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Size dependency of variables influencing fire occurrence in Mediterranean forests of Eastern Spain / Marina Peris-Llopis in European Journal of Forest Research, vol 139 n°4 (August 2020)  

Public [article]  inEuropean Journal of Forest Research > vol 139 n°4 (August 2020) . - pp 525 - 537 Titre : Size dependency of variables influencing fire occurrence in Mediterranean forests of Eastern Spain Type de document : Article/Communication Auteurs : Marina Peris-Llopis, Auteur ; José Ramon Gonzalez-Olabarria, Auteur ; Blas Mola-Yudego, Auteur Année de publication : 2020 Article en page(s) : pp 525 - 537 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] altitude [Termes descripteurs IGN] cartographie numérique [Termes descripteurs IGN] combinaison linéaire ponderée [Termes descripteurs IGN] forêt méditerranéenne [Termes descripteurs IGN] fréquence [Termes descripteurs IGN] incendie de forêt [Termes descripteurs IGN] pente [Termes descripteurs IGN] Pinus (genre) [Termes descripteurs IGN] plan de prévention des risques [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Fires are among the most damaging disturbances to forests in the Mediterranean area. The study analyses the occurrence and characteristics of forest fires in Eastern Spain (1993–2015) to identify key variables related to burnt forest land, differentiating fires according to their burnt area. Data are retrieved from digital cartography, the Spanish Forest Map and data concerning fires. Based on previous research, the variables included are altitude, slope, aspect, fuel, species, population and road density. The fires are classified in small (5–50 ha), medium (50–500 ha) and large (> 500 ha). Four models are considered to explain the proportion of burnt area based on weighted generalized linear models: a general model and one per size class. The results highlight the different relations of similar variables with fires according to the size. When a single model is considered to explain all area burnt, the relationships are mainly driven by large fires. The larger area is burnt on forests with pine, bushes and small trees, whereas smaller fires tend to occur on lower altitude, low slope, high population and road densities. There are large differences in the variables according to the fire sizes, especially for the presence of pine (negative in the medium fires model but positive for the large fires model) and Pasture (which only explains the small fires). The models can be applied to analyse occurrence by fire size in Mediterranean areas, and the results can help elaborate fire prevention strategies and land-planning schemes. Numéro de notice : A2020-423 Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10342-020-01265-9 date de publication en ligne : 10/02/2020 En ligne : https://doi.org/10.1007/s10342-020-01265-9 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95486 [article]

Monitoring clearcutting and subsequent rapid recovery in Mediterranean coppice forests with Landsat time series / Gherardo Chirici in Annals of Forest Science [en ligne], Vol 77 n° 2 (June 2020)  

Public [article]  inAnnals of Forest Science [en ligne] > Vol 77 n° 2 (June 2020) Titre : Monitoring clearcutting and subsequent rapid recovery in Mediterranean coppice forests with Landsat time series Type de document : Article/Communication Auteurs : Gherardo Chirici, Auteur ; Francesca Giannetti, Auteur ; Erica Mazza, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] brûlis [Termes descripteurs IGN] canopée [Termes descripteurs IGN] coupe rase (sylviculture) [Termes descripteurs IGN] dégradation du signal [Termes descripteurs IGN] forêt méditerranéenne [Termes descripteurs IGN] image Landsat [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] reconstruction du signal [Termes descripteurs IGN] régénération (sylviculture) [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] taillis [Termes descripteurs IGN] télémètre laser aéroporté Résumé : (auteur) Key message: This work analyses the rate of recovery of the spectral signal from clearcut areas of coppice Mediterranean forests using Landsat Time Series (LTS). The analysis revealed a more rapid rate of spectral signal recovery than what was found in previous investigations in boreal and temperate forests. Context: The rate of post-disturbance vegetation recovery is an important component of forest dynamics. Aims: In this study, we analyze the recovery of the spectral signal from forest clearcut areas in Mediterranean conditions when the coppice system of forest management is applied. Methods: We used LTS surface reflectance data (1999–2015). We generated an annual reference database of clearcuts using visual interpretation and local forest inventory data, and then derived the Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR) spectral trajectories for these clearcuts. From these spectral trajectories, we calculated the Years to Recovery or Y2R, the number of years it takes for a pixel to return to within a specified threshold (i.e., 70%, 80%, 90%, 100%) of its pre-disturbance value. Spectral recovery rates were then corroborated using measures of canopy height derived from airborne laser scanning (ALS) data. Results: The coppice system is associated with rapid recovery rates when compared to rates of recovery from seeds or seedlings in temperate and boreal forest conditions. We found that the Y2R derived from the spectral trajectories of post-clearcut NBR and NDVI provided similar characterizations of rapid recovery for the coppice system of forest management applied in our study area. The ALS measures of canopy height indicated that the Y2R metric accurately captured the rapid regeneration of coppice systems. Conclusion: The rapid rate of spectral recovery associated with the coppice system is 2–4 years, which contrasts with values reported in boreal and temperate forest environments, where spectral recovery was attained in approximately 10 years. NBR is an effective index for assessing rapid recovery in this forest system. Numéro de notice : A2020-293 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-00936-2 date de publication en ligne : 15/04/2020 En ligne : https://doi.org/10.1007/s13595-020-00936-2 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95123 [article]

Burn severity analysis in Mediterranean forests using maximum entropy model trained with EO-1 Hyperion and LiDAR data / Alfonso Fernández-Manso in ISPRS Journal of photogrammetry and remote sensing, vol 155 (September 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 155 (September 2019) . - pp 102 - 118 Titre : Burn severity analysis in Mediterranean forests using maximum entropy model trained with EO-1 Hyperion and LiDAR data Type de document : Article/Communication Auteurs : Alfonso Fernández-Manso, Auteur ; Carmen Quintano, Auteur ; Dar A. Roberts, Auteur Année de publication : 2019 Article en page(s) : pp 102 - 118 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] entropie [Termes descripteurs IGN] forêt méditerranéenne [Termes descripteurs IGN] image EO1-Hyperion [Termes descripteurs IGN] incendie de forêt [Termes descripteurs IGN] multiple endmember spectral mixture analysis Résumé : (Auteur) All ecosystems and in particular ecosystems in Mediterranean climates are affected by fires. Knowledge of the drivers that most influence burn severity patterns as well an accurate map of post-fire effects are key tools for forest managers in order to plan an adequate post-fire response. Remote sensing data are becoming an indispensable instrument to reach both objectives. This work explores the relative influence of pre-fire vegetation structure and topography on burn severity compared to the impact of post-fire damage level, and evaluates the utility of the Maximum Entropy (MaxEnt) classifier trained with post-fire EO-1 Hyperion data and pre-fire LiDAR to model three levels of burn severity at high accuracy. We analyzed a large fire in central-eastern Spain, which occurred on 16–19 June 2016 in a maquis shrubland and Pinus halepensis forested area. Post-fire hyperspectral Hyperion data were unmixed using Multiple Endmember Spectral Mixture Analysis (MESMA) and five fraction images were generated: char, green vegetation (GV), non-photosynthetic vegetation, soil (NPVS) and shade. Metrics associated with vegetation structure were calculated from pre-fire LiDAR. Post-fire MESMA char fraction image, pre-fire structural metrics and topographic variables acted as inputs to MaxEnt, which built a model and generated as output a suitability surface for each burn severity level. The percentage of contribution of the different biophysical variables to the MaxEnt model depended on the burn severity level (LiDAR-derived metrics had a greater contribution at the low burn severity level), but MaxEnt identified the char fraction image as the highest contributor to the model for all three burn severity levels. The present study demonstrates the validity of MaxEnt as one-class classifier to model burn severity accurately in Mediterranean countries, when trained with post-fire hyperspectral Hyperion data and pre-fire LiDAR. Numéro de notice : A2019-313 Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.isprsjprs.2019.07.003 date de publication en ligne : 14/07/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.07.003 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93339 [article]

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Combining low-density LiDAR and satellite images to discriminate species in mixed Mediterranean forest / Angela Blázquez-Casado in Annals of Forest Science [en ligne], vol 76 n° 2 (June 2019)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 76 n° 2 (June 2019) Titre : Combining low-density LiDAR and satellite images to discriminate species in mixed Mediterranean forest Type de document : Article/Communication Auteurs : Angela Blázquez-Casado, Auteur ; Rafael Calama, Auteur ; Manuel Valbuena, Auteur ; Marta Vergarechea, Auteur ; Francisco Rodriguez, Auteur Année de publication : 2019 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] analyse discriminante [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] forêt méditerranéenne [Termes descripteurs IGN] houppier [Termes descripteurs IGN] image Pléiades-HR [Termes descripteurs IGN] Pinus pinaster [Termes descripteurs IGN] Pinus pinea Résumé : (Auteur) Context : The discrimination of tree species at individual level in mixed Mediterranean forest based on remote sensing is a field which has gained greater importance. In these stands, the capacity to predict the quality and quantity of non-wood forest products is particularly important due to the very different goods the two species produce. Aims : To assess the potential of using low-density airborne LiDAR data combined with high-resolution Pleiades images to discriminate two different pine species in mixed Mediterranean forest (Pinus pinea L. and Pinus pinaster Ait.) at individual tree level. Methods : A Random Forest model was trained using plots from the pure stand dataset, determining which LiDAR and satellite variables allow us to obtain better discrimination between groups. The model constructed was then validated by classifying individuals in an independent set of pure and mixed stands. Results : The model combining LiDAR and Pleiades data provided greater accuracy (83.3% and 63% in pure and mixed validation stands, respectively) than the models which only use one type of covariables. Conclusion : The automatic crown delineation tool developed allows two very similar species in mixed Mediterranean conifer forest to be discriminated using continuous spatial information at the surface: Pleiades images and open source LiDAR data. This approach is easily applicable over large areas, enhancing the economic value of non-wood forest products and aiding forest managers to accurately predict production. Numéro de notice : A2019-180 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-019-0835-x date de publication en ligne : 17/05/2019 En ligne : https://doi.org/10.1007/s13595-019-0835-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92700 [article]

Drought sensitiveness on forest growth in peninsular Spain and the Balearic Islands / Marina Peña-Gallardo in Forests, vol 9 n° 9 (September 2018)  

Public [article]  inForests > vol 9 n° 9 (September 2018) Titre : Drought sensitiveness on forest growth in peninsular Spain and the Balearic Islands Type de document : Article/Communication Auteurs : Marina Peña-Gallardo, Auteur ; S.M. Vicente-Serrano, Auteur ; J. Julio Camarero, Auteur ; et al., Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Végétation [Termes descripteurs IGN] analyse de sensibilité [Termes descripteurs IGN] Baléares, îles [Termes descripteurs IGN] croissance végétale [Termes descripteurs IGN] dendrochronologie [Termes descripteurs IGN] Espagne [Termes descripteurs IGN] forêt méditerranéenne [Termes descripteurs IGN] indice d'humidité [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] productivité [Termes descripteurs IGN] sécheresse Résumé : (Auteur) Drought is one of the key natural hazards impacting net primary production and tree growth in forest ecosystems. Nonetheless, tree species show different responses to drought events, which make it difficult to adopt fixed tools for monitoring drought impacts under contrasting environmental and climatic conditions. In this study, we assess the response of forest growth and a satellite proxy of the net primary production (NPP) to drought in peninsular Spain and the Balearic Islands, a region characterized by complex climatological, topographical, and environmental characteristics. Herein, we employed three different indicators based on in situ measurements and satellite image-derived vegetation information (i.e., tree-ring width, maximum annual greenness, and an indicator of NPP). We used seven different climate drought indices to assess drought impacts on the tree variables analyzed. The selected drought indices include four versions of the Palmer Drought Severity Index (PDSI, Palmer Hydrological Drought Index (PHDI), Z-index, and Palmer Modified Drought Index (PMDI)) and three multi-scalar indices (Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Precipitation Index (SPI), and Standardized Precipitation Drought Index (SPDI)). Our results suggest that—irrespective of drought index and tree species—tree-ring width shows a stronger response to interannual variability of drought, compared to the greenness and the NPP. In comparison to other drought indices (e.g., PDSI), and our results demonstrate that multi-scalar drought indices (e.g., SPI, SPEI) are more advantageous in monitoring drought impacts on tree-ring growth, maximum greenness, and NPP. This finding suggests that multi-scalar indices are more appropriate for monitoring and modelling forest drought in peninsular Spain and the Balearic Islands. Numéro de notice : A2018-504 Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/f9090524 date de publication en ligne : 30/08/2018 En ligne : https://doi.org/10.3390/f9090524 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91217 [article]

Effects of a large-scale late spring frost on a beech (Fagus sylvatica L.) dominated Mediterranean mountain forest derived from the spatio-temporal variations of NDVI / Angelo Nolè in Annals of Forest Science [en ligne], vol 75 n° 3 (September 2018)  

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An object-based approach for mapping forest structural types based on low-density LiDAR and multispectral imagery / Luis Angel Ruiz in Geocarto international, vol 33 n° 5 (May 2018)  

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The potential of multifrequency SAR images for estimating forest biomass in Mediterranean areas / Emanuele Santi in Remote sensing of environment, vol 200 (October 2017)  

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Crown bulk density and fuel moisture dynamics in Pinus pinaster stands are neither modified by thinning nor captured by the Forest Fire Weather Index / Marc Soler Martin in Annals of Forest Science [en ligne], vol 74 n° 3 (September 2017)  

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Assessment of the impacts of climate change on Mediterranean terrestrial ecosystems based on data from field experiments and long-term monitored field gradients in Catalonia / Josep Peñuelas in Environmental and Experimental Botany, vol (May 2017)  

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Modeling Mediterranean forest structure using airborne laser scanning data / Francesca Bottalico in International journal of applied Earth observation and geoinformation, vol 57 (May 2017)  

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A meta-analysis of functional group responses to forest recovery outside of the tropics / Rebecca Spake in Conservation biology, vol 29 n° 6 (December 2015)  

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Tree rings reflect growth adjustments and enhanced synchrony among sites in Iberian stone pine (Pinus pinea L.) under climate change / Fabio Natalini in Annals of Forest Science [en ligne], vol 72 n° 8 (December 2015)  

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Mediterranean forest species mapping using classification of Hyperion imagery / Georgia Galidaki in Geocarto international, vol 30 n° 1 - 2 (January - February 2015)

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Satellite data as indicators of tree biomass growth and forest dieback in a Mediterranean holm oak forest / Romà Ogaya in Annals of Forest Science [en ligne], vol 72 n° 1 (January 2015)  

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