Aplicación del análisis de componentes principales para representar datos usando la información de índices espectrales

En este artículo se muestra el proceso de obtención de las componentes principales usando el programa Statgraphics Centurion XVIII y el software estadístico R. Para ello se usan datos reales de índices espectrales obtenidos a través de los satélites Sentinel-2, en una zona forestal en la provincia de Valencia (España). Se aplican dos métodos para determinar el número óptimo de componentes principales y se analiza el significado de las componentes seleccionadas. También se describen distintos usos de las componentes principales, viendo las ventajas de sustituir las variables originales por las componentes principales, la cuales son combinación lineal de las primeras y están incorreladas.Balaguer Beser, ÁA.; Arcos Villacís, MA. (2023). Aplicación del análisis de componentes principales para representar datos usando la información de índices espectrales. http://hdl.handle.net/10251/19397

Analyzing Independent LFMC Empirical Models in the Mid-Mediterranean Region of Spain Attending to Vegetation Types and Bioclimatic Zones

[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.Ma Alicia Arcos gives thanks for the help received by the Universitat Politecnica de Valencia through a pre-doctoral contract financed in the call, PAID-01-19, subprogram 1. This research was funded by through a collaboration agreement between the company Red Electrica de Espana S.A.U. and the Universitat Politecnica de Valencia (2020-2023), as well as the research project PID2020-117808RB-C21 funded by MCIN/AEI/10.13039/501100011033 and by ESF Investing in your future.Arcos-Villacís, MA.; Edo-Botella, R.; Balaguer-Beser, Á.; Ruiz Fernández, LÁ. (2023). Analyzing Independent LFMC Empirical Models in the Mid-Mediterranean Region of Spain Attending to Vegetation Types and Bioclimatic Zones. Forests. 14(7):1-26. https://doi.org/10.3390/f1407129912614