Cartografía de severidad de incendios forestales a partir de la combinación del modelo de mezclas espectrales y la clasificación basada en objetos

This study shows an accurate and fast methodology in order to evaluate fire severity classes of large forest fires. A single Landsat Enhanced Thematic Mapper multispectral image was utilized in this study with the aim of mapping fire severity classes (high, moderate and low) using a combined-approach based in an spectral mixing model and object-based image analysis. A large wildfire in the Northwest of Spain is used to test the model. Fraction images obtained by Landsat unmixing were used as input data in the object-based image analysis. A multilevel segmentation and a classification were carried out by using membership functions. This method was compared with other simplest ones in order to evaluate the suitability to distinguish between the three fire severity classes above mentioned. McNemar’s test was used to evaluate the statistical significance of the difference between approaches tested in this study. The combined approach achieved the highest accuracy reaching 97.32% and kappa index of agreement of 95.96% and improving accuracy of individual classes.Este estudio presenta una metodología rápida y precisa para la evaluación de los niveles de severidad que afectan a grandes incendios forestales. El trabajo combina un modelo de mezclas espectrales y un análisis de imágenes basado en objetos con el objetivo de cartografiar distintos niveles de severidad (alto, moderado y bajo) empleando una imagen multiespectral Landsat Enhanced Thematic Mapper. Este modelo es testado en un gran incendio forestal ocurrido en el noroeste de España. Las imágenes fracción obtenidas tras aplicar el modelo de mezclas a la imagen Landsat fueron utilizadas como datos de entrada en el análisis basado en objetos. En este se llevó a cabo una segmentación multinivel y una posterior clasificación usando funciones de pertenencia. Esta metodología fue comparada con otras más simples con el fin de evaluar su conveniencia a al hora de distinguir entre los tres niveles de severidad anteriormente mencionados. El test de McNemar fue empleado para evaluar la significancia estadística de la diferencia entre los métodos testados en el estudio. El método combinado alcanzó la más alta precisión con un 97,32% y un índice Kappa del 95,96%, además de mejorar la precisión de los niveles individualmente

Burn severity mapping from Landsat MESMA fraction images and Land Surface Temperature

14 p.Forest fires are incidents of great importance in Mediterranean environments. Landsat data have proven to be suitable for evaluating post-fire vegetation damage and determining different levels of burn severity, which is crucial for planning post-fire rehabilitation. This study assessed the utility of combined Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images and Land Surface Temperature (LST) to accurately map burn severity. We studied a large convection- dominated wildfire, which occurred on 19–21 September 2012 in Spain, in a zone dominated by Pinus pinaster Ait. Burn severity degree (low, moderate, and high) was measured 2–3 months after fire in 111 field plots using the Composite Burn Index (CBI). Four fraction images were generated using MESMA from the reflective bands of a post-fire Landsat 7 Enhanced Thematic Mapper (ETM +) image: 1.-char, 2.-green vegetation (GV), 3.-non-photosynthetic vegetation and soil (NPVS) and 4.-shade. The thermal band was converted to LST using a single channel algorithm. Next, Multinomial Logistic Regression (MLR) was used to obtain the probability of each burn severity level from MESMA fraction images and LST. Finally, a burn severity map was generated from the probability images and independently validated using an error matrix, producer and user accuracies per class, and κ statistic. MLR identified the char fraction image and LST as the only significant explanatory variables when burn severity acted as the response variable. Two burn severity degrees (low-moderate and high) were finally considered to build the final burn severity map. In this way, we reached a higher accuracy (κ = 0.79) than using the original three burn severity levels (κ = 0.66). Our study demonstrates the validity of combining fraction images and LST from Landsat data to map burn severity accurately in Mediterranean countriesS

Desarrollo y aplicaciones de un modelo de crecimiento para plantaciones de Pinus radiata D. Don en El Bierzo (León)

A dynamic growth model for Pinus radiata D. Don plantations in El Bierzo (Spain) was developed with data from two inventories of permanent plots, of between 7 and 36 years old, established by the University of León. In this model, stand conditions at any point in time are defined by three state variables (stand basal area, number of trees per hectare and dominant height).Themodel includes three transition functions derived by the generalized algebraic difference approach to enable projection of the state variables at any particular time. Once they are known, the number of trees in each diameter class is estimated with a distribution function, by recovery of the parameters of theWeibull function by use of the moments method. Finally, a generalized height-diameter function and a taper function allow estimation of total or merchantable stand volume. The model provides satisfactory predictions for a time interval of three years. Simulation of the growth of four stands under two silvicultural regimes and two different sites confirm that the estimates provided by the overall model adequately represent the effects of both stand density and site quality. Other applications for the model are analysed and discussed.Se ha desarrollado un modelo dinámico de crecimiento para plantaciones de Pinus radiata D. Don en El Bierzo (León) a partir de datos de dos inventarios de parcelas permanentes, de entre 7 y 36 años de edad, establecidas por la Universidad de León. En este modelo, las condiciones del rodal en un instante dado están definidas por tres variables de estado (área basimétrica, número de pies por hectárea y altura dominante). El modelo incluye tres funciones de transición obtenidas mediante la metodología de ecuaciones en diferencias algebraicas generalizadas que permite la proyección de las variables de estado a un determinado instante en el tiempo. Una vez conocidas las variables de estado, una función de distribución estima el número de pies en cada clase diamétrica mediante la metodología de recuperación de los parámetros de la función deWeibull usando el método de los momentos. Finalmente, una función de altura-diámetro generalizada y una función de perfil de tronco permiten la estimación del volumen total o comercial del rodal. El modelo proporciona predicciones satisfactorias para un intervalo de proyección de tres años. La simulación del crecimiento de cuatro rodales bajo dos regímenes selvícolas distintos y dos calidades de estación diferentes corrobora que las estimaciones proporcionadas por el modelo global representan adecuadamente los efectos de la densidad de la masa y la calidad de la estación. Finalmente se analizan y discuten otras aplicaciones del modelo elaborado

Burn severity analysis in Mediterranean forests using maximum entropy model trained with EO-1 Hyperion and LiDAR data

P. 102-118All 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.S

Burn severity influence on post-fire vegetation cover resilience from Landsat MESMA fraction images time series in Mediterranean forest ecosystems

14 p.Mediterranean ecosystems are adapted to recurrent forest fires by having regeneration mechanisms that overcome the immediate effects of fire. However, the increasing frequency of fires in most European Mediterranean countries is challenging the natural regrowth capability of these ecosystems. In this context, monitoring post-fire vegetation recovery is a priority for forest management and soil erosion control. In this work, a 13-year series (1999–2011) of Landsat 5 Thematic Mapper (TM)/Landsat 7 Enhanced Thematic Mapper (ETM +) data was used to model post-fire vegetation recovery as a function of burn severity and to quantify post-fire resilience as a measure of vegetation cover regrowth. We evaluated a large forest fire located in Spain that burned approximately 30 km2 of Pinus pinaster Ait. in August 1998. 88 field plots of four burn severity levels (unburned, low, moderate and high) were measured in the field a year after the fire. As a variable representative of vegetation, we chose the shade normalized green vegetation fraction image (SGV) obtained by applying Multiple Endmember Spectral Mixture Analysis (MESMA) to the original Landsat TM/ETM + images. The SGV values were extracted for the 88 field plots and, after performing a one-way analysis of variance (ANOVA), a Fisher's Least Significant Difference (LSD) test allowed us to estimate resilience of vegetation cover as the number of post-fire years exhibiting a statistically significant difference between burned and unburned areas. Next, SGV values were referenced to unburned control plots values and the vegetation recovery index (VRI) was defined. The evolution in time curve of VRI for low, moderate and highly fire affected vegetation was fit using trend models (specifically, an exponential trend for VRI in high and moderate burn severity levels; a linear trend for low burn severity level, Root Mean Square Error, RMSE = 0.18, 0.13, and 0.09, respectively). We observed that vegetation cover affected by low severity fire recovered to its original state after 7 years, and vegetation cover affected by moderate severity recovered after 13 years. Vegetation affected by high severity fire was estimated to recover after 20 years. We conclude that VRI time series based on multitemporal MESMA fractions from Landsat data can be considered a valuable indicator of the post-fire vegetation cover recovery. Its temporal evolution represented post-fire vegetation cover regrowth adequately and facilitated the estimate of vegetation cover resilience in Mediterranean forestsS

Study of post-fire severity in the Valencia region comparing the NBR, RdNBR and RBR indexes derived from Landsat 8 images

Revista oficial de la Asociación Española de Teledetección[EN] In Mediterranean territories, with their characteristic climate that implies long periods of drought and rains often concentrated in torrential episodes, forest managers are faced with a series of decisions that can be urgent after a wildfire, some of them strongly correlated with the degree of damage caused by fire. In this sense, the object of this study was to provide a fast and reliable tool for the initial assessment of post-fire severity in these kinds of territories, by means of remote sensing techniques. Using Landsat 8 imagery, we have calculated three fire severity indices (dNBR, RdNBR, and RBR) for nine fires occurred in the Valencia region, a typical Mediterranean area. For each index, post-fire severity classification thresholds have been obtained taking into account the following categories: unburned, low, moderate, and high. These thresholds have been validated using, as ground-reference, aerial photographs taken from a helicopter. Afterwards, the degree to which post-fire severity was influenced by factors associated with pre-fire vegetation was evaluated, using a variance analysis. This analysis served to compare the three indices in terms of their robustness against the influence of these factors. With the obtained data, and with the study of classification accuracies employing the Kappa statistic, we were able to propose the most suitable index for calculating post-fire severity in the Valencia region, along with its operating thresholds. The findings suggest that the results could be extrapolated to other areas of similar characteristics.[ES] En territorios de ámbito mediterráneo, con su climatología característica que incluye largos periodos de sequía y lluvias que suelen concentrarse en episodios torrenciales, los gestores forestales, tras un incendio, se enfrentan a una serie de decisiones que pueden ser de carácter urgente, algunas de ellas muy correlacionadas con el grado de daño causado por el fuego. En este sentido, el objeto de este estudio ha sido proporcionar una herramienta rápida y fiable para la evaluación inicial de la severidad post-incendio en este tipo de territorios, a partir de técnicas de teledetección. Para nueve incendios ocurridos en la Comunidad Valenciana, zona típicamente mediterránea, y a partir de imágenes Landsat 8, se han calculado tres índices de severidad: dNBR, RdNBR y RBR. Se han obtenido, para cada índice, los umbrales operativos de clasificación de la severidad en cuatro categorías (no quemado, baja, moderada y alta), validados utilizando como referencia-terreno fotografías aéreas tomadas desde helicóptero. Posteriormente se evaluó el grado en que la severidad post-incendio está influenciada por factores asociados a la vegetación preincendio, utilizando para ello un análisis de varianza. Este análisis sirvió para comparar los tres índices en cuanto a su robustez frente a la influencia de estos factores. Con estos datos, y con el estudio de la precisión de clasificación a través del estadístico Kappa, se ha podido llegar a una proposición de índice más idóneo para el cálculo de la severidad post-incendio en el territorio estudiado, con sus umbrales operativos validados. Los resultados obtenidos permiten pensar que podrían ser extrapolables a otros territorios de características similares.Este trabajo ha sido realizado gracias a la colaboración de la Agencia de Seguridad y Respuesta a las Emergencias de la Generalitat Valenciana, con mención especial a D. Jorge Suárez Torres, Subdirector General de la misma.Botella-Martínez, MA.; Fernández-Manso, A. (2017). Estudio de la severidad post-incendio en la Comunidad Valenciana comparando los índices dNBR, RdNBR y RBR a partir de imágenes Landsat 8. Revista de Teledetección. (49):33-47. doi:10.4995/raet.2017.7095SWORD33474

Vegetation and soil fire damage analysis based on species distribution modeling trained with multispectral satellite data

Producción CientíficaForest managers demand reliable tools to evaluate post-fire vegetation and soil damage. In this study, we quantify wildfire damage to vegetation and soil based on the analysis of burn severity, using multitemporal and multispectral satellite data and species distribution models, particularly maximum entropy (MaxEnt). We studied a mega-wildfire (9000 ha burned) in North-Western Spain, which occurred from 21 to 27 August 2017. Burn severity was measured in the field using the composite burn index (CBI). Burn severity of vegetation and soil layers (CBIveg and CBIsoil) was also differentiated. MaxEnt provided the relative contribution of each pre-fire and post-fire input variable on low, moderate and high burn severity levels, as well as on all severity levels combined (burned area). In addition, it built continuous suitability surfaces from which the burned surface area and burn severity maps were built. The burned area map achieved a high accuracy level (κ = 0.85), but slightly lower accuracy when differentiating the three burn severity classes (κ = 0.81). When the burn severity map was validated using field CBIveg and CBIsoil values we reached lower κ statistic values (0.76 and 0.63, respectively). This study revealed the effectiveness of the proposed multi-temporal MaxEnt based method to map fire damage accurately in Mediterranean ecosystems, providing key information to forest managers.Ministerio de Economía, Industria y Competitividad (project 559 AGL2017-86075-C2-1-R)Junta de Castilla y León (project LE001P17)Ministerio de Educación, Cultura y Deporte (grants PRX17/00234 and PRX17/00133

Sistemas tradicionales de ordenación forestal en el centro de la Cuenca del Duero (España)

The historical documentation contributes enough data to understand the traditional management of our woodlands. This work studies a wide space of the interior of Castilla y León, the calcareous plateaus, characterized traditionally by the presence of wide sectors with «encina» (Quercus ilex subsp. ballota) and «quejigo» (Quercus faginea subsp. faginea), and by the historical permanency of three transcendent uses in the life of the woodlands: the firewood, the charcoal and the grass. This documentation allows, first, to verify the existence of some bases of the forest treatment and management in the administration of these woodlands and, second, of a forest planning in short and long term.La documentación histórica aporta suficientes datos como para recomponer la ordenación tradicional de nuestros montes. El trabajo que se presenta hace un intento en este sentido para un sector del interior de Castilla y León, los páramos calcáreos, caracterizado tradicionalmente por la presencia de extensas superficies arboladas con encina (Quercus ilex L. subsp. ballota (Desf.) Samp.) y quejigo (Quercus faginea Lam. subsp. faginea Amaral Franco) y por la continuidad histórica de tres aprovechamientos nucleadores de la vida de estos montes: la leña, el carbón y el pasto. Dicha documentación permite dibujar la existencia de unas bases selvícolas y dasocráticas en la gestión de dichas masas y de una planificación forestal a corto y largo plazo. Unas y otras se plasmas en la relación que se establece entre determinados aprovechamientos y la elección de ciertas especies, en la existencia de una dos formas fundamentales de masa y en la división por cabida como método de ordenación dominante

Flexible membranes anchored to the ground for slope stabilisation: Numerical modelling of soil slopes using SPH

An alternative modelling for flexible membranes anchored to the ground for soil slope stabilisation is presented using Smoothed-Particle Hydrodynamics to model the unstable ground mass in a soil slope, employing a dynamic solve engine. A regression model of pressure normal to the ground, qsim, and also membrane deflection, fsim, have been developed using Design of Experiment. Finally, a comparison between the pressure obtained from numerical simulation and from a limit equilibrium analysis considering infinite slope has been carried out, showing differences in the results, mainly due to the membrane stiffness.The realization of this research paper has been possible thanks to the funding of the following entities: SODERCAN (Sociedad para el Desarrollo de Cantabria), Consejería de Obras Públicas del Gobierno de Cantabria, Iberotalud S.L., Malla Talud Cantabria S.L. and Contratas Iglesias S.L. The authors wish also to acknowledge the support provided by the GICONSIME Research Group of the University of Oviedo and the GITECO Research Group of the University of Cantabria. We also thank Swanson Analysis Inc. for the use of the ANSYS Academic program

Growth of out-of-plane standing MoTe2(1-x)Se2x/MoSe2 composite flake films by sol–gel nucleation of MoOy and isothermal closed space telluro-selenization

This study describes the sol–gel processing of MoOy on Si (1 0 0) to subsequently achieve out-of-plane MoTe2/MoSe2 flake composite films by an isothermal closed space vapor transformation. The oxide precursor films have been prepared from a Mo isopropoxide solution in isopropanol and acid catalysis induced by HCl. Thermal annealing at 200, 400 and 600 °C enhanced the condensation after xerogel formation. An x-ray absorption analysis demonstrates that films condensed at 200 °C are at an intermediate chemical state between MoO3 and MoO2. To achieve MoTe2/MoSe2 composite films, the precursor oxide films were reduced in H2 and exposed to the chalcogenides by isothermal closed space vapor transport at 600 °C. The multilayered nanocomposite films grow with an out-of-plane flake-like structure and an evident integration of Se in the MoTe2 phase according to a MoTe2(1-x)Se2x alloy, with an estimation of x of 0.25. The alloy and the orientation of the flakes are consistent with the bands present in the Raman spectrum. These films are attractive for applications requiring high surface area interfaces favoring gas or ion exchange reactions with transition metal dichalcogenidesThe current research was funded by grant CTQ2017-84309-C2-2-R from Ministerio de Ciencia e Innovación (Spain). The authors acknowledge the ESRF and the Ministerio de Ciencia, Innovación y Universidades (Spain), for provision of synchrotron radiation facilities and the Consejo Superior de Investigaciones Científicas (Spain) financial support for the operation of the beamline under Grant No. PIE 2010 6 OE 01