Search Results (260)

Different monitoring approaches and techniques have been adopted to estimate and prevent soil erosion and its corresponding phenomena at cultural heritage sites. Remote sensing plays a crucial role in detecting and monitoring soil erosion events by providing a wealth of geospatial data and information that helps to better understand and respond to the mechanisms of soil erosion and mitigate or reduce its impacts. The main aims of this review are to (1) provide an overview of remote sensing methods, applications, and sensor types, (2) discuss the role of remote sensing in the estimation of soil erosion at cultural heritage sites, and (3) present a bibliometric analysis of soil erosion studies at cultural heritage sites covering the period from 1994 to 2025. The results of this study provide insights into the yearly scientific production, methods employed, topics, and trends in this field. This research offers valuable information for future research and the development and promotion of policies and strategies for the effective and sustainable management of cultural heritage sites. Full article

Biomass burning processes affect many semi-rural areas in the Mediterranean, but there is a lack of long-term datasets focusing on their classification, obtained by monitoring carbonaceous particle concentrations and optical properties variations. To address this issue, a campaign to measure equivalent black carbon (eBC) and particle number size distributions (0.3–10 μm) was carried out from August 2019 to November 2020 at a coastal semi-rural site in the Basilicata region of Southern Italy. Long-term datasets were useful for aerosol characterization, helping to clearly identify traffic as a constant eBC source. For a shorter period, PM_2.5 mass concentrations were also measured, allowing the estimation of elemental and organic carbon (EC and OC), and chemical and SEM (scanning electron microscope) analysis of aerosols collected on filters. This multi-instrumental approach enabled the discrimination among different biomass burning (BB) processes, and the analysis of three case studies related to domestic heating, regional smoke plume transport, and a local smoldering process. The AAE (Ångström absorption exponent) daily pattern was characterized as having a peak late in the morning and mean hourly values that were always higher than 1.3. Full article

A temporal monitoring of monumental buildings in calcarenite, exposed outdoors in the considered Mediterranean environment of Southern Italy, was performed using XPS, the surface-specific technique. The methodology adopted to monitor the surfaces interacting with atmospheric agents and biotic/abiotic pollutants involved progressive sampling, extended to about five years, from the walls of a new building, specifically installed in the immediate vicinity of an ancient farmhouse in an advanced state of degradation. Taking the ancient building as the final temporal reference, the aim was to obtain adequate information on the degradation processes of calcarenitic stones, from the initial and evolving phases of the new building towards those representative of the old reference. A large set of XPS data was obtained by resolving, through curve-fitting, the acquired spectra into component peaks, identified as ‘indicator’ chemical groups, which trend as a function of time, supported by PCA, demonstrates a close compositional similarity between the samples of the new building analyzed after 52 months from its installation and those of the ancient building dating back to over a century ago. The results obtained can be considered in the diagnostic strategy of the ongoing PNRR programs dedicated to the care of historical monuments and ecosystem sustainability. Full article

Ultrasonic pulse velocity (UPV) is a widely used technique for diagnosis and structural safety assessment of existing buildings. The main difficulties in UPV tests on-site are due to one-sided accessibility of materials and degraded/irregular surfaces. Pulse-echo ultrasonic tomography (PE-UT) can overcome the problem. Though it has been widely applied for detecting inhomogeneities within concrete, few works use the instrument to assess UPV. The present paper aims to fill the gap by comparing PE-UT results with those of through-transmission ultrasonic tests (TT-UT) commonly used for UPV characterization. TT-UT measurements were performed with cylindrical and exponential transducers. The latter are used on irregular surfaces or when coupling gel is forbidden. Few data are in the literature comparing exponential and cylindrical transducers’ results. This is a further element of novelty of the paper. PE-UT and TT-UT results were compared considering the effect of material compositeness, water, transmission mode, and transducer type. It was found that PE-UT allows for reliable and rapid one-sided measurements on concrete and stone in different conditions. The differences between PE-UT and TT-UT results were between 1 and 3%. Exponential transducers gave reliable results on fine-grained stone in direct transmission, with differences lower than 4% with cylindrical transducer results. Full article

Groundwater storage refers to the water stored in the pore spaces of underground aquifers, which has been increasingly affected by both climate change and anthropogenic activities in recent decades. Therefore, monitoring their changes and the factors that affect it is of great importance. Although the influence of natural factors on groundwater is well-recognized, the impact of human activities, despite being a major contributor to its change, has been less explored due to the challenges in measuring such effects. To address this gap, our study employed an integrated approach using remote sensing and the Google Earth Engine (GEE) cloud-free platform to analyze the effects of various anthropogenic factors such as built-up areas, cropland, and surface water on groundwater storage in the Lake Urmia Basin (LUB), Iran. Key anthropogenic variables and groundwater data were pre-processed and analyzed in GEE for the period from 2000 to 2022. The processes linking these variables to groundwater storage were considered. Built-up area expansion often increases groundwater extraction and reduces recharge due to impervious surfaces. Cropland growth raises irrigation demand, especially in semi-arid areas like the LUB, leading to higher groundwater use. In contrast, surface water bodies can supplement water supply or enhance recharge. The results were then exported to XLSTAT software2019, and statistical analysis was conducted using the Mann–Kendall (MK) non-parametric trend test on the variables to investigate their potential relationships with groundwater storage. In this study, groundwater storage refers to variations in groundwater storage anomalies, estimated using outputs from the Global Land Data Assimilation System (GLDAS) model. Specifically, these anomalies are derived as the residual component of the terrestrial water budget, after accounting for soil moisture, snow water equivalent, and canopy water storage. The results revealed a strong negative correlation between built-up areas and groundwater storage, with a correlation coefficient of −1.00. Similarly, a notable negative correlation was found between the cropland area and groundwater storage (correlation coefficient: −0.85). Conversely, surface water availability showed a strong positive correlation with groundwater storage, with a correlation coefficient of 0.87, highlighting the direct impact of surface water reduction on groundwater storage. Furthermore, our findings demonstrated a reduction of 168.21 mm (millimeters) in groundwater storage from 2003 to 2022. GLDAS represents storage components, including groundwater storage, in units of water depth (mm) over each grid cell, employing a unit-area, mass balance approach. Although storage is conceptually a volumetric quantity, expressing it as depth allows for spatial comparison and enables conversion to volume by multiplying by the corresponding surface area. Full article

The Flexible Combined Imager (FCI) instrument aboard the Meteosat Third Generation (MTG-I) geostationary satellite, launched in December 2022 and operational since September 2024, by providing shortwave infrared (SWIR), medium infrared (MIR) and thermal infrared (TIR) data, with an image refreshing time of 10 min and a spatial resolution ranging between 500 m in the high-resolution (HR) and 1–2 km in the normal-resolution (NR) mode, may represent a very promising instrument for monitoring thermal volcanic activity from space, also in operational contexts. In this work, we assess this potential by investigating the recent Mount Etna (Italy, Sicily) eruption of February–March 2025 through the analysis of daytime and night-time SWIR observations in the NR mode. The time series of a normalized hotspot index retrieved over Mt. Etna indicates that the effusive eruption started on 8 February at 13:40 UTC (14:40 LT), i.e., before information from independent sources. This observation is corroborated by the analysis of the MIR signal performed using an adapted Robust Satellite Technique (RST) approach, also revealing the occurrence of less intense thermal activity over the Mt. Etna area a few hours before (10.50 UTC) the possible start of lava effusion. By analyzing changes in total SWIR radiance (TSR), calculated starting from hot pixels detected using the preliminary NHI algorithm configuration tailored to FCI data, we inferred information about variations in thermal volcanic activity. The results show that the Mt. Etna eruption was particularly intense during 17–19 February, when the radiative power was estimated to be around 1–3 GW from other sensors. These outcomes, which are consistent with Multispectral Instrument (MSI) and Operational Land Imager (OLI) observations at a higher spatial resolution, providing accurate information about areas inundated by the lava, demonstrate that the FCI may provide a relevant contribution to the near-real-time monitoring of Mt. Etna activity. The usage of FCI data, in the HR mode, may further improve the timely identification of high-temperature features in the framework of early warning contexts, devoted to mitigating the social, environmental and economic impacts of effusive eruptions, especially over less monitored volcanic areas. Full article

Soil moisture (SM) plays a fundamental role in the water cycle and is an important variable for all processes occurring at the lithosphere–atmosphere interface, which are strongly affected by climate change. Among the different fields of application, accurate SM measurements are becoming more relevant for all studies related to extreme event (e.g., floods, droughts, and landslides) mitigation and assessment. In this study, data acquired by the advanced microwave sounding unit (AMSU) onboard the European Meteorological Operational Satellite Program (MetOP) satellites were used for the first time to extract information on the variability of SM by implementing the original soil wetness index (SWI). Long-term monthly SWI time series collected for the Basilicata region (southern Italy) were analyzed for drought assessment during the period 2007–2021. The accuracy of the SWI product was tested through a comparison with SM products derived by the Advanced SCATterometer (ASCAT) over the 2013–2016 period, while the Standardized Precipitation-Evapotranspiration Index (SPEI) was used to assess the relevance of the long-term achievements in terms of drought analysis. The results indicate a satisfactory accuracy of the SWI, with the mean correlation coefficient values with ASCAT higher than 0.7 and a mean normalized root mean square error less than 0.155. A negative trend in SWI during the 15-year period was found using both the original and deseasonalized series (linear and Sen’s slope ~−0.00525), confirmed by SPEI (linear and Sen’s slope ~−0.00293), suggesting the occurrence of a marginal long-term dry phase in the region. Although further investigations are needed to better assess the intensity and main causes of the phenomena, this result indicates the contribution that satellite data/products can offer in supporting drought assessment. Full article

Accurate estimation of soil moisture content (SMC) is crucial for effective water management, enabling improved monitoring of water stress and a deeper understanding of hydrological processes. While satellite remote sensing provides broad coverage, its spatial resolution often limits its ability to capture small-scale variations in SMC, especially in landscapes with diverse land-cover types. Unmanned aerial vehicles (UAVs) equipped with hyperspectral sensors offer a promising solution to overcome this limitation. This study compares the effectiveness of Sentinel-2, Landsat-8/9 multispectral data and UAV hyperspectral data (from 339.6 nm to 1028.8 nm with spectral bands) in estimating SMC in a research farm consisting of bare soil, cropland and grassland. A DJI Matrice 100 UAV equipped with a hyperspectral spectrometer collected data on 14 field campaigns, synchronized with satellite overflights. Five machine-learning algorithms including extreme learning machines (ELMs), Gaussian process regression (GPR), partial least squares regression (PLSR), support vector regression (SVR) and artificial neural network (ANN) were used to estimate SMC, focusing on the influence of land cover on the accuracy of SMC estimation. The findings indicated that GPR outperformed the other models when using Landsat-8/9 and hyperspectral photography data, demonstrating a tight correlation with the observed SMC (R² = 0.64 and 0.89, respectively). For Sentinel-2 data, ELM showed the highest correlation, with an R² value of 0.46. In addition, a comparative analysis showed that the UAV hyperspectral data outperformed both satellite sources due to better spatial and spectral resolution. In addition, the Landsat-8/9 data outperformed the Sentinel-2 data in terms of SMC estimation accuracy. For the different land-cover types, all types of remote-sensing data showed the highest accuracy for bare soil compared to cropland and grassland. This research highlights the potential of integrating UAV-based spectroscopy and machine-learning techniques as complementary tools to satellite platforms for precise SMC monitoring. The findings contribute to the further development of remote-sensing methods and improve the understanding of SMC dynamics in heterogeneous landscapes, with significant implications for precision agriculture. By enhancing the SMC estimation accuracy at high spatial resolution, this approach can optimize irrigation practices, improve cropping strategies and contribute to sustainable agricultural practices, ultimately enabling better decision-making for farmers and land managers. However, its broader applicability depends on factors such as scalability and performance under different conditions. Full article

Laser nanostructuring via Laser-Induced Periodic Surface Structures (LIPSS), generated using femtosecond laser pulses, has been investigated as a method for precisely modifying titanium surfaces. By adjusting parameters such as the fluence and pulse number of the laser beam, it is feasible to tailor the surface morphology, roughness, and oxidation states of species that can significantly influence the properties and surface bioactivity of the material. In this study, the LIPSS was applied to commercially pure titanium and evaluated for its ability to support calcium phosphate nucleation and growth in Simulated Body Fluid (SBF). Scanning Electron Microscopy (SEM) and Fast Fourier Transform (FFT) analysis confirmed the formation of well-defined periodic structures. Additional characterizations performed by Atomic Force Microscopy (AFM) and X-ray Photoelectron Spectroscopy (XPS) revealed, after laser treatment of titanium, its increased surface roughness and oxidation levels, respectively. These features, when assessed after immersion in SBF, were associated with an improved potential biological performance of the nanostructured surface of the investigated material. The results demonstrated that LIPSS-treated titanium effectively promoted calcium phosphate growth, indicating its enhanced potential bioactivity. Overall, LIPSS nanostructuring presents a scalable and cost-effective strategy for engineering titanium surfaces with potential bioactive properties, supporting their promising application in advanced biomedical implants. Full article

The abandonment of farmland in Europe is a significant issue due to its environmental, socio-economic, and landscape consequences. This tendency mainly impacts marginal and inner areas, located far from large urban districts, because of biophysical and/or socio-economic factors. Although European and national regulations try to turn the fragility of these territories into an opportunity for sustainable development, many of these areas, especially in southern Europe, continue to suffer socio-economic disparities. For this reason, it is necessary to consider regional and district-wide initiatives that can economically revitalize marginal areas while safeguarding their natural capital. Alternative cropping systems, capable of optimizing the quality of some food crops, can play an essential role in the economic development of populations living in marginal areas. These areas, represented by inland zones often abandoned due to the difficulty of applying mechanized agriculture, can represent an opportunity to rediscover sustainable and profitable practices. Among the high-value crops, saffron (Crocus sativus L.), “red gold” and “king of spices”, stands out for its potential. Indeed, thanks to the use of tuff tubs, a more eco-sustainable choice compared to the plastic pots already mentioned in the literature, it is possible to improve the quality of this spice. Furthermore, Crocus sativus L. not only lends itself to multiple uses but also represents a valid opportunity to supplement agricultural income. This is made possible by its high profitability and beneficial properties for human health, offering a way to diversify agricultural production with positive economic and social impacts. It is known that the saffron market in Italy suffers from competition from developing countries (Iran, Morocco, India) capable of producing saffron at lower costs than European countries, thanks to the lower cost of labor. Therefore, this study seeks to identify marginal areas that can be recovered and valorized through an eco-sustainable cultivation system with the potential to enhance the quality of this spice, making it unique and resilient to competition. Specifically, this paper is organized on a dual scale of investigation: (a) at the local level to demonstrate the economic-ecological feasibility of saffron cultivation through the adoption of an alternative farming technique on an experimental site located in Tricarico (Basilicata—Southern Italy, 40°37′ N, 16°09′ E; 472 m. a.s.l.) that, although fertile, is not suitable for mechanized cropping systems; (b) at the regional level through a spatially explicit land suitability analysis to indicate the possible location where to export saffron cultivation. The final map, obtained by combining geo-environmental variables, can be considered a precious tool to support policymakers and farmers to foster a broad agricultural strategy founded on new crop management systems. The adoption of this alternative agroecological system could optimize the use of land resources in the perspective of increasing crop productivity and profitability in marginal agricultural areas. Full article

The deterioration of stone materials due to atmospheric factors is a growing global concern, affecting the integrity and preservation of numerous UNESCO World Heritage Sites around the world. This study provides an estimate of the long-term impact of the climate on the degradation of carbonate stone materials in the UNESCO site of Matera, in southern Italy. Focusing on Gravina calcarenite, a lithotype susceptible to weathering, the research integrates satellite-derived precipitation data from the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) with a dose-response model. The method involves the calibration of CHIRPS precipitation records against ground-based meteorological data, and the use of year-specific recession coefficients K_y dynamically computed as a function of atmospheric CO₂ concentration and temperature. These coefficients were applied within a Lipfert-based equation to estimate annual surface recession from 1981 to 2040 (near future). The results reveal a continuous increase in surface degradation over time, with the cumulative material loss reaching approximately 0.75 mm by 2040. These findings underscore the relevance of climate-responsive models in estimating stone decay and provide a critical basis for adaptive conservation planning. Incorporating future climate projections into risk assessments is essential for the sustainable preservation of carbonate-based cultural heritage exposed to atmospheric and hydrological stressors. Full article

This study introduces a methodology for the improvement of the visibility of archaeological features using an open-source probabilistic machine learning framework applied to UAV LiDAR data from the Torre Castiglione site in Apulia, Italy. By leveraging a Random Forest classification algorithm embedded in an open-source software, the approach processes dense LiDAR point clouds to segment out vegetation from the ground and the structures. Key steps include training the classifier, generating digital terrain models, digital feature models, and digital surface models, and enhancing the visibility of archaeological features. This method has proven effective in improving the interpretation of archaeological sites, revealing previously hidden or difficult-to-access microtopographic and structural details, such as the defensive structures, terraces, and ancient paths of the Torre Castiglione site. The results underline this methodology’s ease of use in uncovering archaeological landscapes under a dense canopy. Moreover, the study emphasises the benefits of using open-source tools to enhance the documentation and analysis of remote or difficult archaeological sites. Full article

Every year about fifty volcanoes erupt on average, posing a serious threat for populations living in the neighboring areas. To mitigate the volcanic risk, many satellite monitoring systems have been developed. Information from the medium infrared (MIR) and thermal infrared (TIR) bands of sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) is commonly exploited for this purpose. However, the potential of daytime shortwave infrared (SWIR) observations from the Sea and Land Surface Temperature Radiometer (SLSTR) aboard Sentinel-3 satellites in supporting the near-real-time monitoring of thermal volcanic activity has not been fully evaluated so far. In this work, we assess this potential by exploring the contribution of a normalized hotspot index (NHI) in the monitoring of the recent Home Reef (Tonga Islands) eruption. By analyzing the time series of the maximum NHI_SWIR value, computed over the Home Reef area, we inferred information about the waxing/waning phases of lava effusion during four distinct subaerial eruptions. The results indicate that the first eruption phase (September–October 2022) was more intense than the second one (September–November 2023) and comparable with the fourth eruptive phase (June–August 2024) in terms of intensity level; the third eruption phase (January 2024) was more difficult to investigate because of cloudy conditions. Moreover, by adapting the NHI algorithm to daytime SLSTR SWIR data, we found that the detected thermal anomalies complemented those in night-time conditions identified and quantified by the operational Level 2 SLSTR fire radiative power (FRP) product. This study demonstrates that NHI-based algorithms may contribute to investigating active volcanoes located even in remote areas through SWIR data at 500 m spatial resolution, encouraging the development of an automated processing chain for the near-real-time monitoring of thermal volcanic activity by means of night-time/daytime Sentinel-3 SLSTR data. Full article

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy characterized by poor prognosis, therapeutic resistance, and frequent recurrence. Current therapeutic options for PDAC include surgery, radiotherapy, immunological and targeted approaches. However, all these therapies provide only a slight improvement in patient survival. Consequently, the discovery of novel specific targets is becoming a priority to develop more effective treatments for PDAC. Mucin 1 (MUC1), a transmembrane glycoprotein, is aberrantly glycosylated and frequently overexpressed in pancreatic cancer. Recent studies highlighted the role of this oncoprotein in pancreatic carcinogenesis and its involvement in the acquisition of typical aggressive features of PDAC, like local invasion, metastases, and drug resistance. This review explores the mechanisms by which MUC1 contributes to cancer onset and progression, with a focus on its potential role as a biomarker and novel therapeutic target for pancreatic adenocarcinoma treatment. Full article

Plant biostimulants are used to promote plant growth by increasing tolerance to abiotic stressors and improving the efficiency of natural resource use. In the present two-year research (2022–2023 and 2023–2024), the effects of biostimulant foliar applications on the morphological parameters, fresh and dry yields, antioxidant capacity, total phenolic content, and chemical composition of the essential oil of thyme (Thymus vulgaris L.) were studied. For this purpose, four commercial biostimulants, Biostimol Plus + Peptamin-V Plus^®, Acadian MPE^®, Megafol^®, and BlueN^®, were evaluated on thyme cultivated in field conditions. The experiment was laid out in a randomized block design with five treatments and with three replications. During the second growing season, the plants treated with BlueN^®, composed of the bacteria Methylobacterium symbioticum SB23, showed the highest plant weight (152.1 g plant⁻¹), fresh biomass yield (501.9 g m⁻²), and dry yield (172.2 g m⁻²). BlueN^® was the biostimulant that also obtained the highest essential oil yield in both years (0.47 and 0.53%), and for all biostimulants, the amount of thymol and carvacrol increased in the second year, especially with Megafol^® (63.75 and 3.16%). The antioxidant capacity was enhanced in the second year by all biostimulants, according to the ABTS assay, but in particular, by BlueN^® and BPPVP (26.97 μmol/g and 25.01 μmol/g), while the phenolic content was higher in the first year, especially with BlueN^® (65.98 mg GAE/g Extract). The other biostimulants had less intense effects. In conclusion, the biostimulants influenced some characteristics of the essential oil, but the greatest influencers were BlueN^®, Megafol^®, and BPPVP. Full article