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Galicia is a region in NW Spain which is usually affected by a high number of forest fires, and it should meet the current regulations regarding the distance between forests and buildings. This paper aims to identify and characterize woodlands and classify buildings according to their fire risk, for a 36 km2 area in Forcarei (Pontevedra, Spain). We used LiDAR data to generate three spatial models (DTM: Digital Terrain Model, DSM: Digital Surface Model and nDSM: Normalized Digital Surface Model) and two statistics to characterize the forest stands (density of dominant trees per hectare and their average height). The identification of forested areas was performed using an object-based classification method using the intensity image, the height model and an orthophotograph of the area, and a kappa coefficient of 0.82 was obtained in the validation. The woodlands were reclassified according to the magnitude of a possible fire, based on the density and the average height of the woodlands. The forest stands were mapped according to the magnitude of a possible fire and it was found that 1.18 km2 would be susceptible to a low magnitude fire, 3.75 km2 to a medium magnitude fire and 2.25 km2 to a fire of a high magnitude. Afterwards, it was determined whether the buildings in the area complied with the legislation relating to minimum distance from the forested areas (30 meters). For those that did not meet this distance, the risk of damage in case of a wildfire was calculated. The result was that 43.01% of buildings in the area complied with the regulations, 9.95% were located in a very low risk area, 25.74% in a low risk location, 12.37% in a medium risk area and 8.93% were in a high or very high risk area.

Objetivo: Conocer el grado de seguimiento de las recomendaciones en prevención secundaria cerebrovascular en atención primaria e identificar factores asociados. Diseño: Transversal multicéntrico. Emplazamiento: Centros de salud de atención primaria de un área metropolitana (944.280 habitantes). Participantes: Pacientes mayores de 18 años con diagnóstico de enfermedad cerebrovascular antes de 6 meses del estudio. Mediciones principales: Extracción de historia clínica informatizada de variables demográficas, factores de riesgo y comorbilidad cardiovascular, fármacos, valores de presión arterial (PA), colesterol LDL y visitas por medicina y enfermería posteriores al episodio. Se consideró buen control: PA