster over the area, and by the fact that coniferous forests tend to recover slower than transitional woodlandshrub, which tend to dominate the areas following the fire event.

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“…In contrast, low aspen recruitment at a severely burned area was attributed to lower soil moisture. Minchella et al (2009) used multitemporal ERS SAR images to monitor the vegetation recovery in a Mediterranean burned area. Following a qualitative approach (analysis of the multitemporal backscattering signatures) they observed that, due to the increase in soil moisture in the backscattering, the measurements, taken throughout at least one year, of the similarity between the backscattering of the burned area and the backscattering of a bare soil around or inside the burned area, may provide a SAR-based index for the vegetation recovery in the burned area.…”

Section: Post-fire Albedo and Land Surface Temperaturementioning

confidence: 99%

Advances in Remote Sensing of Post-Fire Vegetation Recovery Monitoring - A Review

Gitas¹,

Mitri²,

Veraverbeke³

et al. 2012

Remote Sensing of Biomass - Principles and Applications

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Use of multitemporal SAR data for monitoring vegetation recovery of Mediterranean burned areas

Cited by 51 publications

References 14 publications

Mapping and Assessment of PM10 and O3 Removal by Woody Vegetation at Urban and Regional Level

Mapping and Assessment of PM10 and O3 Removal by Woody Vegetation at Urban and Regional Level

Modelling post-fire vegetation recovery in Portugal

Advances in Remote Sensing of Post-Fire Vegetation Recovery Monitoring - A Review

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