The VIIRS-Based RST-FLARE configuration: The Val d'Agri Oil Center Gas Flaring Investigation in between 2015-2019

The RST (Robust Satellite Techniques)-FLARE algorithm is a satellite-based method using a multitemporal statistical analysis of nighttime infrared signals strictly related to industrial hotspots, such as gas flares. The algorithm was designed for both identifying and characterizing gas flares in terms of radiant/emissive power. The Val d'Agri Oil Center (COVA) is a gas and oil pre-treatment plant operating for about two decades within an anthropized area of Basilicata region (southern Italy) where it represents a significant potential source of social and environmental impacts. RST-FLARE, developed to study and monitor the gas flaring activity of this site by means of MODIS (Moderate Resolution Imaging Spectroradiometer) data, has exported VIIRS (Visible Infrared Imaging Radiometer Suite) records by exploiting the improved spatial and spectral properties offered by this sensor. In this paper, the VIIRS-based configuration of RST-FLARE is presented and its application on the recent (2015-2019) gas flaring activity at COVA is analyzed and discussed. Its performance in gas flaring characterization is in good agreement with VIIRS Nightfire outputs to which RST-FLARE seems to provide some add-ons. The great consistency of radiant heat estimates computed with both RST-FLARE developed configurations allows proposing a multi-sensor RST-FLARE strategy for a more accurate multi-year analysis of gas flaring

A Multi-Sensor Exportable Approach for Automatic Flooded Areas Detection and Monitoring by a Composite Satellite Constellation

Timely and frequently updated information about flood-affected areas and their space-time evolution are often crucial in order to correctly manage the emergency phases. In such a context, optical data provided by meteorological satellites, offering the highest available temporal resolution (from hours to minutes), could have a great potential. As cloud cover often occurs reducing the number of usable optical satellite images, an appropriate integration of observations coming from different satellite systems will surely improve the probability to find cloud-free images over the investigated region. To make this integration effective, appropriate satellite data analysis methodologies, suitable for providing congruent results, regardless of the used sensor, are envisaged. In this paper, a sensor-independent approach (RST, Robust Satellites Techniques-FLOOD) is presented and applied to data acquired by two different satellite systems (Advanced Very High Resolution Radiometer (AVHRR) onboard National Oceanic and Atmospheric Administration platforms and Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Earth Observing System satellites) at different spatial resolutions (from 1 km to 250 m) in the case of Elbe flood event occurred in Germany on August 2002. Results achieved demonstrated as the full integration of AVHRR and MODIS RST-FLOOD products allowed us to double the number of satellite passes daily available, improving continuity of monitoring over flood-affected regions. In addition, the application of RST-FLOOD to higher spatial resolution MODIS (250 m) data revealed to be crucial not only for mapping purposes but also for improving RST-FLOOD capability in identifying flooded areas not previously detected at lower spatial resolution

Integration of optical and passive microwave satellite data for flooded area detection and monitoring

Flooding represents a serious threat to millions of people around the world and its hazard is rising as a result of climate changes. From this perspective, flood risk management is a key focus of many governments, whose priority is to have frequently updated and accurate information about the flood state and evolution to promptly react to the disaster and to put in place effective countermeasures devoted to limit damages and human lives losses. Remote sensing technology allows for flood monitoring at different spatial and temporal resolutions with an adequate level of accuracy. In particular, for emergency response purposes, an integrated use of satellite data, acquired by both optical and passive or active microwave instruments, has to be preferred to have more complete and frequently updated information on soil conditions and to better support decision makers. In this framework, multi-year time series of MODIS (Moderate Resolution Imaging Spectroradiometer) and AMSR-E (Advanced Microwave Scanning Radiometer for Earth Observing System) data were processed and analyzed. In detail, the Robust Satellite Techniques (RST), a multi-sensor approach for satellite data analysis, has been implemented for studying the August 2002 Elbe river flood occurred in Germany, trying to assess the potential of such an integrated system for the determination of soil status and conditions (i.e. moisture variation, water presence) as well as for a timely detection and a near real time monitoring of critical soil conditions

Toward the estimation of river discharge variations using MODIS data in ungauged basins

This study investigates the capability of the Moderate resolution Imaging Spectroradiometer (MODIS) to estimate river discharge, even for ungauged sites. Because of its frequent revisits (as little as every 3 h) and adequate spatial resolution (250 m), MODIS bands 1 and 2 have significant potential for mapping the extent of flooded areas and estimating river discharge even for medium-sized basins. Specifically, the different behaviour of water and land in the Near Infrared (NIR) portion of the electromagnetic spectrum is exploited by computing the ratio (C/M) of the MODIS channel 2 reflectance values between two pixels located within (M) and outside (C), but close to, the river. The values of C/M increase with the presence of water and, hence, with discharge. Moreover, in order to reduce the noise effects due to atmospheric contribution, an exponential smoothing filter is applied, thus obtaining C/M⁎. Time series of hourly mean flow velocity and discharge between 2005 and 2011 measured at four gauging stations located along the Po river (Northern Italy) are employed for testing the capability of C/M⁎ to estimate discharge/flow velocity. Specifically, the meanders and urban areas are considered the best locations for the position of the pixels M and C, respectively. Considering the optimal pixels, the agreement between C/M⁎ and discharge/flow velocity is fairly good with values in the range of 0.65–0.77. Additionally, the application to ungauged sites is tested by deriving a unique regional relationship between C/M⁎ and flow velocity valid for the whole Po river and providing only a slight deterioration of the performance. Finally, the sensitivity of the results to the selection of the C and M pixels is investigated by randomly changing their location. Also in this case, the agreement with in situ observations of velocity is fairly satisfactory (r ~ 0.6). The obtained results demonstrate the capability of MODIS to monitor discharge (and flow velocity). Therefore, its application for a larger number of sites worldwide will be the object of future studies

LH receptor (LHR), Steroidogenic Acute Regulatory protein (StAR) and Mitochondrial Membrane Potential (MMP) in bovine granulosa cells are related to follicular size and atresia.

Granulosa cells (GC) play a key role in creating a suitable environment for the growth and the maturation of the oocyte as well as in determining the proper endocrine conditions for breeding and fertilization. However, only the GC of the ovulatory follicle have the opportunity to fully provide these tasks. Cumulus-oocyte complexes (COCs) used for in vitro embryo production (IVEP) are collected from follicles whose GC have not fully acquired or have lost these functions. This may be a reason of low IVEP efficiency. LH receptor (LHR), Steroidogenic Acute Regulatory protein (StAR) and Mitochondrial Membrane Potential (MMP) are direct or indirect markers of endocrine functions and putative candidates for evaluation of follicle quality. This study is aimed at evaluating the quality of GC of bovine ovarian follicles, classified according to their size and atresia grade, in order to provide new information to clarify the poor IVEP success. Bovine ovaries were collected from abattoir and transported to the lab at 4°C. Follicles were dissected, measured and classified according to their atresia grade (Kruip and Dieleman, 1982). The collected COCs were morphologically classified according to criteria related to follicular atresia (Boni et al., 2002). GC were obtained by scraping the follicular wall and filtered on a 50 μm nylon mesh. For each follicle, a part of GC was fixed with 2% paraformaldehyde for 1h. The remaining part was incubated with 5μM JC1 for 30 min followed by washing and reading with a spectrofluorometer (ex. 490 nm, em. 510 to 650 nm). Negative control samples were treated with 2 μM CCCP for 1 h before reading. The MMP values were expressed as the ratio between the fluorescence peaks at ~595 and ~525 nm. In fixed cells, immunofluorescence was carried out after treatment with blocking solution (20% Sea Block blocking buffer in PBS) with either anti-LH receptor antibodies (K-15) or anti-StAR antibodies (K-20) at 1:200 dilution for 90 min. After washing twice with TPBS (PBS + 0.05% Tween), the samples were incubated with secondary FITC-conjugated anti-goat antibodies. The samples were read at fluorescence microscope and the fluorescence intensity analyzed by ImageJ. Statistical analysis was carried out by ANOVA (Systat 11.0). Follicle size negatively affected (P< 0.01) the MMP as well as the expression of both LHR and StAR. Also the atresia grade, when evaluated on the basis of COC morphology, negatively influenced (P< 0.01) the expression of both LHR and StAR but positively influenced (P< 0.01) MMP. The evaluation of atresia grade on the basis of follicle morphology did not show significant effects on both LHR and StAR expression. These results highlight a discrepancy between the morphological characteristics of the follicle/COC and functionality of the GC, as previously demonstrated between COC quality and IVEP efficiency (Boni et al., 2002). Whereas the evaluated parameters represent markers of the steroidogenic activity, it is likely that the mechanisms of follicular regression pass through an upregulation of the GC metabolic activity

RST-BASED FLOODED AREA MAPPING AND MONITORING IN NEAR REAL-TIME BY USING MODIS DATA

Flood forecast and mitigation actions need updated and timely information about precise location, extent and dynamic evolution of the flooding event. Remote sensing technology, based on microwave and optical satellite data, is currently capable of giving reliable contributions towards a rapid detection of affected areas in order to improve flood hazards management and to study remote areas where ground-based observation systems are still lacking. For a near real time monitoring and mapping of flooded areas, fundamental during the crisis and post-crisis phases to support civil protection activities, frequent observations of the Earth’s surface can be derived from optical sensors aboard meteorological satellites. Recently, a new Robust Satellite Technique using AVHRR (Advanced very High Resolution Radiometer) observations has been proposed for mapping and monitoring flooded areas, providing good results. Afterwards, the same approach has been exported on MODIS (Moderate Resolution Imaging Spectroradiometer) data, in order to investigate if its higher spatial resolution in visible and near-infrared channels might be exploited to increase the accuracy in both near real time detection and mapping of flooded areas. Preliminary results confirmed the reliability and the sensitivity of the proposed approach but further analyses have to be carried out in order to better assess the actual reliability and efficiency of such a technique. To this aim, in this paper, the extreme flooding event which hit wide territories of Germany and Czech Republic, during the August 2002, has been studied

A comprehensive analysis of AMSRE C- and X-bands Radio Frequency Interferences

The Advanced Microwave Scanning Radiometer (AMSRE) on Earth Observing System (EOS) Aqua was able to acquire global microwave data for nearly nine years, from June 2002 to October 2011. During its operational phase, the main problem of data quality was due to the Radio Frequency Interference (RFI), which contaminated data acquired at C- and, with less relevance, X-bands. In this work, the multi-temporal Robust Satellite Techniques (RST) approach has been applied to automatically identify areas systematically affected by RFI, contaminating C- and X-band AMSRE radiances. With the scope of producing reliable RFI exclusion maps at global scale, data acquired globally from June 2002 to June 2011 were analyzed. © 2012 IEEE

On the potential of multi-temporal analysis of MODIS and AVHRR data for near real time mapping and monitoring of flooded areas

Floods are devastating natural disasters which may cause very high costs in lives and damages. Among the other potential contributes, satellite remote sensing may help for mapping and monitoring flooded areas. In order to support flood risk management, information coming from satellite, especially during crisis phases, need to be timely provided. Besides, suitable techniques, able to reliably detect flooded areas with a low rate of false alarms, are requested. In this context, a new technique using visible AVHRR data has been recently proposed. In this work, in order to further confirm the reliability and the sensitivity of the proposed approach we analyze the August 2002 flood which hit wide territories of Germany. Afterwards, we exported this approach on MODIS data, in order to exploit the higher spatial resolution in the visible and near-infrared channels offered by such a sensor, for increasing the accuracy in both near real time flooded area mapping and monitorin