Centre dedocumentation
scientifique

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]

Réservation

Réserver ce document

Exemplaires (3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2019091	SL	Revue	Centre de documentation	Revues en salle	Disponible
081-2019093	DEP-RECP	Revue	MATIS	Dépôt en unité	Exclu du prêt
081-2019092	DEP-RECF	Revue	Nancy	Dépôt en unité	Exclu du prêt

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)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 75 n° 3 (September 2018) Titre : 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 Type de document : Article/Communication Auteurs : Angelo Nolè, Auteur ; Angelo Rita, Auteur ; Agostino Maria Silvio Ferrara, Auteur ; Marco Borghetti, Auteur Année de publication : 2018 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] analyse diachronique [Termes descripteurs IGN] canopée [Termes descripteurs IGN] Fagus sylvatica [Termes descripteurs IGN] forêt alpestre [Termes descripteurs IGN] forêt méditerranéenne [Termes descripteurs IGN] gelée [Termes descripteurs IGN] image Landsat-8 [Termes descripteurs IGN] image Landsat-OLI [Termes descripteurs IGN] image Landsat-TIRS [Termes descripteurs IGN] Italie [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] variation temporelle Résumé : (Auteur) Key message: A remote sensing-based approach was implemented to detect the effect of a late spring frost on beech forests in the Mediterranean mountain region. The analysis of spatio-temporal variability of frost effects on normalised difference vegetation index (NDVI) highlighted the distribution of the canopy damage across the forest according to geomorphic factors such as slope, aspect, and altitude. Context: Increased intensity and frequency of extreme temperatures such as late spring frosts and heat waves represent the main drivers affecting forest ecosystem structure and composition in the Mediterranean region. Aims: The main objective of this study was to evaluate the effects of a late spring frost disturbance, which occurred during spring 2016 in southern Italy, through the assessment of the spatial pattern of the damage to the beech forest canopy associated with the peak decrease in normalised difference vegetation index (NDVI), and the analysis of the NDVI temporal recovery after this frost disturbance. Methods: The forest areas affected by frost were detected through the NDVI differencing technique based on Landsat 8 (OLI/TIRS) imagery time series. The influence of local geomorphic factors (i.e., aspect, elevation, and slope) on forest NDVI patterns was assessed by means of a generalized additive model (GAM). Results: A rather counterintuitive NDVI patterns emerged according to the forest exposition, with NDVI significantly higher on the north facing areas than the southerly ones. The main canopy damage occurred at about 1250 m and reached up to 1500 m asl, representing the altitudinal range affected by the frost disturbance. Finally, the full canopy recovery occurred within 3 months of the frost event. Conclusion: The analysis of seasonal Landsat 8 image time series related to local geomorphic factors, such as aspect, slope, and altitude, and plant phenology on a frost event date, contributed to highlight the NDVI spatio-temporal variation and canopy recovery of a Mediterranean mountain beech forest. Numéro de notice : A2018-328 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-018-0763-1 date de publication en ligne : 16/08/2018 En ligne : https://doi.org/10.1007/s13595-018-0763-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90472 [article]

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)  

Public [article]  inGeocarto international > vol 33 n° 5 (May 2018) . - pp 443 - 457 Titre : An object-based approach for mapping forest structural types based on low-density LiDAR and multispectral imagery Type de document : Article/Communication Auteurs : Luis Angel Ruiz, Auteur ; Jorge Abel Recio, Auteur ; Pablo Crespo-Peremarch, Auteur ; Marta Sapena, Auteur Année de publication : 2018 Article en page(s) : pp 443 - 457 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] arbre de décision [Termes descripteurs IGN] biomasse (combustible) [Termes descripteurs IGN] carte forestière [Termes descripteurs IGN] classification barycentrique [Termes descripteurs IGN] classification orientée objet [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] classification par séparateurs à vaste marge [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] forêt méditerranéenne [Termes descripteurs IGN] image Sentinel-MSI [Termes descripteurs IGN] image Worldview [Termes descripteurs IGN] modèle de simulation [Termes descripteurs IGN] structure d'un peuplement forestier Résumé : (Auteur) Mapping forest structure variables provides important information for the estimation of forest biomass, carbon stocks, pasture suitability or for wildfire risk prevention and control. The optimization of the prediction models of these variables requires an adequate stratification of the forest landscape in order to create specific models for each structural type or strata. This paper aims to propose and validate the use of an object-oriented classification methodology based on low-density LiDAR data (0.5 m−2) available at national level, WorldView-2 and Sentinel-2 multispectral imagery to categorize Mediterranean forests in generic structural types. After preprocessing the data sets, the area was segmented using a multiresolution algorithm, features describing 3D vertical structure were extracted from LiDAR data and spectral and texture features from satellite images. Objects were classified after feature selection in the following structural classes: grasslands, shrubs, forest (without shrubs), mixed forest (trees and shrubs) and dense young forest. Four classification algorithms (C4.5 decision trees, random forest, k-nearest neighbour and support vector machine) were evaluated using cross-validation techniques. The results show that the integration of low-density LiDAR and multispectral imagery provide a set of complementary features that improve the results (90.75% overall accuracy), and the object-oriented classification techniques are efficient for stratification of Mediterranean forest areas in structural- and fuel-related categories. Further work will be focused on the creation and validation of a different prediction model adapted to the various strata. Numéro de notice : A2018-140 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2016.1265595 date de publication en ligne : 28/11/2016 En ligne : https://doi.org/10.1080/10106049.2016.1265595 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89690 [article]

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

Permalink

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)  

Permalink

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)  

Permalink

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

Permalink

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)  

Permalink

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)  

Permalink

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

Permalink

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)  

Permalink

Motifs des incendies de forêt en Algérie : analyse comparée des dires d'experts de la Protection Civile et des Forestiers par la méthode Delphi / Ouahiba Meddour-Sahar in VertigO, vol 14 n° 3 (décembre 2014)  

Permalink

Thinning has a positive effect on growth dynamics and growth-climate relationships in Aleppo pine (Pinus halepensis) tree of different crown classes / Jorge Olivar in Annals of Forest Science, vol 71 n° 3 (April - May 2014)  

Permalink