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  • 1
    Publication Date: 2016-10-19
    Description: Industries, which are mainly responsible for high energy consumption, need to invest in research projects in order to develop new managing systems for rational energy use, and to tackle the devastating effects of climate change caused by human behavior. The study described in this paper concerns the forging industry, where the production processes generally start with the heating of steel in furnaces, and continue with other processes, such as heat treatments and different forms of machining. One of the most critical operations, in terms of energy loss, is the opening of the furnace doors for insertion and extraction operations. During this time, the temperature of the furnaces decreases by hundreds of degrees in a few minutes. Because the dispersed heat needs to be supplied again through the combustion of fuel, increasing the consumption of energy and the pollutant emissions, the evaluation of the amount of lost energy is crucial for the development of systems which can contain this loss. To perform this study, CFD simulation software was used. Results show that when the door opens, because of temperature and pressure differences between the furnace and the ambient air, turbulence is created. Results also show that the amount of energy lost for an opening of 10 min for radiation, convection and conduction is equal to 5606 MJ where convection is the main contributor, with 5020 MJ. The model created, after being validated, has been applied to perform other simulations, in order to improve the energy performance of the furnace. Results show that reducing the opening time of the door saves energy and limits pollutant emissions.
    Electronic ISSN: 1996-1073
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Published by MDPI Publishing
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  • 2
    Publication Date: 2020-05-13
    Description: Sun-induced chlorophyll fluorescence (SIF) retrieved from satellite spectrometers can be a highly valuable proxy for photosynthesis. The SIF signal is very small and notoriously difficult to measure, requiring sub-nanometre spectral-resolution measurements, which to date are only available from atmospheric spectrometers sampling at low spatial resolution. For example, the widely used SIF dataset derived from the GOME-2 mission is typically provided in 0.5∘ composites. This paper presents a new SIF dataset based on GOME-2 satellite observations with an enhanced spatial resolution of 0.05∘ and an 8 d time step covering the period 2007–2018. It leverages on a proven methodology that relies on using a light-use efficiency (LUE) modelling approach to establish a semi-empirical relationship between SIF and various explanatory variables derived from remote sensing at higher spatial resolution. An optimal set of explanatory variables is selected based on an independent validation with OCO-2 SIF observations, which are only sparsely available but have a high accuracy and spatial resolution. After bias correction, the resulting downscaled SIF data show high spatio-temporal agreement with the first SIF retrievals from the new TROPOMI mission, opening the path towards establishing a surrogate archive for this promising new dataset. We foresee this new SIF dataset becoming a valuable asset for Earth system science in general and for monitoring vegetation productivity in particular. The dataset is available at https://doi.org/10.2905/21935FFC-B797-4BEE-94DA-8FEC85B3F9E1 (Duveiller et al., 2019).
    Print ISSN: 1866-3508
    Electronic ISSN: 1866-3516
    Topics: Geosciences
    Published by Copernicus
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  • 3
    Publication Date: 2020-04-12
    Description: Coastal sand dunes are highly dynamic aeolian landforms where different spatial patterns can be observed due to the complex interactions and relationships between landforms and land cover. Sediment distribution related to vegetation types is explored here on a single ridge dune system by using an airborne hyperspectral and light detection and ranging (LiDAR) remote sensing dataset. A correlation model is applied to describe the continuum of dune cover typologies, determine the class metrics from landscape ecology and the morphology parameters, and extract the relationship intensity among them. As a main result, the mixture of different vegetation types such as herbaceous, shrubs, and trees classes shows to be a key element for the sediment distribution pattern and a proxy for dune sediment retention capacity, and the anthropic fingerprints can play an even major role influencing both ecological and morphological features. The novelty of the approach is mostly based on the synergistic use of LiDAR with hyperspectral that allowed (i) the benefit from already existing processing methods to simplify the way to obtain thematic maps and coastal metrics and (ii) an improved detection of natural and anthropic landscape.
    Electronic ISSN: 2072-4292
    Topics: Architecture, Civil Engineering, Surveying , Geography
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  • 4
  • 5
    Publication Date: 2020-06-08
    Description: Identifying fire-affected areas is of key importance to support post-fire management strategies and account for the environmental impact of fires. The availability of high spatial and temporal resolution optical satellite data enables the development of procedures for detailed and prompt post-fire mapping. This study proposes a novel approach for integrating multiple spectral indices to generate more accurate burned area maps by exploiting Sentinel-2 images. This approach aims to develop a procedure to combine multiple spectral indices using an adaptive thresholding method and proposes an agreement index to map the burned areas by optimizing omission and commission errors. The approach has been tested for the burned area classification of four study areas in Italy. The proposed agreement index combines multiple spectral indices to select the actual burned pixels, to balance the omission and commission errors, and to optimize the overall accuracy. The results showed the spectral indices singularly performed differently in the four study areas and that high levels of commission errors were achieved, especially for wildfires which occurred during the fall season (up to 0.93) Furthermore, the agreement index showed a good level of accuracy (minimum 0.65, maximum 0.96) for all the study areas, improving the performance compared to assessing the indices individually. This suggests the possibility of testing the methodology on a large set of wildfire cases in different environmental conditions to support the decision-making process. Exploiting the high resolution of optical satellite data, this work contributes to improving the production of detailed burned area maps, which could be integrated into operational services based on the use of Earth Observation products for burned area mapping to support the decision-making process.
    Electronic ISSN: 2072-4292
    Topics: Architecture, Civil Engineering, Surveying , Geography
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  • 6
    Publication Date: 2020-10-27
    Description: Mosquitoes represent a considerable nuisance and are actual/potential vectors of human diseases in Europe. Costly and labour-intensive entomological monitoring is needed to correct planning of interventions aimed at reducing nuisance and the risk of pathogen transmission. The widespread availability of mobile phones and of massive Internet connections opens the way to the contribution of citizen in complementing entomological monitoring. ZanzaMapp is the first mobile “mosquito” application for smartphones specifically designed to assess citizens’ perception of mosquito abundance and nuisance in Italy. Differently from other applications targeting mosquitoes, ZanzaMapp prioritizes the number of records over their scientific authentication by requesting users to answer four simple questions on perceived mosquito presence/abundance/nuisance and geo-localizing the records. The paper analyses 36,867 ZanzaMapp records sent by 13,669 devices from 2016 to 2018 and discusses the results with reference to either citizens’ exploitation and appreciation of the app and to the consistency of the results obtained with the known biology of main mosquito species in Italy. In addition, we provide a first small-scale validation of ZanzaMapp data as predictors of Aedes albopictus biting females and examples of spatial analyses and maps which could be exploited by public institutions and administrations involved in mosquito and mosquito-borne pathogen monitoring and control.
    Print ISSN: 1661-7827
    Electronic ISSN: 1660-4601
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Medicine
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  • 7
    Publication Date: 2018-06-13
    Description: Knowledge of inland water quality and riverine inputs to oceans is fundamental for water management, environmental monitoring, and the definition of policies and planning strategies related to the sustainable use of rivers. While European Union directives aim at the conservation of inland water resources, the ground operational monitoring network is often inadequate. River monitoring using Remote Sensing may complement in-situ measurements, supplying continuous, spatially explicit representation of parameters related to water quality and solid transport, even if the high-frequency dynamics of water parameters may not be caught due to limited satellite revisit time. Sentinel-2 and Landsat-8 satellites, equipped with MSI and OLI optical sensors whose spectral bands perform a more accurate atmospheric correction, allow for the development of methodologies for monitoring river color from space, thanks to high spatial resolution and short revisit times. This study presents a processing chain, developed to monitor water constituents in rivers using high-resolution satellite images. Multi-temporal analysis of chlorophyll-a (Chl-a) and total suspended matter (TSM) bio-geophysical variables was performed for the case study of the Po River (Italy) for the year 2017. Quantitative estimations of water constituents were retrieved from Sentinel-2 optical multispectral satellite data using the C2RCC algorithm, and the main outcomes are discussed. The developed processing chain can be used to create operational services for river monitoring, and represent a major improvement in the identification of spatio-temporal dynamics (like solid transport) in riverine systems.
    Electronic ISSN: 2504-3900
    Topics: Technology
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  • 8
    Publication Date: 2019-06-04
    Description: The Copernicus Programme has become the world’s largest space data provider, providing complete, free and open access to satellite data, mainly acquired by Sentinel satellites. Sentinel-1 Synthetic Aperture Radar (SAR) data have improved spatial resolution and high revisit frequency, making them useful for a wide range of applications. While few research applications need Sentinel-1 Ground Range Detected (GRD) data with few corrections applied, a wider range of users needs products with a standard set of corrections applied. In order to facilitate the exploitation of Sentinel-1 GRD products, there is the need to standardise procedures to preprocess SAR data to a higher processing level. A standard generic workflow to preprocess Copernicus Sentinel-1 GRD data is presented here. The workflow aims to apply a series of standard corrections, and to apply a precise orbit of acquisition, remove thermal and image border noise, perform radiometric calibration, and apply range Doppler and terrain correction. Additionally, the workflow allows spatially snapping of Sentinel-1 GRD products to Sentinel-2 MSI data grids, in order to promote the use of satellite virtual constellations by means of data fusion techniques. The presented workflow allows the production of a set of preprocessed Sentinel-1 GRD data, offering a benchmark for the development of new products and operational down-streaming services based on consistent Copernicus Sentinel-1 GRD datasets, with the aim of providing reliable information of interest to a wide range of communities.
    Electronic ISSN: 2504-3900
    Topics: Technology
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  • 9
    Publication Date: 2019-06-04
    Description: Information related to the impact of wildfire disturbances on ecosystems is of paramount interest to account for environmental loss, to plan strategies for facilitating ecosystem restoration, and to monitor the dynamics of vegetation restoration. Phenological metrics can represent a good candidate to monitor and quantify vegetation recovery after natural hazards like wildfire disturbances. Satellite observations have been demonstrated to be a suitable tool for wildfire disturbed areas monitoring, allowing both the identification of burned areas and the monitoring of vegetation recovery. This research study aims to identify post-fire vegetation restoration dynamics for the area surrounding Naples (Italy), affected by severe wildfires events in 2017. Sentinel-2 satellite data were used to extract phenological metrics from the estimated Leaf Area Index (LAI) and to relate such metrics to environmental variables in order to evaluate the vegetation restoration and landslide susceptibility for different land use classes.
    Electronic ISSN: 2504-3900
    Topics: Technology
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  • 10
    Publication Date: 2018-03-22
    Electronic ISSN: 2504-3900
    Topics: Technology
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