High resolution fire hazard index based on satellite images

In December 2015, after 3 year of activity, the FP7 project PREFER (Space-based Information Support for Prevention and REcovery of Forest Fires Emergency in the MediteRranean Area) came to an end. The project was designed to respond to the need to improve the use of satellite images in applications related to the emergency services, in particular, to forest fires. The project aimed at developing, validating and demonstrating information products based on optical and SAR (Synthetic Aperture Radar) imagery for supporting the prevention of forest fires and the recovery/damage assessment of burnt area. The present paper presents an improved version of one of the products developed under the PREFER project, which is the Daily Fire Hazard Index (DFHI)

Oil spill detection using optical sensors: a multi-temporal approach

Oil pollution is one of the most destructive consequences due to human activities in the marine environment. Oil wastes come from many sources and take decades to be disposed of. Satellite based remote sensing systems can be implemented into a surveillance and monitoring network. In this study, a multi-temporal approach to the oil spill detection problem is investigated. Change Detection (CD) analysis was applied to MODIS/Terra and Aqua and OLI/Landsat 8 images of several reported oil spill events, characterized by different geographic location, sea conditions, source and extension of the spill. Toward the development of an automatic detection algorithm, a Change Vector Analysis (CVA) technique was implemented to carry out the comparison between the current image of the area of interest and a dataset of reference image, statistically analyzed to reduce the sea spectral variability between different dates. The proposed approach highlights the optical sensors’ capabilities in detecting oil spills at sea. The effectiveness of different sensors’ resolution towards the detection of spills of different size, and the relevance of the sensors’ revisiting time to track and monitor the evolution of the event is also investigated

A small satellite mission devoted to mid-low latitude earth observation

This paper aims at assessing the feasibility of a small mission devoted to observe the mid-low latitude regions. The satellite will be equipped with three optical sensors: a medium-high spatial resolution VIS-NIR multi-spectral sensor, allowing the surface monitoring and land-use and land-cover studies; a medium spatial-resolution 3-bands thermal (MIR-TIR) sensor allowing the surface temperature (LST, SST) estimate and hot-spots (fires, volcanic eruption, etc.) detection; a panchromatic VIS-NIR camera for night-time observation able to reveal artificial and natural lights. The selected orbit, called multi-sun-synchronous (MSS), represents an innovation with respect to the classical sun-synchronous orbit much suitable for observing tropical regions, allowing an enhanced revisit frequency. Further, such an orbit allows the observation of the same region of the Earth at different local-time. In this way, the diurnal cycle of surface temperatures can be reconstructed with a 2-hours local-time step. An analysis of the capability of the selected ground stations to acquire the data gathered by the remote sensing sensors has been carried out. Orbital perturbations have been taken into account and an estimate of the propellant required for ground track control has been performed in order to verify its compatibility with a small mission requirements

Oil Spill Detection Analyzing “Sentinel 2“ Satellite Images: A Persian Gulf Case Study

Oil spills near exploitation areas and oil loading ports are often related to the ambitions of governments to get more oil market share and the negligence at the time of the loading in large tankers or ships. The present study investigates one oil spill event using multi sensor satellite images in the Al Khafji (between Kuwait and Saudi Arabia) zone. Oil slicks have been characterized with multi sensor satellite images over the Persian Gulf and then analyzed in order to detect and classify oil spills in this zone. In particular this paper discusses oil pollution detection in the Persian Gulf by using multi sensor satellite images data. Oil spill images have been selected by using Sentinel 2 images pinpointing oil spill zones. ENVI software for analysing satellite images and ADIOS (Automated Data Inquiry for Oil Spills) for oil weathering modelling have been used. The obtained results in Al Khafji zone show that the oil spill moves towards the coastline firstly increasing its surface and then decreasing it until reaching the coastline

Enhancing Surface Soil Moisture Estimation through Integration of Artificial Neural Networks Machine Learning and Fusion of Meteorological, Sentinel-1A and Sentinel-2A Satellite Data

For many environmental and agricultural applications, an accurate estimation of surface soil moisture is essential. This study sought to determine whether combining Sentinel-1A, Sentinel-2A, and meteorological data with artificial neural networks (ANN) could improve soil moisture estimation in various land cover types. To train and evaluate the model’s performance, we used field data (provided by La Tuscia University) on the study area collected during time periods between October 2022, and December 2022. Surface soil moisture was measured at 29 locations. The performance of the model was trained, validated, and tested using input features in a 60:10:30 ratio, using the feed-forward ANN model. It was found that the ANN model exhibited high precision in predicting soil moisture. The model achieved a coefficient of determination (R2) of 0.71 and correlation coefficient (R) of 0.84. Furthermore, the incorporation of Random Forest (RF) algorithms for soil moisture prediction resulted in an improved R2 of 0.89. The unique combination of active microwave, meteorological data and multispectral data provides an opportunity to exploit the complementary nature of the datasets. Through preprocessing, fusion, and ANN modeling, this research contributes to advancing soil moisture estimation techniques and providing valuable insights for water resource management and agricultural planning in the study area

Derivation of Land Surface Temperature from MODIS Data Using the General Split Window Technique

Fast Atmospheric Signature Code (FASCODE), a line-by-line radiative transfer programme, was used to simulate Moderate Resolution Imaging Spectroradiometer (MODIS) data at wavelengths 11.03 and 12.02 mm to ascertain how accurately the land surface temperature (LST) can be inferred, by the split window technique (SWT), for a wide range of atmospheric and terrestrial conditions. The approach starts from the Ulivieri algorithm, originally applied to Advanced Very High Resolution Radiometer (AVHRR) channels 4 and 5. This algorithm proved to be very accurate compared to several others and takes into account the atmospheric effects, in particular the water vapour column (WVC) amount and a non-unitary surface emissivity. Extended simulations allowed the determination of new coefficients of this algorithm appropriate to MODIS bands 31 and 32, using different atmospheric conditions. The algorithm was also improved by removing some of the hypothesis on which its original expression was based. This led to the addition of a new corrective term that took into account the interdependence between water vapour and non-unitary emissivity values and their effects on the retrieved surface temperature. The LST products were validated within 1K with in situ LSTs in 11 cases

Presenting a Semi-Automatic, Statistically-Based Approach to Assess the Sharpness Level of Optical Images from Natural Targets via the Edge Method. Case Study: The Landsat 8 OLI–L1T Data

Developing reliable methodologies of data quality assessment is of paramount importance for maximizing the exploitation of Earth observation (EO) products. Among the different factors influencing EO optical image quality, sharpness has a relevant role. When implementing on-orbit approaches of sharpness assessment, such as the edge method, a crucial step that strongly affects the final results is the selection of suitable edges to use for the analysis. Within this context, this paper aims at proposing a semi-automatic, statistically-based edge method (SaSbEM) that exploits edges extracted from natural targets easily and largely available on Earth: agricultural fields. For each image that is analyzed, SaSbEM detects numerous suitable edges (e.g., dozens-hundreds) characterized by specific geometrical and statistical criteria. This guarantees the repeatability and reliability of the analysis. Then, it implements a standard edge method to assess the sharpness level of each edge. Finally, it performs a statistical analysis of the results to have a robust characterization of the image sharpness level and its uncertainty. The method was validated by using Landsat 8 L1T products. Results proved that: SaSbEM is capable of performing a reliable and repeatable sharpness assessment; Landsat 8 L1T data are characterized by very good sharpness performance

Validation of sentinel-2 leaf area index (LAI) product derived from SNAP toolbox and its comparison with global LAI products in an African semi-arid agricultural landscape

This study validated SNAP-derived LAI from Sentinel-2 and its consistency with existing global LAI products. The validation and intercomparison experiments were performed on two processing levels, i.e., Top-of-Atmosphere and Bottom-of-Atmosphere reflectances and two spatial resolutions, i.e., 10 m, and 20 m. These were chosen to determine their effect on retrieved LAI accuracy and consistency. The results showed moderate R2, i.e., ~0.6 to ~0.7 between SNAPderived LAI and in-situ LAI, but with high errors, i.e., RMSE, BIAS, and MAE >2 m2 m–2 with marked differences between processing levels and insignificant differences between spatial resolutions. In contrast, inter-comparison of SNAP-derived LAI with MODIS and Proba-V LAI products revealed moderate to high consistencies, i. e., R2 of ~0.55 and ~0.8 respectively, and RMSE of ~0.5 m2 m–2 and ~0.6 m2 m–2, respectively. The results in this study have implications for future use of SNAP-derived LAI from Sentinel-2 in agricultural landscapes, suggesting its global applicability that is essential for large-scale agricultural monitoring. However, enormous errors in characterizing field-level LAI variability indicate that SNAP-derived LAI is not suitable for precision farming. In fact, from the study, the need for further improvement of LAI retrieval arises, especially to support farm-level agricultural management decisions

A Common Approach to Foster Prevention and Recovery of Forest Fires in Mediterranean Europe

Most countries of Mediterranean Europe are strongly affected by forest fires, with major socio-economic and environmental impacts that can spread over several regions and countries. A transnational approach allows creating synergies regarding resource sharing and problem-solving strategies. The access to high quality and up-to-date information is critical to improve fire hazard mitigation measures and promote comparable appraisals between different regions. Several collaborative initiatives have been implemented in Europe to foster research and service development, focusing on common issues amongst countries. The PREFER project was one of these initiatives, with the purpose of contributing to protect human communities and forests from fire hazard, by providing cartographic products through the implementation of a new systematic framework. The participation of end users, such as civil protection organizations and forest services, covering the Euro-Mediterranean region, was crucial to ensure the operational application of the mapping products. Fuel classification, daily fire hazard indices, vulnerability assessment and damage severity levels were some of the mapping applications developed for several test areas in Mediterranean Europe. This chapter illustrates the potential enhancements for forest fire management offered by this framework, bearing in mind the benefits of applying shared and harmonized approaches for common issues

Direct Anterior versus Lateral Approach for Femoral Neck Fracture: Role in COVID-19 Disease

Background: During the COVID-19 emergency, the incidence of fragility fractures in elderly patients remained unchanged. The management of these patients requires a multidisciplinary approach. The study aimed to assess the best surgical approach to treat COVID-19 patients with femoral neck fracture undergoing hemiarthroplasty (HA), comparing direct lateral (DL) versus direct anterior approach (DAA). Methods: A single-center, observational retrospective study including 50 patients affected by COVID-19 infection (30 males, 20 females) who underwent HA between April 2020 to April 2021 was performed. The patients were allocated into two groups according to the surgical approach used: lateral approach and anterior approach. For each patient, the data were recorded: age, sex, BMI, comorbidity, oxygen saturation (SpO2), fraction of the inspired oxygen (FiO2), type of ventilation invasive or non-invasive, HHb, P/F ratio (PaO2/FiO2), hemoglobin level the day of surgery and 1 day post operative, surgical time, Nottingham Hip Fractures Score (NHFS) and American Society of Anesthesiologists Score (ASA). The patients were observed from one hour before surgery until 48 h post-surgery of follow-up. The patients were stratified into five groups according to Alhazzani scores. A non-COVID-19 group of patients, as the control, was finally introduced. Results: A lateral position led to a better level of oxygenation (p < 0.01), compared to the supine anterior approach. We observed a better post-operative P/F ratio and a reduced need for invasive ventilation in patients lying in the lateral position. A statistically significant reduction in the surgical time emerged in patients treated with DAA (p < 0.01). Patients within the DAA group had a significantly lower blood loss compared to direct lateral approach. Conclusions: DL approach with lateral decubitus seems to preserved respiratory function in HA surgery. Thus, the lateral position may be associated with beneficial effects on gas exchange