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Barraza V.,Institute of Astronomy and Space Physics IAFE | Grings F.,Institute of Astronomy and Space Physics IAFE | Ferrazzoli P.,University of Rome Tor Vergata | Huete A.,University of Technology, Sydney | And 4 more authors.
Journal of Geophysical Research G: Biogeosciences | Year: 2014

This study focused on the time series analysis of passive microwave and optical satellite data collected from six Southern Hemisphere ecosystems in Australia and Argentina. The selected ecosystems represent a wide range of land cover types, including deciduous open forest, temperate forest, tropical and semiarid savannas, and grasslands. We used two microwave indices, the frequency index (FI) and polarization index (PI), to assess the relative contributions of soil and vegetation properties (moisture and structure) to the observations. Optical-based satellite vegetation products from the Moderate Resolution Imaging Spectroradiometer were also included to aid in the analysis. We studied the X and Ka bands of the Advanced Microwave Scanning Radiometer-EOS and Wind Satellite, resulting in up to four observations per day (1:30, 6:00, 13:30, and 18:00-h). Both the seasonal and hourly variations of each of the indices were examined. Environmental drivers (precipitation and temperature) and eddy covariance measurements (gross ecosystem productivity and latent energy) were also analyzed. It was found that in moderately dense forests, FI was dependent on canopy properties (leaf area index and vegetation moisture). In tropical woody savannas, a significant regression (R2) was found between FI and PI with precipitation (R2->-0.5) and soil moisture (R2->-0.6). In the areas of semiarid savanna and grassland ecosystems, FI variations found to be significantly related to soil moisture (R2->-0.7) and evapotranspiration (R2->-0.5), while PI varied with vegetation phenology. Significant differences (p-<-0.01) were found among FI values calculated at the four local times. Key Points Passive microwave indices can be used to estimate vegetation moisture Microwave observations were supported by flux data Passive microwave indices could be used to estimate evapotranspiration ©2014. American Geophysical Union. All Rights Reserved.


Castelletti G.,Institute of Astronomy and Space Physics IAFE | Joshi B.C.,National Center for Radio Astrophysics | Surnis M.P.,National Center for Radio Astrophysics | Supan L.,Institute of Astronomy and Space Physics IAFE | Dubner G.,Institute of Astronomy and Space Physics IAFE
Proceedings of the International Astronomical Union | Year: 2014

We report here on the first dedicated simultaneous imaging and pulsar observations towards the supernova remnant (SNR) G15.4+0.1, the possible counterpart of the very high energy (VHE) source HESS J1818-154. The observations were carried out using the Giant Metrewave Radio Telescope (GMRT) at 610 and 1400 MHz. Preliminary analysis of data suggests absence of pulsations towards the centroid of HESS J1818-154, with upper limits of 0.6 and 0.3 mJy at 610 and 1400 MHz, respectively. Analysis of data with a larger beam is in progress, which may confirm the presence of a putative pulsar and its wind nebula if it is offset from the centroid of HESS J1818-154. © International Astronomical Union 2014.


Vittucci C.,University of Rome Tor Vergata | Guerriero L.,University of Rome Tor Vergata | Ferrazzoli P.,University of Rome Tor Vergata | Rahmoune R.,University of Rome Tor Vergata | And 2 more authors.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing | Year: 2014

The aim of this work is to investigate the exploitation of radiometric acquisitions from satellite sensors at different microwave frequencies in view of the prediction of river water level. A case study has been identified in the Bermejo basin, in northern Argentina. This river is seasonally affected by severe flooding events in the lower part, mostly due to rains occurring in the upper basin, that produce sediment loadings flushing down along the lower basin thus changing the watercourse. While the effectiveness of microwave radiometry at Ka band for flood monitoring is consolidated in the literature, this study also considers X and C bands (provided by the Advanced Microwave Scanning Radiometer (AMSR) series together with the higher frequency) and highlights the better sensitivity to soil conditions of L band data (made recently available, thanks to SMOS) over moderately and densely vegetated areas. This study confirms, first, the well-known capability of passive microwave remote sensing instruments to record brightness temperature variations due to rainfall and floods occurred near river edges under different seasonal conditions. For this purpose, a multifrequency comparative analysis is conducted. Second, it investigates whether these properties can be exploited for flood forecasting: a model which directly links the daily satellite measurements to the river water level has been tested, considering 1- to 7-day forecast horizons. The results show that forecasting models can take advantage of the sensitivity of low frequencies to soil moisture conditions in order to predict flood peaks, despite the instrument's low resolutions. © 2008-2012 IEEE.


Barraza V.,Institute of Astronomy and Space Physics IAFE | Grings F.,Institute of Astronomy and Space Physics IAFE | Ferrazzoli P.,University of Rome Tor Vergata | Salvia M.,Institute of Astronomy and Space Physics IAFE | And 4 more authors.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing | Year: 2014

Information about daily variations of vegetation moisture is of widespread interest to monitor vegetation stress and as a proxy to evapotranspiration. In this context, we evaluated optical and passive microwave remote sensing indices for estimating vegetation moisture content in the Dry Chaco Forest, Argentina. The three optical indices analyzed were the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Water Index (NDWI) and the Normalized Difference Infrared Index (NDII) and, for the microwave region the Frequency Index (FI). All these indices are mainly sensitive to leaf area index (LAI), but NDWI and NDII, and FI are also sensitive to leaf water content (LWC) and Canopy Water Content (CWC) respectively. Using optical and microwave radiative transfer models for the vegetation canopy, we estimated the range of values of LAI, LWC and CWC that can explain both NDWI/NDII and FI observations. Using a combination of simulations and microwave and optical observations, we proposed a two step approach to estimate leaf and canopy moisture content from NDWI, NDII and FI. We found that the short variation of LWC estimated from NDWI and NDII present a dynamic range of values which is difficult to explain from the biophysical point of view, and it is partially related to atmosphere contamination and canopy radiative transfer model limitations. Furthermore, the observed FI short-term variations ($\sim$8 days) cannot be explained unless significant CWC variations are assumed. The CWC values estimated from FI present a short-term variations possibly related to vegetation hydric stress. © 2008-2012 IEEE.


Bruscantini C.A.,Institute of Astronomy and Space Physics IAFE | Maas M.,Institute of Astronomy and Space Physics IAFE | Grings F.,Institute of Astronomy and Space Physics IAFE | Karszenbaum H.,Institute of Astronomy and Space Physics IAFE
13th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment, MicroRad 2014 - Proceedings | Year: 2014

The Microwave Radiometer (MWR) on board the SACD/Aquarius mission, launched on June 2011, is a Dicke radiometer operating at 23.8 GHz (H-Pol) and 36.5 GHz (H/V/45-Pol). MWR channels are useful to provide ancillary data for the various retrievals to be performed with Aquarius regarding ocean and land applications. In this study we report the calibration results obtained by a land cross-calibration between Windsat and MWR. Results were generated for the 2011-2012 period and using the version V5.0S of the MWR data. Radiometer inter-comparison over selected homogeneous targets is widely used for calibration assessment and data quality evaluation. The methodology lays on the temporal stability of the selected targets and their homogeneity in terms of brightness temperature (Tb), so that radiometers with similar characteristics (frequency, polarization, incidence angle) should observe the same Tb when passing over the target within a short temporal window. Differences on observed Tbs are associated to a poor calibration of the instrument under study. The cross-calibration is an adjustment of the Tb data of the radiometer under study to match the Tb data of the already calibrated radiometer. In this study, linear adjustments are applied for each MWR beams of its three channels to match Windsat observations. In order to examine the entire dynamic range of land observations, 19 homogeneous targets were selected for cross-calibration. These targets have been previously selected for quality assessment of AMSR-E data [1]. Targets include tropical and boreal forests, desert, grassland and Sahel. Overall, it was found that the instrument compares favorably toWindsat over land targets. Nevertheless, certain issues to be resolved are identified and corrections are proposed. © 2014 IEEE.


Bruscantini C.A.,Institute of Astronomy and Space Physics IAFE | Grings F.,Institute of Astronomy and Space Physics IAFE | Barber M.,Institute of Astronomy and Space Physics IAFE | Perna P.,Institute of Astronomy and Space Physics IAFE | Karszenbaum H.,Institute of Astronomy and Space Physics IAFE
13th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment, MicroRad 2014 - Proceedings | Year: 2014

In this work, several retrieval algorithms were implemented to retrieve soil moisture (sm) and optical depth (τ) from Aquarius/SAC-D observations. Currently used sm retrieval algorithms (H- and V-pol Single Channel Algorithm, SCAH and SCAV; Microwave Polarization Difference Algorithm, MPDA) were computed over Pampas Plains, Argentina. The methodology of a novel Bayesian algorithm developed is also presented, and its results are contrasted with the previous algorithms. Finally, performance metrics for each algorithms were derived using SMOS Level-2 sm and τ as benchmark products. The new Bayesian approach provide the sm retrieval algorithm that exhibited the lowest ubRMSE (0.115m 3/m3), though very close to USDA SCA and SCAV ubRMSE (0.116m3/m3). Nevertheless, some improvements are discussed in Section 4 that might increase significantly the Bayesian algorithm performance. © 2014 IEEE.

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