The study of afforestation is crucial to monitor land transformations and represents a central topic in sustainable development procedures, in terms of climate change, ecosystem services monitoring, ...and planning policies activities. Although surveying afforestation is important, the assessment of the growing forests is difficult, since land cover has different durations depending on the species. In this context, remote sensing can be a valid instrument to evaluate the afforestation process. Nevertheless, while a vast literature on forest disturbance exists, only a few studies focus on afforestation and almost none directly exploits remote sensing data. This study aims to automatically classify non-forest, afforestation, and forest areas using remote sensing data. To this purpose, we constructed a reference dataset of 61 polygons that suffered a change from non-forest to forest in the period 1988-2020. The reference data were constructed with the Land Use Inventory of Italy and through photointerpretation of orthophotos (1988-2012, spatial resolution 50 × 50 cm) and very high-resolution images (2012-2020, spatial resolution 30 × 30 cm). Using Landsat Best Available Pixel composites time-series (1984-2020) we calculated 52 temporal predictors: four temporal metrics (median, standard deviation, Pearson’s correlation coefficient R, and slope) calculated for 13 different bands (the six Landsat spectral bands, three Spectral Vegetation Indices, and four Tasseled Cap Indices). To verify the possibility of distinguishing afforestation from non-forest and forest, given the differences between them can be minimal, we tested four different models aiming at classifying the following categories: (i) non-forest/afforestation, (ii) afforestation/forest, (iii) non-forest/forest and (iv) non-forest/afforestation/forest. Temporal predictors were used with random forest which was calibrated using random search, validated using k-fold Cross-Validation Overall Accuracy (OAcv), and further using out-of-bag independent data (OAoob). Results illustrate that the distinction of afforestation/forest reaches the largest OAcv (87%), followed by non-forest/forest (83%), non-forest/afforestation (75%) and non-forest/afforestation/forest (72%). The different OA values confirm that the difference in photosynthetic activity between forest and afforestation can be analysed through remote sensing to distinguish them. Although remote sensing data are currently not exploited to monitor afforestation areas our results suggest it may be a valid support for country-level monitoring and reporting.
ALICE (A Large Ion Collider Experiment) studies the Quark-Gluon Plasma (QGP): a deconfined state of nuclear matter obtained in ultra-relativistic heavy-ion collisions. One of the key probes for QGP ...characterization is the study of quarkonia and open heavy flavour production, of which ALICE exploits the muonic decay. In particular, a set of Resistive Plate Chambers (RPCs), placed in the forward rapidity region of the ALICE detector, is used for muon identification purposes.
The correct operation of these detectors is ensured by the choice of the proper gas mixture. Currently they are operated with a mixture of C2H2F4, i-C4H10 and SF6 but, starting from 2017, new EU regulations have enforced a progressive phase-out of C2H2F4 because of its large Global Warming Potential (GWP), which is making it difficult and costly to purchase. Moreover, CERN asked LHC experiments to reduce greenhouse gases emissions, to which RPC operation contributes significantly.
A possible candidate for C2H2F4 replacement is the C3H2F4 (diluted with other gases, such as CO2), which has been extensively tested using cosmic muons. Promising gas mixtures have been devised; the next crucial steps are the detailed in-beam characterization of such mixtures as well as the study of their performance under increasing irradiation levels.
This contribution will describe the methodology and results of beam tests carried out at the CERN Gamma Irradiation Facility (equipped with a high activity 137Cs source and muon beam) with an ALICE-like RPC prototype, operated with several mixtures with varying proportions of CO2, C3H2F4, i-C4H10 and SF6 . Absorbed currents, efficiencies, prompt charges, cluster sizes, time resolutions and rate capabilities will be presented, both from digitized (for detailed shape and charge analysis) and discriminated (using the same front-end electronics as employed in ALICE) signals.
In the last few years, an intense R &D activity on particle detectors for future HEP applications has been carried on with the aim of developing new techniques as well as studying the performance of ...already existing detectors when operated in a high rate environment. As for Resistive Plate Chamber detectors, the main challenges to face are the improvement of their detection capabilities and longevity at very high-rates, and the search for new eco-friendly gasmixtures free from greenhouse components. Results obtained in the framework of the RPC ECOGas@GIF++ Collaboration on a thin-Resistive Plate Chamber exposed at the CERN Gamma Irradiation Facility and operated with eco-friendly gas mixtures based on Tetrafluoropropene and Carbon dioxide will be discussed in this paper.
Results obtained by the RPC ECOgas@GIF++ Collaboration, using Resistive Plate Chambers operated with new, eco-friendly gas mixtures, based on tetrafluoropropene and carbon dioxide, are shown and ...discussed in this paper. Tests aimed to assess the performance of this kind of detectors in high-irradiation conditions, analogous to the ones foreseen for the coming years at the Large Hadron Collider experiments, were performed, and demonstrate a performance basically similar to the one obtained with the gas mixtures currently in use, based on tetrafluoroethane, which is being progressively phased out for its possible contribution to the greenhouse effect. Long term aging tests are also being carried out, with the goal to demonstrate the possibility of using these eco-friendly gas mixtures during the whole High Luminosity phase of the Large Hadron Collider.
Resistive Plate Chamber detectors are largely used in current High Energy Physics experiments, typically operated in avalanche mode with large fractions of Tetrafluoroethane (C2H2F4), a gas recently ...banned by the European Union due to its high Global Warming Potential (GWP). An intense R&D activity is ongoing to improve RPC technology in view of future HEP applications. In the last few years the RPC EcoGas@GIF++ Collaboration has been putting in place a joint effort between the ALICE, ATLAS, CMS, LHCb/SHiP and EP-DT Communities to investigate the performance of present and future RPC generations with eco-friendly gas mixtures. Detectors with different layout and electronics have been operated with ecological gas mixtures, with and without irradiation at the CERN Gamma Irradiation Facility (GIF++). Results of these performance studies together with plans for an aging test campaign are discussed in this article.
Resistive Plate Chambers (RPCs) are gaseous detectors widely used in high energy physics experiments, operating with a gas mixture primarily containing Tetrafluoroethane ...(C\(_{2}\)H\(_{2}\)F\(_{4}\)), commonly known as R-134a, which has a global warming potential (GWP) of 1430. To comply with European regulations and explore environmentally friendly alternatives, the RPC EcoGas@GIF++ collaboration, involving ALICE, ATLAS, CMS, LHCb/SHiP, and EP-DT communities, has undertaken intensive R\&D efforts to explore new gas mixtures for RPC technology. A leading alternative under investigation is HFO1234ze, boasting a low GWP of 6 and demonstrating reasonable performance compared to R-134a. Over the past few years, RPC detectors with slightly different characteristics and electronics have been studied using HFO and CO\(_{2}\)-based gas mixtures at the CERN Gamma Irradiation Facility. An aging test campaign was launched in August 2022, and during the latest test beam in July 2023, all detector systems underwent evaluation. This contribution will report the results of the aging studies and the performance evaluations of the detectors with and without irradiation.
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