Análisis de la percepción de los riesgos naturales en la Universidad de Alicante

Los estudios sobre percepción de riesgos intentan analizar las relaciones afectivas y éticas que una comunidad establece con el ambiente en que vive. Las percepciones ambientales son entendidas como la forma en que cada persona aprecia y valora su entorno. El presente artículo tiene como objetivo analizar la percepción de riesgos naturales en los miembros de la comunidad académica de la Universidad de Alicante. Para evaluar la percepción se aplicaron encuestas. Han sido contestadas 80 encuestas, todas por medio electrónico. Los resultados indican que la percepción de las principales amenazas por fenómenos naturales son: las inundaciones, las sequías y los incendios forestales. Se concluye resaltando la importancia de trabajos que aporten información sobre la percepción ambiental, con el fin de hacer más eficiente la aplicación de políticas ambientales.

Public health lessons for refugee reception: the example of Sidi Bulgayz

Conflicts force millions of people to abandon their homes and flee life-threatening persecution, war, and ethnic and political discrimination. From the end of World War II to the present day, more than 59 million people worldwide have become refugees and displaced persons. Displacement affects people's health, psychological well-being and economic welfare.

Imaging Land Subsidence Induced by Groundwater Extraction in Beijing (China) Using Satellite Radar Interferometry

Beijing is one of the most water-stressed cities in the world. Due to over-exploitation of groundwater, the Beijing region has been suffering from land subsidence since 1935. In this study, the Small Baseline InSAR technique has been employed to process Envisat ASAR images acquired between 2003 and 2010 and TerraSAR-X stripmap images collected from 2010 to 2011 to investigate land subsidence in the Beijing region. The maximum subsidence is seen in the eastern part of Beijing with a rate greater than 100 mm/year. Comparisons between InSAR and GPS derived subsidence rates show an RMS difference of 2.94 mm/year with a mean of 2.41 ± 1.84 mm/year. In addition, a high correlation was observed between InSAR subsidence rate maps derived from two different datasets (i.e., Envisat and TerraSAR-X). These demonstrate once again that InSAR is a powerful tool for monitoring land subsidence. InSAR derived subsidence rate maps have allowed for a comprehensive spatio-temporal analysis to identify the main triggering factors of land subsidence. Some interesting relationships in terms of land subsidence were found with groundwater level, active faults, accumulated soft soil thickness and different aquifer types. Furthermore, a relationship with the distances to pumping wells was also recognized in this work.