Search results for "Radar backscattering"

showing 4 items of 4 documents

A semi-empirical approach for surface soil water content estimation from radar data without a-priori information on surface roughness

2006

Abstract In this study, the spatial distribution of soil water content in an agricultural area of 30 km 2 in Southern Italy has been estimated by using high-resolution space-borne Synthetic Aperture Radar data. Multi-polarised SAR images acquired during the SIR-C mission in April 1994 have been analysed by using the semi-empirical surface backscattering model derived by Oh, Y., Sarabandi K., Ulaby F.T., 1992. An empirical model and an inversion technique for radar scattering from bare soil surface. IEEE Trans. Geosci. Remote Sensing, 30(2), 370381. A site-specific calibration procedure of the cited model has been proposed to derive soil dielectric constant values without a-priori informatio…

Synthetic aperture radarHydrological modellingRadar backscatteringSurface finishSoil water contentlaw.inventionlawSoil waterSurface roughnessSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliEnvironmental scienceSpatial variabilityHydrological modelRadarWater contentWater Science and TechnologyRemote sensingJournal of Hydrology
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Coupling SAR X-band and optical data for NDVI retrieval: model calibration and validation on two test areas

2013

Sustainability of modern agro-hydrology requires the knowledge of spatial and temporal variability of vegetation biomass to optimize management of land and water resources. Diversely from optical imaging, temporal resolution of active sensors, such as SAR, is not limited by sky cloudiness; thus, they may be combined with optical imageries to provide a more continuous monitoring of land surfaces. Several new SAR missions (e.g., ALOS-PALSAR, COSMO-SkyMed 1 and 2, TerraSAR-X, TerraSAR-X2, Sentinel 1) acquiring at X-, C- and L-bands and dual polarization capability, are characterized by a short revisit time (from 12 h to ~10 days) and high spatial resolution (<20 m). These satellites could prov…

Synthetic aperture radarL bandMeteorologyBackscatterCloud covermedia_common.quotation_subjectSettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaContinuous monitoringRadar backscatteringNormalized Difference Vegetation IndexNDVI cross-polarized backscattering DEIMOS-1 COSMO-SkyMed Landsat 7 SCL-offGeographySkyTemporal resolutionSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliSettore ICAR/06 - Topografia E Cartografiamedia_commonRemote sensingvegetation index
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Investigating the Relationship between X-Band SAR Data from COSMO-SkyMed Satellite and NDVI for LAI Detection

2013

Monitoring spatial and temporal variability of vegetation is important to manage land and water resources, with significant impact on the sustainability of modern agriculture. Cloud cover noticeably reduces the temporal resolution of retrievals based on optical data. COSMO-SkyMed (the new Italian Synthetic Aperture RADAR-SAR) opened new opportunities to develop agro-hydrological applications. Indeed, it represents a valuable source of data for operational use, due to the high spatial and temporal resolutions. Although X-band is not the most suitable to model agricultural and hydrological processes, an assessment of vegetation development can be achieved combing optical vegetation indices (V…

Synthetic aperture radarMeteorologyCOSMO-SkyMedCloud coverSettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaX bandLand coverRadar backscatteringNormalized Difference Vegetation IndexLAIcross-polarized backscatteringTemporal resolutionDEIMOS-1General Earth and Planetary SciencesEnvironmental scienceSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliNormalized Difference Vegetation Index (NDVI)lcsh:QNormalized Difference Vegetation Index (NDVI); LAI; cross-polarized backscattering; DEIMOS-1; COSMO-SkyMedLeaf area indexlcsh:ScienceImage resolutionSettore ICAR/06 - Topografia E CartografiaRemote sensingRemote Sensing
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Coupling two radar backscattering models to assess soil roughness and surface water content at farm scale

2013

Remote sensing techniques are useful for agro-hydrological monitoring at the farm scale because the availability of spatially and temporally distributed data improves agricultural models for irrigation and crop yield optimization under water scarcity conditions. This research focuses on the surface water content retrieval using active microwave data. Two semi-empirical models were chosen as these showed the best performances in simulating cross and co-polarized backscatter. Thus, these models were coupled to obtain reliable assessments of both soil water content and soil roughness. The use of the coupled model enables one to avoid using roughness measured in situ. Remote sensing images and …

backscattering soil water content surface roughness vegetation indicesBackscatterSettore ICAR/02 - Costruzioni Idrauliche E Marittime E Idrologiasoil water contentRadar backscatteringSurface finishlaw.inventionData setlawvegetation indicesSoil waterSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliEnvironmental scienceRadarUnderwaterSettore ICAR/08 - Scienza Delle CostruzioniScale (map)Surface waterWater Science and TechnologyRemote sensingHydrological Sciences Journal
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