1,721,031 research outputs found
Spectral index utility for summer urban heating analysis
No full textThe land surface temperature (LST) retrieval in an urban environment by thermal remote sensing is a widespread scientific topic and several studies have been made to point out the correspondence between spectral indices and LST pattern. This work evaluates the potential of the spectral indices introduced in the literature, more than 30, by assessing their correlation with the summer LST in the heterogeneous urban area of Rome, Italy, considering two different triplets of images acquired during 2009 and 2011 by the Landsat Thematic Mapper (TM). The spectral indices have been divided into vegetation and built up-soil indices employing the reflective TM bands, and then ranked on the basis of their linear and monotonic relationship with the LST. Vegetation indices have a strong negative correlation with LST: vegetation area (VA), non-linear index, modified soil adjusted vegetation index exhibit a greater Pearson and Spearman correlation coefficient with LST. The more useful spectral indices for built up and soil analysis, exhibiting a greater positive correlation with LST, are the impervious surface area (ISA), the bare soil index, the index-based built-up index, and the normalized difference built-up index. Interesting indications of the impact on the spectral index performance of specific land-cover classes embedded in an urban environment, such as the bare soil and the water classes were pointed out; for example, the reduction of the ISA and VA capability to display the full dynamic range of the LST patter
Downscaling of land surface temperature using airborne high-resolution data: A case study on Aprilia, Italy
No full textA regression-based downscaling of land surface temperature was developed over the heterogeneous urban area of Aprilia, Central Italy, using high resolution (HR) airborne data. Airborne sensors provided thermal and visible– near infrared (VNIR) measurements at 2-m pixel size. Coarse resolution images at 40, 30, and 20 m, upscaled by aggregation from the native airborne data, were sharpened to the finer resolution of 2 m. The main core of the downscaling method is the use of the spectral mixture analysis (SMA) to derive fractional pixel composition as predictors of the regression scheme. The HR VNIR data allow choosing detailed land cover types in the application of SMA, such as bright/dark roofs, and the benefit of this detailed selection is proved. The estimation error of the custom technique improves of about 10%–15% with respect to a classical regression downscaling
On the possibility of sensing an early stage fire in moving vehicles by microwave radiometry
No full textThis paper deals with passive remote sensing of fire spots in moving vehicles by a ground-based microwave radiometer mounted near a rail or a road. Images have been simulated at 30 GHz, identifying also dielectric properties of the vehicle wall able to guarantee a penetration of the microwave radiation. The 30-GHz operative frequency can be considered a trade-off between the antenna system dimensions and the penetration capability of microwave radiation through a dielectric wall. It has been seen that the radiation associated to the fire spot emerges distinctly through a dielectric wall in several cases, depending also on fire dimensions, loss tangent values of the wall, and its thickness. This study confirms that the detection of an early stage fire through a dielectric wall by microwave radiometry is promising, taking into account that the use of infrared sensor systems mainly depends on emissivity knowledge of the vehicle surface and on the heating of the monitored external wal
Optimization of the biomechanical design of plate-loaded strength training machines: The free-weight lifting experience
No full textWe established a set of analytical equations that constitute the biomechanical framework for the optimal design of plateloaded strength training machines. Specifically, we assessed the effect on the exercise kinetics of a change in the distance dP between the site P of the resistance lever where the weight plates are loaded and the axis of rotation of the lever. To this end, the distance dP was increased, while keeping the value of the resistance torque tR unchanged by a simultaneous decrease in the mass mP of plates loaded on the lever (dPmP=const). A progressive increase in dP (under the condition dPmP=const) yielded a sharp decrease, followed by a steady increase, in the moment of inertia of the loaded resistance lever (relative to its axis of rotation). The impact of this change on the kinetic effects related to the inertia of the moving equipment masses (inertial effects) has been discussed for maximal and explosive exercises, and for sub-maximal exercises executed at controlled cadence. We also detected a specific value of dP for which the torque related to the inertial effects, expressed as a percentage of tR, turns out to be independent of the selected level of external resistance. This condition precisely reflects the linear-dynamic condition that occurs when lifting free weights
The synergy of ground based GPS measurements and the GPS radio occultation for analyzing precipitation events
No full textThe Global Positioning System (GPS), both with ground-based and Low Earth Orbit (LEO) receivers, allows to retrieve atmospheric parameters in all the weather conditions. Ground-based GPS technique provides the integrated water vapour (IWV) with temporal continuity at a specific receiver station, while the GPS LEO satellites allow profiling the atmosphere through the Radio Occultation (RO) technique, with high vertical resolution but low temporal resolution at a specific site.
The objective of this work is to connect the convective system intensity measured by meteorological weather stations, to the storm ́s characteristics retrieved by the GPS signal.
Several precipitation events (in Europe and United States) were analyzed exploiting the potential of the two GPS techniques (i.e. ground-based and space-based GPS receivers). From ground-based receivers, time series of IWV were produced at specific locations with the purpose of analysing the water vapour behaviour before and during precipitation events and connecting this behaviour to the precipitation intensity. From LEO receivers, the profiling potential was exploited to retrieve the cloud top altitude of convective events, and we connected the cloud top altitude to the precipitation intensity.
The GPS technique can be considered as a supplemental meteorological system useful in studying precipitation events, but with very different spatial and temporal features depending on the receiver positioning. Our results are promising and the synergy of the different information provided on the same target area by ground based and LEO receivers could contribute to the development of an algorithm for nowcasting the intensity of the severe convection
Tecniche di ‘change detection’ attraverso l’utilizzo del sensore laser scanning 3D
No full textThe idea of the following work is to test a technique of 'Change Detection' based on the generation of Digital Elevation Models of the ground realized through the use of a laser scanning 3D. This sensor works in the near infrared and allows to measure points to the ground with space solution of the order of the centimetre with a precision of ± 6 mm. Exploiting the data obtained from the laser scanner producing DEM with very high precision is possible to apply a differential technique based on the temporal comparison of the DEM built up at different times. This technique allows to evaluate the shifting vectors, to investigate the geometrical changes and the different structure of the ground surface and in particular to compute volume
Surface and air heat island of Milan: spatial and temporal analysis from MODIS
No full textIn this work the urban heat island (UHI) maps were produced over Milan using data provided by the Moderate-resolution Imaging Spectroradiometer (MODIS). Two types of UHI were analyzed simultaneously: the canopy layer heat island (CLHI) and the surface urban heat island (SUHI). The SUHI and CLHI maps allow to monitor the spatial and temporal evolution of surface and air heating and also to point out and quantify the different features (e.g. magnitude, spatial extent, orientation and UHI centre location) using a Gaussian surface fitting.This results indicate that the SUHI effect is a noticeable phenomenon throughout the whole diurnal cycle: it has a stronger intensity in the daytime with peaks around 9-10 K while in the nighttime it decreases by a factor of 2. In contrast, the CLHI during the daytime is absent and after sunset shows features similar to the nighttime SUHI
Mapping the Land Surface Temperature over Urban Areas from Space: a Downscaling Approach
No full textSince decades, the land surface temperature (LST) is a parameter widely considered in the urban area mapping
from space. LST has been often retrieved and mapped to evaluate the surface urban heat island (SUHI) using
different spaceborne platforms, such as AATSR, ASTER, MODIS and Landsat. Several factors need to be assessed in
the LST retrieval from satellite thermal infrared data: sensor radiometric calibration, atmospheric correction, surface
emissivity estimation. Particularly, in urban area mapping issue, the satellite sensor spatial resolution may be a
limiting factor in detailing the fine scale spatial variability, especially in the presence of impervious surfaces and
sharp transitions (e.g., buildings, roads, parking lots, riverside, restricted vegetated zones), such as in a urban
texture. The growing demand of remote sensing maps with finer and finer spatial resolution to successfully
monitor the SUHI effects at district level and to avoid temperature underestimation stimulates the development of
downscaling techniques when the actual sensor measurements do not meet the spatial detail requirements. In this
work we perform the downscaling of coarse resolution LST maps from MODIS and Landsat to finer resolutions
with the aim to increase the information content of the original maps, using summer satellite images over Milan,
Rome and Florence. The downscaling is the enhancement of the spatial resolution of the original pixel data using
ancillary information at higher spatial resolution. Different physical and statistical downscaling approaches have
been proposed in literature: in this work, a statistical LST downscaling approach regression-based using different
spectral indices over heterogeneous urban landscape is proposed, and the reliability assessed. This analysis allows
to select the spectral indices and their combinations providing the best results in the LST image sharpening. First,
the downscaling was performed using the Landsat TM data over Milan and Rome, assuming the 120 m spatial
resolution image as reference. Then, the same downscaling regressive schemes were applied on the contemporary
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coarse resolution LST MODIS image and verified with the reference LST Landsat map. A further downscaling
assessment at finer resolution was carried out using the LST retrieved from Landsat TM over the city of Florence:
in this case the sharpened image was compared with a high-resolution thermal image provided by an airborne
survey carried out on July 18, 2010. Two Landsat scenes were processed before and after the flight, with the aim
to evaluate the impact of the Landsat TM thermal channel resolution (120 m) on the LST estimation over a
heterogeneous urban texture. Again, thermal data were downscaled at 30 m with a statistical algorithm using a
regression on different spectral indices. The proposed approaches and comparisons allows us to assess potentials
and limits of the LST downscaling performed over an heterogeneous urban area
Gestione real time, analisi e previsione di temperature estreme sul bacino del Trasimeno
No full textObiettivo di questo lavoro è la previsione delle temperature minime e delle gelate sul bacino del Lago Trasimeno. Tali parametri influenzano direttamente il microclima dell’area del Trasimeno, la qualità e la quantità delle produzioni agricole limitrofe e il livello idrico del lago. Accanto a tale analisi, si sta inoltre procedendo alla realizzazione di un sito web nel quale tali previsioni vengano rese disponibili real-time a tutte le utenze, insieme ai dati meteorologici registrati.
Il database a disposizione è costituito da dati provenienti da 8 diverse stazioni meteorologiche distribuite su tutto il bacino lacustre dal 1988. Per prevedere le temperature estreme è stato implementato un algoritmo statistico di tipo regressivo utilizzando i dati raccolti fino alla fine del 2003. Parallelamente lo stesso dataset è stato impiegato per addestrare opportune reti neurali. Per la validazione, gli algoritmi regressivi e le reti neurali sono stati successivamente testati sui dati meteorologici più recenti. Tali metodologie sono state implementate in ambiente Matlab, realizzando una procedura automatica che permette di prevedere le gelate e le temperature estreme giornaliere in real-time a partire dall’ora del tramonto.
L’analisi degli errori commessi nella previsione delle temperature estreme ha permesso di stabilire la metodologia migliore e i parametri atmosferici necessari per tale tipo di previsione. L’algoritmo di previsione agrometeorologica assieme ad un sistema informatico di allerta on-line, permetterà di prevenire danni alle colture e di migliorarne la qualità
A stable gaussian fitting procedure for the parameterization of remote sensed thermal images
Full text linkAn image analysis procedure based on a two dimensional Gaussian fitting is presented and applied to satellite maps describing the surface urban heat island (SUHI). The application of this fitting technique allows us to parameterize the SUHI pattern in order to better understand its intensity trend and also to perform quantitative comparisons among different images in time and space. The proposed procedure is computationally rapid and stable, executing an initial guess parameter estimation by a multiple regression before the iterative nonlinear fitting. The Gaussian fit was applied to both low and high resolution images (1 km and 30 m pixel size) and the results of the SUHI parameterization shown. As expected, a reduction of the correlation coefficient between the map values and the Gaussian surface was observed for the image with the higher spatial resolution due to the greater variability of the SUHI values. Since the fitting procedure provides a smoothed Gaussian surface, it has better performance when applied to low resolution images, even if the reliability of the SUHI pattern representation can be preserved also for high resolution images.An image analysis procedure based on a two dimensional Gaussian fitting is presented and applied to satellite maps describing the surface urban heat island (SUHI). The application of this fitting technique allows us to parameterize the SUHI pattern in order to better understand its intensity trend and also to perform quantitative comparisons among different images in time and space. The proposed procedure is computationally rapid and stable, executing an initial guess parameter estimation by a multiple regression before the iterative nonlinear fitting. The Gaussian fit was applied to both low and high resolution images (1 km and 30 m pixel size) and the results of the SUHI parameterization shown. As expected, a reduction of the correlation coefficient between the map values and the Gaussian surface was observed for the image with the higher spatial resolution due to the greater variability of the SUHI values. Since the fitting procedure provides a smoothed Gaussian surface, it has better performance when applied to low resolution images, even if the reliability of the SUHI pattern representation can be preserved also for high resolution images
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