Balaguer Beser, Ángel Antonio

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Balaguer Beser
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Ángel Antonio
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Now showing 1 - 3 of 3
  • Publication
    Empirical Models for Spatio-Temporal Live Fuel Moisture Content Estimation in Mixed Mediterranean Vegetation Areas Using Sentinel-2 Indices and Meteorological Data
    (MDPI AG, 2021-09) Costa-Saura, José M.; Balaguer Beser, Ángel Antonio; Ruiz Fernández, Luis Ángel; Pardo Pascual, Josep Eliseu; Soriano-Sancho, José L.; Dpto. de Matemática Aplicada; Dpto. de Ingeniería Cartográfica Geodesia y Fotogrametría; Escuela Técnica Superior de Ingeniería Geodésica, Cartográfica y Topográfica; Grupo de Cartografía Geoambiental y Teledetección; Generalitat Valenciana
    [EN] Live fuel moisture content (LFMC) is an input factor in fire behavior simulation models highly contributing to fire ignition and propagation. Developing models capable of accurately estimating spatio-temporal changes of LFMC in different forest species is needed for wildfire risk assessment. In this paper, an empirical model based on multivariate linear regression was constructed for the forest cover classified as shrublands in the central part of the Valencian region in the Eastern Mediterranean of Spain in the fire season. A sample of 15 non-monospecific shrubland sites was used to obtain a spatial representation of this type of forest cover in that area. A prediction model was created by combining spectral indices and meteorological variables. This study demonstrates that the Normalized Difference Moisture Index (NDMI) extracted from Sentinel-2 images and meteorological variables (mean surface temperature and mean wind speed) are a promising combination to derive cost-effective LFMC estimation models. The relationships between LFMC and spectral indices for all sites improved after using an additive site-specific index based on satellite information, reaching a R-adj(2) = 0.70, RMSE = 8.13%, and MAE = 6.33% when predicting the average of LFMC weighted by the canopy cover fraction of each species of all shrub species present in each sampling plot.
  • Publication
    Modelos empíricos de predicción del contenido de humedad del combustible vivo mediante índices espectrales de Sentinel-2 y datos meteorológicos
    (Editorial Universitat Politècnica de València, 2021-10-01) Arcos, María; Balaguer Beser, Ángel Antonio; Ruiz Fernández, Luis Ángel; Dpto. de Matemática Aplicada; Dpto. de Ingeniería Cartográfica Geodesia y Fotogrametría; Escuela Técnica Superior de Ingeniería Geodésica, Cartográfica y Topográfica; Grupo de Cartografía Geoambiental y Teledetección; Universitat Politècnica de València
    [EN] The water content of the vegetation affects the flammability of the vegetation and fire behavior. A standard measure of this parameter is the live fuel moisture content (LFMC), calculated as the percentage of humidity of the vegetation relative to its dry weight. The aim of this work was to predict LFMC values of Rosmarinus officinalis in forest areas of the Valencian Community (Spain) using spectral indices obtained from Sentinel-2 satellite images and meteorological data. For this, LFMC values of this species were obtained from field samples collected biweekly from June to October in years 2019 and 2020 in three forest plots in the province of Valencia (Spain). The meteorological data (precipitation, temperature, relative humidity and wind speed) were obtained from observatories of the State Meteorological Agency (AEMET) of Spain. Multiple linear regression models were applied to estimate LFMC, using as predictor variables different spectral indices generated from Sentinel-2 images, calculated using Google Earth Engine and R programming. The results obtained using smoothed spectral data with the Savitzky-Golay filter were compared with data without such smoothing, also considering the differential contribution of the meteorological variables in each of the interpolated dates for each plot with data from the study area.
  • Publication
    Analyzing Independent LFMC Empirical Models in the Mid-Mediterranean Region of Spain Attending to Vegetation Types and Bioclimatic Zones
    (MDPI AG, 2023-07) Arcos-Villacís, María Alicia; Edo-Botella, Roberto; Balaguer Beser, Ángel Antonio; Ruiz Fernández, Luis Ángel; Dpto. de Matemática Aplicada; Dpto. de Ingeniería Cartográfica Geodesia y Fotogrametría; Escuela Técnica Superior de Ingeniería Geodésica, Cartográfica y Topográfica; Grupo de Cartografía Geoambiental y Teledetección; European Social Fund; AGENCIA ESTATAL DE INVESTIGACION; RED ELECTRICA DE ESPAÑA, S.A.U.; UNIVERSIDAD POLITECNICA DE VALENCIA
    [EN] This paper presents empirical models developed through stepwise multiple linear regression to estimate the live fuel moisture content (LFMC) in a Mediterranean area. The models are based on LFMC data measured in 50 field plots, considering four groups with similar bioclimatic characteristics and vegetation types (trees and shrubs). We also applied a species-specific LFMC model for Rosmarinus officinalis in plots with this dominant species. Spectral indices extracted from Sentinel-2 images and their averages over the study time period in each plot with a spatial resolution of 10 m were used as predictors, together with interpolated meteorological, topographic, and seasonal variables. The models achieved adjusted R2 values ranging between 52.1% and 74.4%. Spatial and temporal variations of LFMC in shrub areas were represented on a map. The results highlight the feasibility of developing satellite-derived LFMC operational empirical models in areas with various vegetation types and taking into account bioclimatic zones. The adjustment of data through GAM (generalized additive models) is also addressed in this study. The different error metrics obtained reflect that these models provided a better fit (most adjusted R2 values ranged between 65% and 74.1%) than the linear models, due to GAMs being more versatile and suitable for addressing complex problems such as LFMC behavior.