Modeling of SAR signatures of shallow water ocean topography

A hydrodynamic/electromagnetic model was developed to explain and quantify the relationship between the SEASAT synthetic aperture radar (SAR) observed signatures and the bottom topography of the ocean in the English Channel region of the North Sea. The model uses environmental data and radar system parameters as inputs and predicts SAR-observed backscatter changes over topographic changes in the ocean floor. The model results compare favorably with the actual SEASAT SAR observed backscatter values. The developed model is valid for only relatively shallow water areas (i.e., less than 50 meters in depth) and suggests that for bottom features to be visible on SAR imagery, a moderate to high velocity current and a moderate wind must be present

Further SEASAT SAR coastal ocean wave analysis

Analysis techniques used to exploit SEASAT synthetic aperture radar (SAR) data of gravity waves are discussed and the SEASAT SAR's ability to monitor large scale variations in gravity wave fields in both deep and shallow water is evaluated. The SAR analysis techniques investigated included motion compensation adjustments and the semicausal model for spectral analysis of SAR wave data. It was determined that spectra generated from fast Fourier transform analysis (FFT) of SAR wave data were not significantly altered when either range telerotation adjustments or azimuth focus shifts were used during processing of the SAR signal histories, indicating that SEASAT imagery of gravity waves is not significantly improved or degraded by motion compensation adjustments. Evaluation of the semicausal (SC) model using SEASAT SAR data from Rev. 974 indicates that the SC spectral estimates were not significantly better than the FFT results

Highlighting biome-specific sensitivity of fire size distributions to time-gap parameter using a new algorithm for fire event individuation

Detailed spatial-temporal characterization of individual fire dynamics using remote sensing data is important to understand fire-environment relationships, to support landscape-scale fire risk management, and to obtain improved statistics on fire size distributions over broad areas. Previously, individuation of events to quantify fire size distributions has been performed with the flood-fill algorithm. A key parameter of such algorithms is the time-gap used to cluster spatially adjacent fire-affected pixels and declare them as belonging to the same event. Choice of a time-gap to define a fire event entails several assumptions affecting the degree of clustering/fragmentation of the individual events. We evaluate the impact of different time-gaps on the number, size and spatial distribution of active fire clusters, using a new algorithm. The information produced by this algorithm includes number, size, and ignition date of active fire clusters. The algorithm was tested at a global scale using active fire observations from the Moderate Resolution Imaging Spectroradiometer (MODIS). Active fire cluster size distributions were characterized with the Gini coefficient, and the impact of changing time-gap values was analyzed on a 0.5° cell grid. As expected, the number of active fire clusters decreased and their mean size increased with the time-gap value. The largest sensitivity of fire size distributions to time-gap was observed in African tropical savannas and, to a lesser extent, in South America, Southeast Asia, and eastern Siberia. Sensitivity of fire individuation, and thus Gini coefficient values, to time-gap demonstrate the difficulty of individuating fire events in tropical savannas, where coalescence of flame fronts with distinct ignition locations and dates is very common, and fire size distributions strongly depend on algorithm parameterization. Thus, caution should be exercised when attempting to individualize fire events, characterizing their size distributions, and addressing their management implications, particularly in the African savannas

Curso "Propiedad intelectual y servicios de información"

Sección: Noticias. Noticias internasEl pasado mes de octubre tuvo lugar en Madrid entre los días 17 y 19, el Curso “Propiedad intelectual y servicios de información”, organizado por la Unidad de Coordinación de Bibliotecas y el Gabinete de Formación del CSIC.N

Soil methane sink capacity response to a long-term wildfire chronosequence in Northern Sweden

Boreal forests occupy nearly one fifth of the terrestrial land surface and are recognised as globally important regulators of carbon (C) cycling and greenhouse gas emissions. Carbon sequestration processes in these forests include assimilation of CO2 into biomass and subsequently into soil organic matter, and soil microbial oxidation of methane (CH4). In this study we explored how ecosystem retrogression, which drives vegetation change, regulates the important process of soil CH4 oxidation in boreal forests. We measured soil CH4 oxidation processes on a group of 30 forested islands in northern Sweden differing greatly in fire history, and collectively representing a retrogressive chronosequence, spanning 5000 years. Across these islands the build-up of soil organic matter was observed to increase with time since fire disturbance, with a significant correlation between greater humus depth and increased net soil CH4 oxidation rates. We suggest that this increase in net CH4 oxidation rates, in the absence of disturbance, results as deeper humus stores accumulate and provide niches for methanotrophs to thrive. By using this gradient we have discovered important regulatory controls on the stability of soil CH4 oxidation processes that could not have not been explored through shorter-term experiments. Our findings indicate that in the absence of human interventions such as fire suppression, and with increased wildfire frequency, the globally important boreal CH4 sink could be diminished

In Vivo Imaging of Cerebral Energy Metabolism with Two-Photon Fluorescence Lifetime Microscopy of NADH

Minimally invasive, specific measurement of cellular energy metabolism is crucial for understanding cerebral pathophysiology. Here, we present high-resolution, in vivo observations of autofluorescence lifetime as a biomarker of cerebral energy metabolism in exposed rat cortices. We describe a customized two-photon imaging system with time correlated single photon counting detection and specialized software for modeling multiple-component fits of fluorescence decay and monitoring their transient behaviors. In vivo cerebral NADH fluorescence suggests the presence of four distinct components, which respond differently to brief periods of anoxia and likely indicate different enzymatic formulations. Individual components show potential as indicators of specific molecular pathways involved in oxidative metabolism