iForest - Biogeosciences and Forestry


COSMO-SkyMed potential to detect and monitor Mediterranean maquis fires and regrowth: a pilot study in Capo Figari, Sardinia, Italy

Gaia Vaglio Laurin (1-2)   , Ruggero Avezzano (3), Valentina Bacciu (2), Fabio Del Frate (3), Dario Papale (1), Maria Virelli (4)

iForest - Biogeosciences and Forestry, Volume 11, Issue 3, Pages 389-395 (2018)
doi: https://doi.org/10.3832/ifor2623-011
Published: May 15, 2018 - Copyright © 2018 SISEF

Research Articles

Mediterranean maquis is a complex and widespread ecosystem in the region, intrinsically prone to fire. Many species have developed specific adaptation traits to cope with fire, ensuring resistance and resilience. Due to the recent changes in socio-economy and land uses, fires are more and more frequent in the urban-rural fringe and in the coastlines, both now densely populated. The detection of fires and the monitoring of vegetation regrowth is thus of primary interest for local management and for understanding the ecosystem dynamics and processes, also in the light of the recurrent droughts induced by climate change. Among the main objectives of the COSMO-SkyMed radar constellation mission there is the monitoring of environmental hazards; the very high revisiting time of this mission is optimal for post-hazard response activities. However, very few studies exploited such data for fire and vegetation monitoring. In this research, Cosmo-SkyMed is used in a Mediterranean protected area covered by maquis to detect the burnt area extension and to conduct a mid-term assessment of vegetation regrowth. The positive results obtained in this research highlight the importance of the very high-resolution continuous acquisitions and the multi-polarization information provided by COSMO-SkyMed for monitoring fire impacts on vegetation.


Cosmo-SkyMed, Maquis, Fire, Mediterranean Vegetation

Authors’ address

Gaia Vaglio Laurin
Dario Papale
Department for Innovation in Biological, Agro-Food and Forest Systems (DIBAF), University of Tuscia, I-01100 Viterbo (Italy)
Gaia Vaglio Laurin
Valentina Bacciu
Fondazione CMCC (Euro-Mediterranean Center on Climate Change), Division on Impacts on Agriculture, Forests and Ecosystem Services, I-07100 Sassari and I-01100 Viterbo (Italy)
Ruggero Avezzano
Fabio Del Frate
Department of Civil Engineering and Computer Sciences (DICII), University of Rome Tor Vergata, I-00100 Rome (Italy)
Maria Virelli
Italian Space Agency, I-00100 Rome (Italy)

Corresponding author

Gaia Vaglio Laurin


Vaglio Laurin G, Avezzano R, Bacciu V, Frate FD, Papale D, Virelli M (2018). COSMO-SkyMed potential to detect and monitor Mediterranean maquis fires and regrowth: a pilot study in Capo Figari, Sardinia, Italy. iForest 11: 389-395. - doi: 10.3832/ifor2623-011

Academic Editor

Davide Ascoli

Paper history

Received: Sep 03, 2017
Accepted: Mar 05, 2018

First online: May 15, 2018
Publication Date: Jun 30, 2018
Publication Time: 2.37 months

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Arnett JT, Coops NC, Daniels LD, Falls RW (2015)
Detecting forest damage after a low-severity fire using remote sensing at multiple scales. International Journal of Applied Earth Observation and Geoinformation 35: 239-246.
CrossRef | Gscholar
Attema E, Ulaby FT (1978)
Vegetation modeled as a water cloud. Radio science 13 (2): 357-364.
CrossRef | Gscholar
Bastos A, Gouveia C, Da Camara C, Trigo R (2011)
Modelling post-fire vegetation recovery in Portugal. Biogeosciences 8 (12): 3593-3607.
CrossRef | Gscholar
Bernhard EM, Twele A, Gähler M (2011)
Rapid mapping of forest fires in the European Mediterranean region-a change detection approach using X-band SAR-data. Photogrammetrie-Fernerkundung-Geoinformation 4: 261-270.
CrossRef | Gscholar
Bernhard EM, Twele A, Gahler M (2012)
Burnt area mapping in the European-Mediterranean: SAR backscatter change analysis and synergistic use of optical and SAR data. In: Proceedings of Geoscience and Remote Sensing Symposium (IGARSS) 22-27 July 2012. IEEE International, Munich, Germany, pp. 2141-2143.
CrossRef | Gscholar
Bolton DK, Coops NC, Hermosilla T, Wulder MA, White JC (2017)
Assessing variability in post-fire forest structure along gradients of productivity in the Canadian boreal using multi-source remote sensing. Journal of Biogeography 44 (6): 1294-1305.
CrossRef | Gscholar
Chen W, Jiang H, Moriya K, Sakai T, Cao C (2018)
Monitoring of post-fire forest regeneration under different restoration treatments based on ALOS/PALSAR data. New Forests 49 (1): 105-121.
CrossRef | Gscholar
Chu T, Guo X, Takeda K (2016)
Remote sensing approach to detect post-fire vegetation regrowth in Siberian boreal larch forest. Ecological Indicators 62: 32-46.
CrossRef | Gscholar
Cocke AE, Fulé PZ, Crouse JE (2005)
Comparison of burn severity assessments using differenced normalized burn ratio and ground data. International Journal of Wildland Fire 14 (2): 189-198.
CrossRef | Gscholar
Corona P, Lamonaca A, Chirici G (2008)
Remote sensing support for post fire forest management. iForest - Biogeosciences and Forestry 1 (1): 6-12.
CrossRef | Gscholar
Covello F, Battazza F, Coletta A, Lopinto E, Fiorentino C, Pietranera L, Valentini G, Zoffoli S (2010)
Cosmo-SkyMed an existing opportunity for observing the earth. Journal of Geodynamics 49 (3): 171-180.
CrossRef | Gscholar
Diaz-Delgado R, Pons X (2001)
Spatial patterns of forest fires in Catalonia (NE of Spain) along the period 1975-1995: analysis of vegetation recovery after fire. Forest Ecology and Management 147 1: 67-74.
CrossRef | Gscholar
Diaz-Delgado R, Lloret F, Pons X (2003)
Influence of fire severity on plant regeneration by means of remote sensing imagery. International Journal of Remote Sensing 24 (8): 1751-1763.
CrossRef | Gscholar
Engelbrecht J, Theron A, Vhengani L, Kemp J (2017)
A simple normalized difference approach to burnt area mapping using multi-polarisation C-Band SAR. Remote Sensing 9 (8): 764.
CrossRef | Gscholar
Gimeno M, San-Miguel-Ayanz J (2004)
Evaluation of Radarsat-1 data for identification of burnt areas in southern Europe. Remote Sensing of Environment 92 (3): 370-375.
CrossRef | Gscholar
Gitas I, Mitri G, Veraverbeke S, Polychronaki A (2012)
Advances in remote sensing of post-fire vegetation recovery monitoring - a review. In: “Remote Sensing of Biomass - Principles and Applications” (Fatoyinbo L ed). InTech, London, UK, 143-177.
CrossRef | Gscholar
Holecz F, Barbieri M, Eyre C, Mönnig N (2010)
Forest management-mapping, monitoring, and inference of biophysical parameters using ALOS PALSAR and Cosmo-SkyMed data. JAXA Kyoto and Carbon Initiative 2010, Tokyo, Japan, pp. 10.
Online | Gscholar
Imperatore P, Azar R, Calo F, Stroppiana D, Brivio PA, Lanari R, Pepe A (2017)
Effect of the vegetation fire on backscattering: an investigation based on Sentinel-1 observations. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 10 (10): 4478-4492.
CrossRef | Gscholar
Jenkins LK, Bourgeau-Chavez LL, French NH, Loboda TV, Thelen BJ (2014)
Development of methods for detection and monitoring of fire disturbance in the Alaskan tundra using a two-decade long record of synthetic aperture radar satellite images. Remote Sensing 6 (7): 6347-6364.
CrossRef | Gscholar
Joyce KE, Belliss SE, Samsonov SV, McNeill SJ, Glassey PJ (2009)
A review of the status of satellite remote sensing and image processing techniques for mapping natural hazards and disasters. Progress in Physical Geography 33 (2): 183-207.
CrossRef | Gscholar
Karteris M (1996)
Burned land mapping and post-fire effects. EARSeL eProceedings 4: 90-96.
Online | Gscholar
Kasischke E, Hoy E, French N, Turetsky M (2007)
Post-fire evaluation of the effects of fire on the environment using remotely-sensed data. In: “6th EARSeL Towards an Operational Use of Remote Sensing in Forest Fire Management”. Thessaloniki (Greece) 27-29 Sept 2007. Office for Official Publications, European Community, Luxembourg, pp. 38-56.
Online | Gscholar
Key C, Benson N (2004)
Ground measure of severity, the composite burn index. Firemon Landscape Assessment 4: 1-55.
Kurum M (2015)
C-band SAR backscatter evaluation of 2008 Gallipoli forest fire. IEEE Geoscience and Remote Sensing Letters 12 (5): 1091-1095.
CrossRef | Gscholar
Lentile LB, Holden ZA, Smith AM, Falkowski MJ, Hudak AT, Morgan P, Lewis SA, Gessler PE, Benson NC (2006)
Remote sensing techniques to assess active fire characteristics and post-fire effects. International Journal of Wildland Fire 15 (3): 319-345.
CrossRef | Gscholar
Lohberger S, Stängel M, Atwood EC, Siegert F (2017)
Spatial evaluation of Indonesia’s 2015 fire affected area and estimated carbon emissions using Sentinel-1. Global Change Biology 24 (2): 644-654.
CrossRef | Gscholar
Mari N, Laneve G, Cadau E, Porcasi X (2012)
Fire damage assessment in Sardinia: the use of Alos /Palsar data for post fire effects management. European Journal of Remote Sensing 45 (1): 233-241.
CrossRef | Gscholar
Miller JD, Knapp EE, Key CH, Skinner CN, Isbell CJ, Creasy RM, Sherlock JW (2009)
Calibration and validation of the relative differenced normalized burn ratio (RDNBR) to three measures of fire severity in the Sierra Nevada and Klamath mountains, California, USA. Remote Sensing of Environment 113 (3): 645-656.
CrossRef | Gscholar
Minchella A, Del Frate F, Capogna F, Anselmi S, Manes F (2009)
Use of multitemporal sar data for monitoring vegetation recovery of Mediterranean burned areas. Remote Sensing of Environment 113 (3): 588-597.
CrossRef | Gscholar
Polychronaki A, Gitas IZ, Veraverbeke S, Debien A (2013)
Evaluation of Alos Palsar imagery for burned area mapping in Greece using object-based classification. Remote Sensing 5 (11): 5680-5701.
CrossRef | Gscholar
Ranson K, Sun G, Kovacs K, Kharuk V (2002)
Utility of SAR for mapping forest disturbance in Siberia. In: Proceedings of the “Geoscience and Remote Sensing Symposium”. Toronto (Canada) 24-28 June 2002. IEEE International 4: 2081-2083.
Richter R, Schläpfer D (2015)
Atmospheric/topographic correction for satellite imagery: ATCOR-2/3 user guide, version 9.0.0. Wessling, ReSe Applications Schläpfer, Switzerland, pp. 254.
Ricotta C, Avena G, Olsen E, Ramsey R, Winn D (1998)
Monitoring the landscape stability of Mediterranean vegetation relation to fire with a fractal algorithm. International Journal of Remote Sensing 19 (5): 871-881.
CrossRef | Gscholar
Ruffault J, Mouillot F (2017)
Contribution of human and biophysical factors to the spatial distribution of forest fire ignitions and large wildfires in a French Mediterranean region. International Journal of Wildland Fire 26 (6): 498-508.
CrossRef | Gscholar
Saatchi S, Halligan K, Despain DG, Crabtree RL (2007)
Estimation of forest fuel load from radar remote sensing. IEEE Transactions on Geoscience and Remote Sensing 45 (6): 1726-1740.
CrossRef | Gscholar
San-Miguel-Ayanz J, Schulte E, Schmuck G, Camia A, Strobl P, Liberta G, Giovando C, Boca R, Sedano F, Kempeneers P, Mcinerney D, Withmore C, De Oliveira SS, Rodrigues M, Durrant T, Corti P, Oehler F, Vilar L, Amatulli G (2012)
Comprehensive monitoring of wildfires in Europe: the European Forest Fire Information System (EFFIS). In: “Approaches to Managing Disaster - Assessing Hazards, Emergencies and Disaster Impacts”. InTech, London, UK, pp. 87-108.
CrossRef | Gscholar
Shoshany M (2000)
Satellite remote sensing of natural Mediterranean vegetation: a review within an ecological context. Progress in Physical Geography 24 (2): 153-178.
CrossRef | Gscholar
Stroppiana D, Azar R, Calò F, Pepe A, Imperatore P, Boschetti M, Silva J, Brivio P, Lanari R (2015)
Integration of optical and SAR data for burned area mapping in Mediterranean regions. Remote Sensing 7 (2): 1320-1345.
CrossRef | Gscholar
Tanase MA, Santoro M, De La Riva J, Perez-Cabello F, Le Toan T (2010a)
Sensitivity of X-, C-, and l-band SAR backscatter to burn severity in Mediterranean pine forests. IEEE Transactions on Geoscience and Remote Sensing 48 (10): 3663-3675.
CrossRef | Gscholar
Tanase MA, Perez-Cabello F, De La Riva J, Santoro M (2010b)
TerraSAR-X data for burn severity evaluation in Mediterranean forests on sloped terrain. IEEE Transactions on Geoscience and Remote Sensing 48 (2): 917-929.
CrossRef | Gscholar
Tanase MA, Santoro M, Wegmuller De La Riva J, Perez-Cabello F (2010c)
Properties of X-, C- and l-band repeat-pass interferometric SAR coherence in Mediterranean pine forests affected by fires. Remote Sensing of Environment 114 (10): 2182-2194.
CrossRef | Gscholar
Tanase MA, De La Riva J, Santoro M, Perez-Cabello F, Kasischke E (2011)
Sensitivity of sar data to post-fire forest regrowth in Mediterranean and boreal forests. Remote Sensing of Environment 115 (8): 2075-2085.
CrossRef | Gscholar
Tanase MA, Santoro M, Aponte C, De La Riva J (2014)
Polarimetric properties of burned forest areas at c- and l-band. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 7: 267-276.
CrossRef | Gscholar
Tanase MA, Kennedy R, Aponte C (2015)
Fire severity estimation from space: a comparison of active and passive sensors and their synergy for different forest types. International Journal of Wildland Fire 24 (8): 1062-1075.
CrossRef | Gscholar
Ulander L (1996)
Radiometric slope correction of synthetic-aperture radar images. IEEE Transactions on Geoscience and Remote Sensing 34: 1115-1122.
CrossRef | Gscholar
Van Wagtendonk JW, Root RR, Key CH (2004)
Comparison of Aviris and Landsat ETM+ detection capabilities for burn severity. Remote Sensing of Environment 92 (3): 397-408.
CrossRef | Gscholar

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