Search results for "math"
showing 10 items of 25151 documents
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…
Mapping land surface emissivity from NDVI: Application to European, African, and South American areas
1996
Thermal infrared emissivity is an important parameter both for surface characterization and for atmospheric correction methods. Mapping the emissivity from satellite data is therefore a very important question to solve. The main problem is the coupling of the temperature and emissivity effects in the thermal radiances. Several methods have been developed to obtain surface emissivity from satellite data. In this way we propose a theoretical model that relates the emissivity to the NDVI (normalized difference vegetation index) of a given surface and explains the experimental behavior observed by van de Griend and Owe. We can use it to obtain the emissivity in any thermal channel, but in this …
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.
Top-of-Atmosphere Retrieval of Multiple Crop Traits Using Variational Heteroscedastic Gaussian Processes within a Hybrid Workflow.
2021
In support of cropland monitoring, operational Copernicus Sentinel-2 (S2) data became available globally and can be explored for the retrieval of important crop traits. Based on a hybrid workflow, retrieval models for six essential biochemical and biophysical crop traits were developed for both S2 bottom-of-atmosphere (BOA) L2A and S2 top-of-atmosphere (TOA) L1C data. A variational heteroscedastic Gaussian process regression (VHGPR) algorithm was trained with simulations generated by the combined leaf-canopy reflectance model PROSAILat the BOA scale and further combined with the Second Simulation of a Satellite Signal in the Solar Spectrum (6SV) atmosphere model at the TOA scale. Establishe…
A space-time rainfall generator for highly convective Mediterranean rainstorms
2003
Distributed hydrological models require fine resolution rainfall inputs, enhancing the practical interest of space-time rainfall models, capable of generating through numerical simulation realistic space-time rainfall intensity fields. Among different mathematical approaches, those based on point processes and built upon a convenient analytical description of the raincell as the fundamental unit, have shown to be particularly suitable and well adapted when extreme rainfall events of convective nature are considered. Starting from previous formulations, some analytical refinements have been considered, allowing practical generation of space-time rainfall intensity fields for that type of rai…