Monitoring soil wetness variations by means of satellite passive microwave observations: the HYDROPTIMET study cases

Soil moisture is an important component of the hydrological cycle. In the framework of modern flood warning systems, the knowledge of soil moisture is crucial, due to the influence on the soil response in terms of infiltration-runoff. Precipitation-runoff processes, in fact, are related to catchment's hydrological conditions before the precipitation. Thus, an estimation of these conditions is of significant importance to improve the reliability of flood warning systems. Combining such information with other weather-related satellite products (i.e. rain rate estimation) might represent a useful exercise in order to improve our capability to handle (and possibly mitigate or prevent) hydro-geological hazards. <P style='line-height: 20px;'> Remote sensing, in the last few years, has supported several techniques for soil moisture/wetness monitoring. Most of the satellite-based techniques use microwave data, thanks to the all-weather and all-time capability of these data, as well as to their high sensitivity to water content in the soil. On the other hand, microwave data are unfortunately highly affected by the presence of surface roughness or vegetation coverage within the instantaneous satellite field of view (IFOV). Those problems, consequently, strongly limit the efficiency and the reliability of traditional satellite techniques. <P style='line-height: 20px;'> Recently, using data coming from AMSU (Advanced Microwave Sounding Unit), flying aboard NOAA (National Oceanic and Atmospheric Administration) satellites, a new methodology for soil wetness estimation has been proposed. The proposed index, called Soil Wetness Variation Index (<I>SWVI</I>), developed by a multi-temporal analysis of AMSU records, seems able to reduce the problems related to vegetation and/or roughness effects. Such an approach has been tested, with promising results, on the analysis of some flooding events which occurred in Europe in the past. <P style='line-height: 20px;'> In this study, results achieved for the HYDROPTIMET test cases will be analysed and discussed in detail. This analysis allows us to evaluate the reliability and the efficiency of the proposed technique in identifying different amounts of soil wetness variations in different observational conditions. In particular, the proposed indicator was able to document the actual effects of meteorological events, in terms of space-time evolution of soil wetness changes, for all the analysed HYDROPTIMET test cases. Moreover, in some circumstances, the <I>SWVI</I> was able to identify the presence of a sort of 'early' signal in terms of soil wetness variations, which may be regarded as a timely indication of an anomalous value of soil water content. This evidence suggests the opportunity to use such an index in the pre-operational phases of the modern flood warning systems, in order to improve their forecast capabilities and their reliability

Assessment of water vapor content from MIVIS TIR data

The main objective of land remotely sensed images is to derive biological, chemical and physical parameters by inverting sample sets of spectral data. For the above aim hyperspectral scanners on airborne platform are a powerful remote sensing instrument for both research and environmental applications because of their spectral resolution and the high operability of the platform. Fine spectral information by MIVIS (airborne hyperspectral scanner operating in 102 channels ranging from VIS to TIR) allows researchers to characterize atmospheric parameters and their effects on measured data which produce undesirable features on surface spectral signatures. These effects can be estimated (and remotely sensed radiances corrected) if atmospheric spectral transmittance is known at each image pixel. Usually ground-based punctual observations (atmospheric sounding balloons, sun photometers, etc.) are used to estimate the main physical parameters (like water vapor and temperature profiles) which permit us to estimate atmospheric spectral transmittance by using suitable radiative transfer model and a specific (often too strong) assumption which enable atmospheric properties measured only in very few points to be extended to the whole image. Several atmospheric gases produce observable absorption features, but only water vapor strongly varies in time and space. In this work the authors customize a self-sufficient «split-window technique» to derive (at each image pixel) atmospheric total columnar water vapor content (TWVC) using only MIVIS data collected by the fourth MIVIS spectrometer (Thermal Infrared band). MIVIS radiances have been simulated by means of MODTRAN4 radiative transfer code and the coefficients of linear regression to estimate TWVC from «split-windows» MIVIS radiances, based on 450 atmospheric water vapor profiles obtained by radiosonde data provided by NOAA\NESDIS. The method has been applied to produce maps describing the spatial variability of the water vapor columnar content along a trial scene. The procedure has been validated by means of the MIVIS data acquired over Venice and the contemporary radiosonde data. A discrepancy within 5% has been measured between the estimate of TWVC derived from the proposed self-sufficient split-window technique and the coincident radiosonde measurements. If confirmed by further analyses such a result will permit us to fully exploit MIVIS TIR capability to offer a more effective (at image pixel level) and self-sufficient (no ancillary observations required) way to obtain atmospherically corrected MIVIS radiances

Monitoring the Agung (Indonesia) ash plume of November 2017 by means of infrared Himawari 8 data

The Agung volcano (Bali; Indonesia) erupted in later November 2017 after several years of quiescence. Because of ash emissions, hundreds of flights were cancelled, causing an important air traffic disruption in Indonesia. We investigate those ash emissions from space by applying the RSTASH algorithm for the first time to Himawari-8 data and using an ad hoc implementation scheme to reduce the time of the elaboration processes. Himawari-8 is a new generation Japanese geostationary meteorological satellite, whose AHI (Advanced Himawari Imager) sensor offers improved features, in terms of spectral, spatial and temporal resolution, in comparison with the previous imagers of the MTSAT (Multi-Functional Transport Satellite) series. Those features should guarantee further improvements in monitoring rapidly evolving weather/environmental phenomena. Results of this work show that RSTASH was capable of successfully detecting and tracking the Agung ash plume, despite some limitations (e.g., underestimation of ash coverage under certain conditions; generation of residual artefacts). Moreover, estimates of ash cloud-top height indicate that the monitored plume extended up to an altitude of about 9.3 km above sea level during the period 25 November at 21:10 UTC-26 November at 00:50 UTC. The study demonstrates that RSTASH may give a useful contribution for the operational monitoring of ash clouds over East Asia and the Western Pacific region, well exploiting the 10 min temporal resolution and the spectral features of the Himawari-8 data

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

Improving the RST-OIL algorithm for oil spill detection under severe sun glint conditions

In recent years, the risk related to oil spill accidents has significantly increased due to a global growth in offshore extraction and oil maritime transport. To ensure sea safety, the implementation of a monitoring system able to provide real-time coverage of large areas and a timely alarm in case of accidents is of major importance. Satellite remote sensing, thanks to its inherent peculiarities, has become an essential component in such a system. Recently, the general Robust Satellite Technique (RST) approach has been successfully applied to oil spill detection (RST-OIL) using optical band satellite data. In this paper, an advanced configuration of RST-OIL is presented, and we aim to extend its applicability to a larger set of observation conditions, referring, in particular, to those in the presence of severe sun glint effects that generate some detection limits to the RST-OIL standard algorithm. To test such a configuration, the DeepWater Horizon platform accident from April 2010 was selected as a test case. We analyzed a time series of Moderate Resolution Imaging Spectroradiometer (MODIS) images that are usually significantly affected by sun glint in the Gulf of Mexico area. The accuracy of the achieved results was evaluated for comparison with a well-established satellite methodology based on microwave data, which confirms the potential of the proposed approach in identifying the oil presence on the scene with good accuracy and reliability, even in these severe conditions

Advanced satellite technique for volcanic activity monitoring and early warning

Nowadays, satellite remote sensing is an important tool for volcanic activity monitoring, thanks to several operational satellite platforms providing data everywhere with high observational frequencies and generally at low cost. Among different techniques available, an advanced satellite method, named RST (Robust Satellite Technique), based on the multitemporal analysis of satellite data, has shown a high capability in volcanic activity monitoring. This approach has proved capable of identifying and tracking volcanic ash cloud and of correctly detecting and monitoring volcanic thermal anomalies. This paper analyzes some recent results, obtained applying this approach to the last eruptive events of Mt. Etna using both polar and geostationary satellites. In particular, for the first time, this approach is implemented on the present geostationary platform MSG-SEVIRI, with 15 min of temporal resolution. Preliminary results, together with a future potential of this implementation, are shown and discussed. Moreover, a differential RST index in time domain is also proposed for near real-time application, as a possible contribution to the development of an efficient early warning satellite system for volcanic hazard mitigation

Robust satellite techniques (RST) for the thermal monitoring of earthquake prone areas: the case of Umbria-Marche October, 1997 seismic events

Several authors claim a space-time correlation between increases in Earth’s emitted Thermal Infra-Red (TIR) radiation and earthquake occurrence. The main problems of such studies regard data analysis and interpretation, which are often done without a validation/confutation control. In this context, a robust data analysis technique (RST, i.e. Robust Satellite Techniques) is proposed which permits a statistically based definition of TIR «anomaly » and uses a validation/confutation approach. This technique was already applied to satellite TIR surveys in seismic regions for about twenty earthquakes that occurred in the world. In this work RST is applied for the first time to a time sequence of seismic events. Nine years of Meteosat TIR observations have been analyzed to characterize the unperturbed TIR signal behaviour at specific observation times and locations. The main seismic events of the October 1997 Umbria-Marche sequence have been considered for validation, and relatively unperturbed periods (no earthquakes with Mb ≥ 4) were taken for confutation purposes. Positive time-space persistent TIR anomalies were observed during seismic periods, generally overlapping the principal tectonic lineaments of the region and sometimes focusing on the vicinity of the epicentre. No similar (in terms of relative intensity and space-time persistence) TIR anomalies were detected during seismically unperturbed periods

Irpinia earthquake 23 November 1980 – Lesson from Nature reviled by joint data analysis

A devastating earthquake of magnitude 6.9 occurred in Southern Italy on 23rd November 1980 in Irpinia-Basilicata area. Variations of different geochemical, atmospheric and ionospheric parameters and electromagnetic emissions were registered around the time of the Irpinia earthquake. The substantial progress reached in understanding the physics of the electromagnetic and thermal anomalies associated with the earthquake preparation process permitted us to create the Lithosphere-Atmosphere-Ionosphere (LAI) coupling model published recently. It shows that the observed effects are not independent but present the cause-consequence chain of physical processes and plasma- chemical reactions. We try to analyze the seismic data, radon emanation, hydrological anomalies, ground based ionosondes network, NOAA/AVHRR Thermal Infrared Irradiance (TIR) anomaly, Intercosmos-19 satellite topside sounding and VLF emissions data using the concept of the developed model and existing laboratory and largescale active experiments on air ionization. If the observed radon activity is really connected with the earthquake preparation process, all other variations of the atmosphere and ionosphere parameters can be explained as a consequence of the main physical process – air ionization by radon

Seismically active area monitoring by robust TIR satellite techniques: a sensitivity analysis on low magnitude earthquakes in Greece and Turkey

International audienceSpace-time TIR anomalies, observed from months to weeks before earthquake occurrence, have been suggested by several authors as pre-seismic signals. Up to now, such a claimed connection of TIR emission with seismic activity has been considered with some caution by scientific community mainly for the insufficiency of the validation data-sets and the scarce importance attached by those authors to other causes (e.g. meteorological) that, rather than seismic activity, could be responsible for the observed TIR signal fluctuations. A robust satellite data analysis technique (RAT) has been recently proposed which, thanks to a well-founded definition of TIR anomaly, seems to be able to identify anomalous space-time TIR signal transients even in very variable observational (satellite view angle, land topography and coverage, etc.) and natural (e.g. meteorological) conditions. Its possible application to satellite TIR surveys in seismically active regions has been already tested in the case of several earthquakes (Irpinia: 23 November 1980, Athens: 7 September 1999, Izmit: 17 August 1999) of magnitude higher than 5.5 by using a validation/confutation approach, devoted to verify the presence/absence of anomalous space-time TIR transients in the presence/absence of seismic activity. In these cases, a magnitude threshold (generally M In this work, 9 medium-low magnitude (

Seismically active area monitoring by robust TIR satellite techniques: a sensitivity analysis on low magnitude earthquakes in Greece and Turkey

Space-time TIR anomalies, observed from months to weeks before earthquake occurrence, have been suggested by several authors as pre-seismic signals. Up to now, such a claimed connection of TIR emission with seismic activity has been considered with some caution by scientific community mainly for the insufficiency of the validation data-sets and the scarce importance attached by those authors to other causes (e.g. meteorological) that, rather than seismic activity, could be responsible for the observed TIR signal fluctuations. A robust satellite data analysis technique (RAT) has been recently proposed which, thanks to a well-founded definition of TIR anomaly, seems to be able to identify anomalous space-time TIR signal transients even in very variable observational (satellite view angle, land topography and coverage, etc.) and natural (e.g. meteorological) conditions. Its possible application to satellite TIR surveys in seismically active regions has been already tested in the case of several earthquakes (Irpinia: 23 November 1980, Athens: 7 September 1999, Izmit: 17 August 1999) of magnitude higher than 5.5 by using a validation/confutation approach, devoted to verify the presence/absence of anomalous space-time TIR transients in the presence/absence of seismic activity. In these cases, a magnitude threshold (generally M In this work, 9 medium-low magnitude (4b The analysis, which was performed using 8 years of Meteosat TIR observations, demonstrated that anomalous TIR transients can be observed even in the presence of medium-low magnitude earthquakes (4b<5.5). As far as the research (just started) of possible correlation among TIR anomalies and earthquake occurrence is concerned, such a result suggests that: a) in order to identify seismically unperturbed periods for confutation purposes, a magnitude threshold (at least) lower than 4 should be used; b) the proposed validation/confutation approach should be applied in low-seismicity areas in order to find suitably long seismically quiescent periods