809 research outputs found

    First results of a GNSS-R experiment from a stratospheric balloon over boreal forests

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    The empirical results of a global navigation satellite systems reflectometry (GNSS-R) experiment onboard the Balloon EXperiments for University Students (BEXUS) 17 stratospheric balloon performed north of Sweden over boreal forests show that the power of the reflected signals is nearly independent of the platform height for a high coherent integration time T-c = 20 ms. This experimental evidence shows a strong coherent component in the forward scattered signal, as compared with the incoherent component, that allows to be tracked. The bistatic coherent reflectivity is also evaluated as a function of the elevation angle, showing a decrease of similar to 6 dB when the elevation angle increases from 35. to 70 degrees. The received power presents a clearly multimodal behavior, which also suggests that the coherent scattering component may be taking place in different forest elements, i.e., soil, canopy, and through multiple reflections canopy-soil and soil-trunk. This experiment has provided the first GNSS-R data set over boreal forests. The evaluation of these results can be useful for the feasibility study of this technique to perform biomass monitoring that is a key factor to analyze the carbon cycle.Peer ReviewedPostprint (author's final draft

    Contribution to the application of near ground L-band radiometry

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    Premi HEMAV 2019 al millor TFGARIEL is an L-band radiometer adapted from Earth Observation satellite technology for use in terrestrial, near to ground surveys of moisture. The key technical benefits are compact size, lightweight, mobility and high pixel density (up to 1m2). This project demonstrates the capability of high spatial and temporal resolution L-Band radiometry to produce detailed soil moisture contour maps within a 1 km2 area. The study was performed prior, during and after 12 mm of rainfall to determine the soil surface absorption and adsorption behaviour in relation to surface moisture. The radiometer was equipped with photodiodes to enable the normalised difference vegetation index (NDVI) data to be extracted concurrently. Hence this is a very near ground, high resolution and high precision study of soil moisture derived from L-band emissivity. 
 The project is focused on the technology application and production of useful products in the form of moisture contour maps and vegetation detection. The radiometer functioned admirably during the consecutive test campaigns and in conditions that varied from direct sun to rain and mud. Patterns of soil moisture over time and within specific sub-areas of the field are identified and quantified. The intra-field differences appear to primarily be related to soil type and soil surface characteristics which were qualitatively assessed in this study as quantified approaches are available in empirical and theoretical studies. Average field moistures are measured daily and differentiation is made between soil types within the field. The effect of dry and moist surface emissivity on retrieved moisture is noted, as is the effect of vegetation on soil surface emissivity with the aid of the vegetation index. Comparisons are drawn to the highest resolution satellite imagery (30 m spatial, 3 day temporal) and highlight the limitations and richness of local data that is missed in relation to local soil moisture surface absorption patterns during rainfall. The radiometer is shown to achieve very high resolution and precision that is not possible from satellite or even light aircraft. Furthermore, it is shown to be able to study ground conditions when they are occluded from satellite and hence the moisture profile maps presented are unique in their detail.Award-winnin

    Study of multifrequency sensitivity to soil moisture variations in the lower Bermejo basin

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    In this paper, a sensitivity analysis to soil moisture variations as a rain effect has been performed at several microwave bands over the lower Bermejo basin, a subtropical area of Argentina mostly spread by moderately dense forests. Parameters such as emissivity and Polarization Index have been considered to carry out the study. In particular, the performance of L-band SMOS measurements has been compared with C and X band AMSR-E one, highlighting the better achievement of the lower frequencies due to the weaker interaction with the vegetation structures. This work intends to give a contribution in the subject of soil moisture sensitivity, which is a preliminary step in the development of retrieval algorithms.Fil: Vittucci, Cristina. Universita Tor Vergata. Centro Interdipartimentale Vito Volterra; ItaliaFil: Guerriero, Leila. Universita Tor Vergata. Centro Interdipartimentale Vito Volterra; ItaliaFil: Ferrazzoli, Paolo. Universita Tor Vergata. Centro Interdipartimentale Vito Volterra; ItaliaFil: Rahmoune, Rachid. Universita Tor Vergata. Centro Interdipartimentale Vito Volterra; ItaliaFil: Barraza Bernadas, Verónica Daniela. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; ArgentinaFil: Grings, Francisco Matias. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; Argentin

    Sensitivity of GNSS-R spaceborne observations to soil moisture and vegetation

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    Global navigation satellite systems-reflectometry (GNSS-R) is an emerging remote sensing technique that makes use of navigation signals as signals of opportunity in a multistatic radar configuration, with as many transmitters as navigation satellites are in view. GNSS-R sensitivity to soil moisture has already been proven from ground-based and airborne experiments, but studies using space-borne data are still preliminary due to the limited amount of data, collocation, footprint heterogeneity, etc. This study presents a sensitivity study of TechDemoSat-1 GNSS-R data to soil moisture over different types of surfaces (i.e., vegetation covers) and for a wide range of soil moisture and normalized difference vegetation index (NDVI) values. Despite the scattering in the data, which can be largely attributed to the delay-Doppler maps peak variance, the temporal and spatial (footprint size) collocation mismatch with the SMOS soil moisture, and MODIS NDVI vegetation data, and land use data, experimental results for low NDVI values show a large sensitivity to soil moisture and a relatively good Pearson correlation coefficient. As the vegetation cover increases (NDVI increases) the reflectivity, the sensitivity to soil moisture and the Pearson correlation coefficient decreases, but it is still significant.Postprint (author's final draft

    Radar measurement of soil moisture content

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    The effect of soil moisture on the radar backscattering coefficient was investigated by measuring the 4-8 GHz spectral response from two types of bare-soil fields: slightly rough and very rough, in terms of the wavelength. An FM-CW radar system was used to measure the return at 10 frequency points across the 4-8 GHz band, at different look angles, and for all polarization combinations. The results indicate that the radar response to soil moisture content is highly dependent on the surface roughness, microwave frequency, and look angle. The response seems to be linear over the range 15%-30% moisture content for all angles, frequencies, polarizations and surface conditions

    Managing Water in Agriculture through Remote Sensing Applications

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    The climatic factors and their variability, both spatial and temporal, linked to precipita-tion decreasing and irregular distribution, due to climatic changes, have been gathering a higher weight in the definition of water management policies. These policies have important implications on agriculture. Using new technologies that allow a better use of water requires institutional changes in major areas. The first point is the need for base information with an adequate spatial and temporal resolution. The work we have done includes itself in the water efficient and sustained use, allowing the improvement of irrigation systems and it’s the result of a jointly effort of several teams based on an international project. The PLEIADES Project - Participatory multi-Level EO-assisted tools for Irrigation water management: and Agricultural Decision - Support, falls in the 6th Framework Programme, Priority 6 - Sustainable Development, Global Change and Ecosystems – CEC - Research Directorate-General-Integrating and Strengthening the European Research Area. The Portuguese working area was the Caia irrigation area, a subsystem of Guadiana basin, located in the southeast of Portugal, near the border with Spain. The system praised by PLEIADES stands mainly over FAO normative, about culture water needs and the calculation of cultural coefficient (Kc) in a simple way, directly from remote sensing data. For that we simply use radiometric pa-rameters derived from visible and infrared bands.info:eu-repo/semantics/publishedVersio

    Survey of methods for soil moisture determination

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    Existing and proposed methods for soil moisture determination are discussed. These include: (1) in situ investigations including gravimetric, nuclear, and electromagnetic techniques; (2) remote sensing approaches that use the reflected solar, thermal infrared, and microwave portions of the electromagnetic spectrum; and (3) soil physics models that track the behavior of water in the soil in response to meteorological inputs (precipitation) and demands (evapotranspiration). The capacities of these approaches to satisfy various user needs for soil moisture information vary from application to application, but a conceptual scheme for merging these approaches into integrated systems to provide soil moisture information is proposed that has the potential for meeting various application requirements

    An artificial neural network approach for soil moisture retrieval using passive microwave data

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    Soil moisture is a key variable that defines land surface-atmosphere (boundary layer) interactions, by contributing directly to the surface energy and water balance. Soil moisture values derived from remote sensing platforms only accounts for the near surface soil layers, generally the top 5cm. Passive microwave data at L-band (1.4 GHz, 21cm wavelength) measurements are shown to be a very effective observation for surface soil moisture retrieval. The first space-borne L-band mission dedicated to observing soil moisture, the European Space Agency's (ESA) Soil Moisture and Ocean Salinity (SMOS) mission, was launched on 2nd November 2009.Artificial Neural Network (ANN) methods have been used to empirically ascertain the complex statistical relationship between soil moisture and brightness temperature in the presence of vegetation cover. The current problem faced by this method is its inability to predict soil moisture values that are 'out-of-range' of the training data.In this research, an optimization model is developed for the Backpropagation Neural Network model. This optimization model utilizes the combination of the mean and standard deviation of the soil moisture values, together with the prediction process at different pre-determined, equal size regions to cope with the spatial and temporal variation of soil moisture values. This optimized model coupled with an ANN of optimum architecture, in terms of inputs and the number of neurons in the hidden layers, is developed to predict scale-to-scale and downscaling of soil moisture values. The dependency on the accuracy of the mean and standard deviation values of soil moisture data is also studied in this research by simulating the soil moisture values using a multiple regression model. This model obtains very encouraging results for these research problems.The data used to develop and evaluate the model in this research has been obtained from the National Airborne Field Experiments in 2005
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