Search results for "mathematics"
showing 10 items of 22031 documents
HF radar for wind waves measurements in the Malta-Sicily Channel
2018
Abstract The CALYPSO HF radar network is a permanent and fully operational observing system currently composed of four CODAR SeaSonde stations. The system is providing real-time hourly maps of sea surface currents and waves data in the Malta-Sicily Channel. The present work aims to compare significant wave height measurements by HF Radar to wave data from numerical models and satellite altimeter. This is the first time that this set of wave data are analysed since the four HF radars were installed between 2012 and 2015. Results suggest that CODAR HF Radar wave data are a reliable source of wave information even in the case of extreme events, providing an avenue to improve and complete the o…
Gas mass derived by infrasound and UV cameras: Implications for mass flow rate
2016
Abstract Mass Flow Rate is one of the most crucial eruption source parameter used to define magnitude of eruption and to quantify the ash dispersal in the atmosphere. However, this parameter is in general difficult to be derived and no valid technique has been developed yet to measure it in real time with sufficient accuracy. Linear acoustics has been applied to infrasonic pressure waves generated by explosive eruptions to indirectly estimate the gas mass erupted and then the mass flow rate. Here, we test on Stromboli volcano (Italy) the performance of such methodology by comparing the acoustic derived results with independent gas mass estimates obtained with UV cameras, and constraining th…
ERA5-Land: A state-of-the-art global reanalysis dataset for land applications
2021
Framed within the Copernicus Climate Change Service (C3S) of the European Commission, the European Centre for Medium-Range Weather Forecasts (ECMWF) is producing an enhanced global dataset for the land component of the fifth generation of European ReAnalysis (ERA5), hereafter referred to as ERA5-Land. Once completed, the period covered will span from 1950 to the present, with continuous updates to support land monitoring applications. ERA5-Land describes the evolution of the water and energy cycles over land in a consistent manner over the production period, which, among others, could be used to analyse trends and anomalies. This is achieved through global high-resolution numerical integrat…
Toward a Comprehensive Dam Monitoring: On-Site and Remote-Retrieved Forcing Factors and Resulting Displacements (GNSS and PS–InSAR)
2021
Many factors can influence the displacements of a dam, including water level variability and environmental temperatures, in addition to the dam composition. In this work, optical-based classification, thermal diachronic analysis, and a quasi-PS (Persistent Scatter) Interferometric SAR technique have been applied to determine both forcing factors and resulting displacements of the crest of the Castello dam (South Italy) over a one-year time period. The dataset includes Sentinel-1A images acquired in Interferometric Wide swath mode using the Terrain Observation with Progressive Scans SAR (TOPSAR); Landsat 8 Thermal Infrared Sensor (TIRS) thermal images, and Global Navigation Satellite System …
Dynamic Triggering of Mud Volcano Eruptions During the 2016-2017 Central Italy Seismic Sequence
2017
On 24 August 2016 a seismic event (Mw 6.0) was the first of the long Central Italy sequence (ongoing at the end of 2017) of medium-to-high magnitude earthquakes, with nine Mw ≥5 up to October 2017, and with about 74.000 seismic events registered after one year. The largest was the Mw 6.5 30 October 2016 event near Norcia. After the major seismic events, seventeen mud volcanoes erupted around Monteleone di Fermo village (Marche region). Mud volcano eruptions generally occurred a few hours to a few days after the main earthquakes, suggesting a seismic triggering. We analyzed the peak ground velocities (PGV) and dynamic stresses during the three largest earthquakes. We also evaluated the stati…
Seismic sources and stress transfer interaction among axial normal faults and external thrust fronts in the Northern Apennines (Italy): A working hyp…
2016
In this study we analyse the main potential seismic sources in some axial and frontal sectors of the Northern Apennines, in Italy. This region was hit by a peculiar series of earthquakes that started in 1916 on the external thrust fronts near Rimini. Later, in 1917-1921, seismicity (up to Mw approximate to 6.5) shifted into the axial zone and clearly migrated north-westward, along the belt of active normal faults. The collection of fault-slip data focused on the active normal faults potentially involved in this earthquake series. The acquired data allowed us to better characterize the geometry and kinematics of the faults. In a few instances, the installation of local seismic networks durin…
Multi-Crop Green LAI Estimation with a New Simple Sentinel-2 LAI Index (SeLI)
2019
The spatial quantification of green leaf area index (LAIgreen), the total green photosynthetically active leaf area per ground area, is a crucial biophysical variable for agroecosystem monitoring. The Sentinel-2 mission is with (1) a temporal resolution lower than a week, (2) a spatial resolution of up to 10 m, and (3) narrow bands in the red and red-edge region, a highly promising mission for agricultural monitoring. The aim of this work is to define an easy implementable LAIgreen index for the Sentinel-2 mission. Two large and independent multi-crop datasets of in situ collected LAIgreen measurements were used. Commonly used LAIgreen indices applied on the Sentinel-2 10 m ×
Crop specific algorithms trained over ground measurements provide the best performance for GAI and fAPAR estimates from Landsat-8 observations
2021
Abstract Estimation of Green Area Index (GAI) and fraction of Absorbed Photosynthetically Active Radiation (fAPAR) from decametric satellites was investigated in this study using a large database of ground measurements over croplands. It covers six main crop types including rice, corn, wheat and barley, sunflower, soybean and other types of crops. Ground measurements were completed using either digital hemispherical cameras, LAI-2000 or AccuPAR devices over sites representative of a decametric pixel. Sites were spread over the globe and the data collected at several growth stages concurrently to the acquisition of Landsat-8 images. Several machine learning techniques were investigated to re…
Optimizing Gaussian Process Regression for Image Time Series Gap-Filling and Crop Monitoring
2020
Image processing entered the era of artificial intelligence, and machine learning algorithms emerged as attractive alternatives for time series data processing. Satellite image time series processing enables crop phenology monitoring, such as the calculation of start and end of season. Among the promising algorithms, Gaussian process regression (GPR) proved to be a competitive time series gap-filling algorithm with the advantage of, as developed within a Bayesian framework, providing associated uncertainty estimates. Nevertheless, the processing of time series images becomes computationally inefficient in its standard per-pixel usage, mainly for GPR training rather than the fitting step. To…
Empirical and physical estimation of Canopy Water Content from CHRIS/PROBA data
2013
20 páginas, 4 tablas, 7 figuras.