1,721,181 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
Comparison between surface and canopy layer urban heat island using MODIS data
No full textUrban heat island (UHI) maps were produced over the city of Milan, Italy, 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 highlight 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. Although the 1-km spatial resolution of MODIS may represent a limitation for a finer scale analysis, the four daily passes are essential to monitor the urban heat island at different times during the day
The usefulness of the Global Navigation Satellite Systems (GNSS) in the analysis of precipitation events
No full textIt is well known that the use of the Global Navigation Satellite Systems (GNSS), both with ground-based and Low Earth Orbit (LEO) receivers, allows retrieving atmospheric parameters in all the weather conditions.Ground-based GNSS technique provides the integrated precipitable water vapour (IPWV) with temporal continuity at a specific receiver station, while the GNSS LEO technique allows for Radio Occultation (RO) observations of the atmosphere, providing a detailed atmospheric profiling but without temporal continuity at a specific site.In this work, several precipitation events that occurred in Italy were analysed exploiting the potential of the two GNSS techniques (i.e. ground-based and space-based GNSS receivers). From ground-based receivers, time series of IPWV were produced at specific locations with the purpose of analysing the water vapour behaviour during precipitation events. From LEO receivers, the profiling potential was exploited to retrieve the cloud top altitude of convective events, taking into account that although GNSS RO could capture the dynamics of the atmosphere with high vertical resolution, the temporal resolution is not enough to continuously monitor such an event in a local area. Therefore, the GNSS 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
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
Land Surface Temperature and Urban Density: Multiyear Modeling and Relationship Analysis Using MODIS and Landsat Data
No full textThis work aims to model and relate the urban density and land surface temperature (LST) by a straightforward and efficient approach. Although the urban density-LST relation is widely addressed in literature, this study allows for its modeling and parameterization in an accurate way, providing a further scientific support for the city planning policy. The urban density and the LST analysis is carried out in the Bangkok area for the years 2004, 2008, 2012, and 2016; in this time interval, the city exhibited an evident urban expansion. Firstly, by using land cover maps obtained from Landsat reflective observations, the urban land density growth across the years studied is evaluated by applying a ring-based approach, a method employed in urban theory, providing urban density curves as a function of the distance from the city center. For each year, the urban density curve is well modeled by an inverse S-shape function, the parameters of which highlight an urban sprawl over the years studied and an outskirt growth in recent years. Then, employing 237 MODIS LST images, the night-time and daytime mean LST patterns for each year were processed applying the same ring-based analysis, obtaining LST trends versus distance. Albeit the mean LST decreases away from the city core, the daytime and night-time trends are different in both shape and values. The daytime LST exhibits a trend also modeled by an inverse S-shape function, whereas the night-time one is modeled by a quadratic function. Finally, the urban density-LST relationship is inferred across the years: For daytime, the relation is quadratic with a coefficient of determination r2 around 0.98–0.99, whereas for night-time the relation is linear with r2 of the order of 0.95–0.96. The proposed approach allows for reliable modeling and to straightforwardly infer a very accurate urban density-LST relationship
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
Satellite and ground-based sensors for the Urban Heat Island analysis in the city of Rome
Full text linkIn this work, the trend of the Urban Heat Island (UHI) of Rome is analyzed by both ground-based weather stations and a satellite-based infrared sensor. First, we have developed a suitable algorithm employing satellite brightness temperatures for the estimation of the air temperature belonging to the layer of air closest to the surface. UHI spatial characteristics have been assessed using air temperatures measured by both weather stations and brightness temperature maps from the Advanced Along Track Scanning Radiometer (AATSR) on board ENVISAT polar-orbiting satellite. In total, 634 daytime and nighttime scenes taken between 2003 and 2006 have been processed. Analysis of the Canopy Layer Heat Island (CLHI) during summer months reveals a mean growth in magnitude of 3-4 K during nighttime and a negative or almost zero CLHI intensity during daytime, confirmed by the weather stations. © 2010 by the authors; licensee MDPI, Basel, Switzerland
Reducing scaling effect on downscaled land surface temperature maps in heterogenous urban environments
No full textThe literature review indicates that a scaling effect does exist in downscaling land surface temperature (DLST) processes, and no substantial methods were specially developed for addressing it. In this research, the main aim is to develop a new method to reduce the scaling effect on DLST maps at high resolutions. A thermal component-based thermal spectral unmixing (TSU) model was modified and a multiple regression (REG) model was adopted to create DLST maps at high resolutions. A combined variance of red and NIR bands at a very high resolution with a difference image between upscaled LST and DLST was used to develop a new method. With two case data sets, LSTs at coarse resolutions were downscaled by using the modified TSU model and the REG model to create DLST results. The new method with a correction term expression (a linear model created by using a semi-empirical approach) was used to improve the DLST maps in the two case study areas. The experimental results indicate that the new method could reduce the root mean square error and the mean absolute error >30% and >33%, respectively, and thus demonstrate that the proposed method was effective and significant, especially reducing the scaling effect on DLST results at very high resolutions. The novel significance for the new method is directly reducing the scaling effect on DLST maps at high resolutions
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
Correcting Scaling Effect in Downscaling Surface Temperature at High Resolutions with a Multiple Regional Correction Approach
No full textThere exists a scaling error in currently downscaling land surface temperature (DLST) processes and it is necessary to develop substantial methods specially for reducing it. In this letter, a multiple regional correction (MRC) approach with multiple correction terms (mCTs) was proposed to correct scaling errors in DLST processes. The test results indicate that (1) the proposed approach can effectively correct the scaling effects in DLST processes at high resolutions by reducing root mean square error by ~ 55%; (2) all initial resolutions considered for optical data (0.5 m – 4 m) were effective for developing the MRC approach with mCTs in correcting the scaling errors. Overall, this novel approach can significantly improve the accuracy of DLST maps at very high resolutions
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