0000000000763047

AUTHOR

Rita Montone

showing 3 related works from this author

Enhancing TIR Image Resolution via Bayesian Smoothing for IRRISAT Irrigation Management Project

2013

Accurate estimation of physical quantities depends on the availability of High Resolution (HR) observations of the Earth surface. However, due to the unavoidable tradeoff between spatial and time resolution, the acquisition instants of HR data hardly coincides with those required by the estimation algorithms. A possible solution consists in constructing a synthetic HR observation at a given time k by exploiting Low Resolution (LR) and HR data acquired at different instants. In this work we recast this issue as a smoothing problem, thus focusing on cases in which observations acquired both before and after time k are available. The proposed approach is validated on a region of interest for t…

EstimationIrrigation Managementbusiness.industrySettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaBrightness TemperatureBayesian SmoothingThermal SharpeningBayesian smoothingGeographyRegion of interestMultitemporal AnalysiKey (cryptography)thermal infraredComputer visionArtificial intelligencebusinessIrrigation managementImage resolutionAlgorithmMultisensor Data FusionSmoothingSettore ICAR/06 - Topografia E CartografiaPhysical quantity
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Robustified smoothing for enhancement of thermal image sequences affected by clouds

2015

Obtaining radiometric surface temperature information with both high acquisition rate and high spatial resolution is still not possible through a single sensor. However, in several earth observation applications, the fusion of data acquired by different sensors is a viable solution for so called image sharpening. A related issue is the presence of clouds, which may impair the performance of the data fusion algorithms. In this paper we propose a robustified setup for the sharpening of thermal images in a non real-time scenario, capable to deal with missing thermal data due to cloudy pixels, and robust with respect to cloud mask misclassifications. The effectiveness of the presented technique…

Cloud MaskingEarth observationComputer scienceSharpeningBayesian SmoothingRobustness (computer science)Multitemporal AnalysiThermalRobustneSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliComputer visionRobustnessImage resolutionMultitemporal AnalysisPixelbusiness.industrySettore ING-INF/03 - TelecomunicazioniSettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaComputer Science Applications1707 Computer Vision and Pattern RecognitionBayesian Smoothing; Cloud Masking; Multitemporal Analysis; Robustness; Thermal Sharpening; Earth and Planetary Sciences (all); Computer Science Applications1707 Computer Vision and Pattern RecognitionThermal SharpeningArtificial intelligencebusinessEarth and Planetary Sciences (all)SmoothingSettore ICAR/06 - Topografia E CartografiaInterpolation
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Soil water content monitoring: a verification of thermal inertia approaches on low spatial, high temporal resolutions images

2013

Soil water content is directly connected with soil evaporation and plant transpiration processes; in particular, soil water content within the root zone, is readily available to evapotranspiration. Thus, in agricultural sciences, the assessment of the spatial distribution of soil water content could be of utmost importance in evaluating crop water requirement. In spite of limitations to applicability due to contingent cloud cover, water content of the upper part of the soil can be determined by applying the thermal inertia approach by coupling optical and thermal infrared images. The thermal inertia formulation, rigorously retrieved on bare soil, has been also verified on soils partially co…

Cloud coverSettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaSoil scienceVegetationSoil water contentSpatial distributionPhase differenceSoil thermal propertiesGeographyMODISEvapotranspirationSoil waterSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliWater contentThermal inertiaSettore ICAR/06 - Topografia E CartografiaRemote sensingTranspirationRemote Sensing for Agriculture, Ecosystems, and Hydrology XV
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