Evaluación de la cobertura de la vegetación después de un incendio mediante análisis de mezclas espectrales. Aplicación y comparación de diferentes métodos de caracterización de factores de referencia

The analysis of satellite images allows one to monitor the regeneration of vegetation after a fire. In this work, a methodology for quantifying post fire vegetation cover was developed. The proposed methodology is based on the examination of Landsat 7 ETM+ images by using Spectral Mixture Analysis (SMA) and involves the following steps: a) pre-processing, b) inherent dimensionality image determination c) endmember characterization following two methods that thus lead to different models: traditional method based on the knowledge of the area worked as well as Minimum Noise Fraction and Pixel Purity Index method, d) model inversion and combination, e) comparison between the vegetation cover estimated by each model and that measured in field, and f) selection of the most accurate model and mapping of the vegetation cover for the study area. The cover estimated provided by the different models exhibited a high correlation (Spearman’s correlation coefficient >0.89). The average absolute difference between the estimated and field-measured vegetation cover obtained with the most accurate model for each fire never exceeded 6%.El análisis de imágenes de satélite permite el seguimiento y evaluación de los procesos de restauración post-incendio. En este trabajo se presentan parte de los resultados de una metodología dirigida a la cuantificación de la cobertura de la vegetación después de un incendio. La metodología propuesta se basa en el empleo de imágenes Landsat 7 ETM+ mediante un Análisis de Mezclas Espectrales (SMA) y supone los siguientes procesos: a) pre-procesado de la imagen, b) determinación de la dimensión intrínseca (inherent dimensionality) de la imagen c) selección y caracterización de los factores de referencia (endmember) mediante dos métodos propuestos en la literatura: estudio previo de la zona de trabajo, Minimum Noise Fraction y pixles puros (Pixel Purity Index), d) inversión del modelo y combinación, e) comparación entre la cobertura estimada por cada modelos y las medidas realizadas en el campo, y f) selección del modelo de mayor precisión para la realización de una cartografía de la cobertura de la vegetación en el área de estudio. La cobertura estimada por los diferentes modelos muestran una alta correlación (Coeficiente de correlación de Spearman > 0.89), lo que ha permitido establecer una diferencia entre las medidas de cobertura a través de la imagen y la estimación de campo que en ningún caso han superado el 6% de la cobertura post-inendio

Implicit finite volume simulation of 2D shallow water flows in flexible meshes

In this work, an implicit method for solving 2D hyperbolic systems of equations is presented, focusing on the application to the 2D shallow water equations. It is based on the first order Roe''s scheme, in the framework of finite volume methods. A conservative linearization is done for the flux terms, leading to a non-structured matrix for unstructured meshes thus requiring iterative methods for solving the system. The validation is done by comparing numerical and exact solutions in both unsteady and steady cases. In order to test the applicability of the implicit scheme to real world situations, a laboratory scale tsunami simulation is carried out and compared to the experimental data. The implicit schemes have the advantage of the unconditional stability, but a quality loss in the transient solution can appear for high CFL numbers. The properties of the scheme are well suited for the simulation of unsteady shallow water flows over irregular topography using all kind of meshes

Implicit 2D surface flow models performance assessment: Shallow Water Equations vs. Zero-Inertia Model

Zero-Inertia (ZI) models are used in overland flow simulation due to their mathematical simplicity, compared to more complex formulations such as Shallow Water (SW) models. The main hypothesis in ZI models is that the flow is driven by water surface and friction gradients, neglecting local accelerations. On the other hand, SW models are a complete dynamical formulation that provide more information at the cost of a higher level of complexity. In realistic problems, the usually huge number of cells required to ensure accurate spatial representation implies a large amount of computing effort and time. This is particularly true in 2D models. Hence, there is an interest in developing efficient numerical methods. In general terms, numerical schemes used to solve time dependent problems can be classified in two groups, attending to the time evaluation of the unknowns: explicit and implicit methods. Explicit schemes offer the possibility to update the solution at every cell from the known values but are restricted by numerical stability reasons. This can lead to very slow simulations in case of using fine meshes. Implicit schemes avoid this restriction at the cost of generating a system of as many equations as computational cells multiplied by the number of variables to solve. In this work, an implicit finite volume numerical scheme has been used to solve the 2D equations in both ZI and SW models. The scheme is formulated so that both quadrilateral and triangular meshes can be used. A conservative linearization is done for the flux terms, leading to a non-structured matrix for unstructured meshes thus requiring iterative methods for solving the system. A comparison between 2D SW and 2D ZI is done in terms of performance, efficiency and mesh requirements, in which both models benefit of an implicit temporal discretization in steady and nearly-steady situations

A 2D finite volume simulation tool to enable the assessment of combined hydrological and morphodynamical processes in mountain catchments

Nowadays, the great power of modern computers allows to develop computational models able to deal with simulations of several coupled phenomena over detailed complex topography. An efficient and properly calibrated computational model represents a useful tool to provide insight into the catchment dynamics at hydrological and geomorphological levels. In addition, it allows to develop detailed risk management and conservation plans. In this work, we present a coupled surface-groundwater distributed flow model with hydrological (rainfall and infiltration) and geomorphological (suspended and bed load sediment transport) components. The coupled model is applied to well characterized experimental catchments that are used as realistic test cases. The calibration of the water flow model response to rainfall is performed by means of the fitting to experimental outlet hydrographs of the results supplied by a coupled formulation of 2D Shallow Water Equations and 2D Darcy's law for saturated porous media connected via suitable infiltration laws. The calibration of a suspended and bed load model is also addressed by means of the fitting to experimental outlet sedigraphs. The numerical results show a good agreement between numerical and observed hydrographs and sedigraphs, significantly improving previous published simulations. Additionally, the need to repeat the simulations in the calibration processes is no longer an unapproachable problem

Evolutionary q-Gaussian radial basis function neural networks for multiclassification

This paper proposes a radial basis function neural network (RBFNN), called the q-Gaussian RBFNN, that reproduces different radial basis functions (RBFs) by means of a real parameter q. The architecture, weights and node topology are learnt through a hybrid algorithm (HA). In order to test the overall performance, an experimental study with sixteen data sets taken from the UCI repository is presented. The q-Gaussian RBFNN was compared to RBFNNs with Gaussian, Cauchy and inverse multiquadratic RBFs in the hidden layer and to other probabilistic classifiers, including different RBFNN design methods, support vector machines (SVMs), a sparse classifier (sparse multinomial logistic regression, SMLR) and a non-sparse classifier (regularized multinomial logistic regression, RMLR). The results show that the q-Gaussian model can be considered very competitive with the other classification methods. © 2011 Elsevier Ltd

Benefits of a dance group intervention on institutionalized elder people: A Bayesian network approach

The present study aims to explore the effects of an adapted classical dance intervention on the psychological and functional status of institutionalized elder people using a Bayesian network. All participants were assessed at baseline and after the 9 weeks period of the intervention. Measures included balance and gait, psychological well-being, depression, and emotional distress. According to the Bayesian network obtained, the dance intervention increased the likelihood of presenting better psychological well-being, balance, and gait. Besides, it also decreased the probabilities of presenting emotional distress and depression. These findings demonstrate that dancing has functional and psychological benefits for institutionalized elder people. Moreover it highlights the importance of promoting serious leisure variety in the daily living of institutionalized elder adults

Ambivalence and innovative moments in grief psychotherapy: the cases of Emily and Rose

Several studies have suggested that the process of narrative change in psychotherapy occurs through the emergence and expansion of moments of novelty, known as innovative moments (IMs), that allow changes in the problematic self-narrative responsible for the client’s suffering. However, as these IMs challenge typical (and problematic) ways of acting, feeling, and thinking, they may also generate discrepancy or uncertainty. Clients may reduce uncertainty by returning to the problematic self-narrative immediately after the emergence of an IM, thus ensuring the homeostasis of the previous meaning system. This cyclical movement is a form of ambivalence, which can maintain problematic stability across therapy and lead to therapeutic failure. In this study, we identified return to the problem markers (RPMs), which are empirical indicators of the ambivalence process, for all IMs in two cases of constructivist grief psychotherapy. Both cases evidenced a high percentage of IMs with RPMs, and the evolution of IMs and RPMs along treatment was significantly correlated. We suggest that stability of the ambivalence process in grief psychotherapy may represent a form of self-protection from the anxiety or guilt of releasing pain as a disconnection from the deceased

A model for computing thermally-driven shallow flows

In many natural disasters such as overland oil spills or lava flows, physical fluid properties as density change when considering non-homogeneous spatial and time variable distributions of the temperature. This effect is even more remarkable when these flows show a non-Newtonian behaviour due to the sensitivity of their rheological properties as viscosity or yield stress to temperature. In these cases, temperature becomes a significant variable that drives the fluid behaviour, which must be solved using an energy equation coupled with the free surface flow system. Special attention is devoted to thermal source terms which must include all the heat fluid exchanges, and their modelling sometimes can govern the complete flow behaviour. Fluid density, viscosity and yield stress, also affected by temperature, must be recomputed every time step. Summarizing, this work presents a 2D free surface flow model considering density and temperature variations, which could even modify viscosity and yield stress, with heat transfer mechanisms. The model is applied to oil spill overland simulations and heating/cooling test cases are carried out to ensure the system energy balance. As conclusions, it can be said that the numerical results demonstrate the importance of the heat exchange effects and those of the density, viscosity and yield stress variations

Numerical simulation of valley flood using an implicit diffusion wave model

[EN] In this work, a diffusion wave overland flow model is presented for the efficient resolution of valley flood situations. The spatial discretization is done following an upwind finite volume scheme, applied in a non-structured triangular mesh. An implicit scheme is used for the temporal discretization, which involves the generation of a system of equations, one for each computational cell. The BiConjugate Gradient Stabilized (BiCGStab) method is used for the resolution of the system. The computational efficiency is measured by means of a CPU cost comparison between the explicit and implicit versions of the numerical scheme. In general, the diffusive model benefits from an implicit discretization becoming much more efficient than the explicit versión. Due to the non-linearity of the diffusive wave equation, larger time steps do not always imply shorter computational times. The optimal time step size must be identified in every new problem. The diffusive wave model has been applied to a valley flooding case proposed by the UK Environmental Agency in order to compare its performance with that provided by commercial models.[ES] En este trabajo se presenta un modelo difusivo de flujo superficial para la resolución eficiente de problemas de inundación de valles fluviales. La discretización espacial se realiza mediante un esquema upwind de volúmenes finitos, aplicado en una malla triangular no estructurada. Para la discretización temporal se ha empleado un esquema implícito, lo que conlleva la generación de un sistema de tantas ecuaciones como celdas de cálculo tenga la malla computacional. Para su resolución, se ha empleado el método del Gradiente Biconjugado Estabilizado (BiCGStab). La eficiencia computacional se mide realizando una comparación de tiempos de CPU de las versiones explícita e implícita del mismo esquema numérico aplicado al modelo de onda difusiva. El estudio demuestra que, en general, el modelo difusivo se beneficia de una discretización temporal implícita, aumentando su eficiencia en gran medida frente al uso de un esquema explícito. Debido al carácter no lineal de la ecuación difusiva, un paso de tiempo mayor no siempre garantiza un menor coste computacional y resulta necesario encontrar el paso de tiempo óptimo para cada problema. Se ha aplicado el modelo difusivo a un caso test de inundación de valle fluvial propuesto por la UK Environmetal Agency para evaluar su capacidad predictiva en relación a modelos comerciales. Por último, se han comparado los resultados de calado y nivel de agua proporcionados por el modelo propuesto con los generados por una formulación matemática basada en las ecuaciones completas de aguas poco profundas no encontrándose diferencias relevantes en el ejemplo analizado.El presente trabajo ha sido parcialmente financiado por el Gobierno de Aragón a través del Fondo Social Europeo.Fernández-Pato, J.; García-Navarro, P. (2016). Simulación numérica de inundación de valles fluviales mediante un modelo difusivo implícito. Ingeniería del Agua. 20(3):115-126. doi:10.4995/ia.2016.4548.SWORD115126203Burden, R.L., Faires, J.D. (2010). Numerical analysis. Brooks/Cole, Cengage Learning.Cea, L., Garrido, M. Puertas, J. (2010). Experimental validation of two-dimensional depth-averaged models for forecasting rainfallrunofffrom precipitation data in urban áreas. 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Diffusive-wave based hydrologic-hydraulic model with sediment transport I: model development. Journal of Hydrologic Engineering, 17(10), 1093-1104. doi:10.1061/(ASCE)HE.1943-5584.0000552Maguya, A.S., Junttila, V., Kauranne, T. (2013). Adaptive algorithm for large scale DTM interpolation from LIDAR data for forestry applications in steep forested terrain. ISPRS Journal of Photogrammetry and Remote Sensing, 85, 74-83. doi:10.1016/j.isprsjprs.2013.08.005Mahmood, K., Yevjevich, V. (1975). Unsteady flows in open channels. Water Resources Publications, Fort Collins, Colorado.Merwade, V., Cook, A., Coonrod, J. (2008). GIS techniques for creating river terrain models for hydrodynamic and flood inundation mapping. Environmental Modelling & Software, 23(10-11), 1300-1311. doi:10.1016/j.envsoft.2008.03.005Moussa, R., Bocquillon, C. (2009). On the use of the diffusive wave modelling extreme flood events with overbank flow in floodplain. Journal of Hydrology, 374(1-2), 116-135. doi:10.1016/j.jhydrol.2009.06.006Mui, A., He, Y, Weng, Q. (2015). An object-based approach to delineate wetlands across landscapes of varied disturbance with high spatial resolution satellite imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 109, 30-46. doi:10.1016/j.isprsjprs.2015.08.005Murillo, J., García-Navarro, P. (2010). Weak solutions for partial differential equations with source terms: Application to the shallow water equations. Journal of Computational Physics, 229(11), 4327-4368. doi:10.1016/j.jcp.2010.02.016Neal, J., Villanueva, I., Wright, N. Willis, T. Fewtrell, T., Bates, P. (2012). How much physical complexity is needed to model flood inundation? Hydrological Processes, 26(15), 2264-2282. doi:10.1002/hyp.8339Néelz, S., Pender, G. (2013). Benchmarking of 2D hydraulic modelling packages. UK Environmental Agency.Gomez-Pereira, L.M., Wicherson, R.J. (1999). 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The shallow water equations and their application to realistic cases

The numerical modelling of 2D shallow flows in complex geometries involving transient flow and movable boundaries has been a challenge for researchers in recent years. There is a wide range of physical situations of environmental interest, such as flow in open channels and rivers, tsunami and flood modelling, that can be mathematically represented by first-order non-linear systems of partial differential equations, whose derivation involves an assumption of the shallow water type. Shallow water models may include more sophisticated terms when applied to cases of not pure water floods, such as mud/debris floods, produced by landslides. Mud/debris floods are unsteady flow phenomena in which the flow changes rapidly, and the properties of the moving fluid mixture include stop and go mechanisms. The present work reports on a numerical model able to solve the 2D shallow water equations even including bed load transport over erodible bed in realistic situations involving transient flow and movable flow boundaries. The novelty is that it offers accurate and stable results in realistic problems since an appropriate discretization of the governing equations is performed. Furthermore, the present work is focused on the importance of the computational cost. Usually, the main drawback is the high computational effort required for obtaining accurate numerical solutions due to the high number of cells involved in realistic cases. However, the proposed model is able to reduce computer times by orders of magnitude making 2D applications competitive and practical for operational flood prediction. Moreover our results show that high performance code development can take advantage of general purpose and inexpensive Graphical Processing Units, allowing to run almost 100 times faster than old generation codes in some cases