Suchergebnisse

The covid-19 pandemic has not only affected health and education; it has also caused a serious economic crisis as a result of the closure of companies and businesses in all sectors. Confinement and mobility restrictions, measures taken by the Government to reduce social contact and the spread of the virus, are a matter of concern for entrepreneurs, wage earners and independent workers, given the deterioration of businesses, the loss of capital and jobs, the uncertainty regarding projected investments and the reduced cash flow. Together, these factors make many companies unsustainable over time, which poses an uncertain outlook for the country. ; La pandemia del covid-19 no solo ha afectado la salud y la educación; también ha ocasionado una grave crisis económica como resultado del cierre de empresas y negocios de todos los sectores. El confinamiento y las restricciones de movilidad, medidas tomadas por el Gobierno para disminuir el contacto social y la propagación del virus, son motivo de preocupación para empresarios, asalariados y trabajadores independientes, ante el deterioro de los negocios, la pérdida de capitales y empleos, la incertidumbre respecto de las inversiones proyectadas y la reducción del flujo de caja. Sumados, estos factores hacen que muchas empresas sean insostenibles en el tiempo, lo que plantea un panorama incierto para el país

Land Surface Temperature (LST) is one of the key inputs for Soil-Vegetation-Atmosphere transfer modeling in terrestrial ecosystems. In the frame of BIOSPEC (Linking spectral information at different spatial scales with biophysical parameters of Mediterranean vegetation in the context of global change) and FLUXPEC (Monitoring changes in water and carbon fluxes from remote and proximal sensing in Mediterranean "dehesa" ecosystem) projects LST retrieved from Landsat data is required to integrate ground-based observations of energy, water, and carbon fluxes with multi-scale remotely-sensed data and assess water and carbon balance in ecologically fragile heterogeneous ecosystem of Mediterranean wooded grassland (dehesa). Thus, three methods based on the Radiative Transfer Equation were used to extract LST from a series of 2009–2011 Landsat-5 TM images to assess the applicability for temperature input generation to a Landsat-MODIS LST integration. When compared to surface temperatures simulated using MODerate resolution atmospheric TRANsmission 5 (MODTRAN 5) with atmospheric profiles inputs (LSTref), values from Single-Channel (SC) algorithm are the closest (root-mean-square deviation (RMSD) = 0.50 °C); procedure based on the online Radiative Transfer Equation Atmospheric Correction Parameters Calculator (RTE-ACPC) shows RMSD = 0.85 °C; Mono-Window algorithm (MW) presents the highest RMSD (2.34 °C) with systematical LST underestimation (bias = 1.81 °C). Differences between Landsat-retrieved LST and MODIS LST are in the range of 2 to 4 °C and can be explained mainly by differences in observation geometry, emissivity, and time mismatch between Landsat and MODIS overpasses. There is a seasonal bias in Landsat-MODIS LST differences due to greater variations in surface emissivity and thermal contrasts between landcover components. ; This research has been financially supported by the BIOSPEC project ―Linking spectral information at different spatial scales with biophysical parameters of Mediterranean vegetation in the context of Global Change‖ [28] (CGL2008-02301/CLI, Ministry of Science and Innovation, Spain), the FLUXPEC project ―Monitoring changes in water and carbon fluxes from remote and proximal sensing in a Mediterranean dehesa ecosystem‖ [29] (CGL2012-34383, Ministry of Economy and Competitiveness, Spain), and by a collaboration agreement between the Aragón Government and the Obra Social ―La Caixa‖ (DGA-La Caixa, GA-LC-042/2011), Spain ; We acknowledge support by the CSIC Open Access Publication Initiative through its Unit of Information Resources for Research (URICI). ; Peer reviewed