Mariapia Faruolo

Coupling MODIS and Radar Altimetry Data for Discharge Estimation in Poorly Gauged River Basins

The capability of coupling measurements of river velocity derived from Moderate Resolution Imaging Spectroradiometer (MODIS) and water levels derived from ENVISAT Advanced Radar Altimeter (RA-2) for river discharge estimation is thoroughly investigated. The method is applied even considering the possible unavailability of the river cross-section survey by using the entropy theory for reconstructing the bathymetry. The discharge estimation accuracy is validated using in situ measurements along the Po River (Northern Italy) where daily observations are available for the period 2005-2010. The agreement with the observed discharge is fairly satisfactory with coefficient of correlation of 0.91 and relative root-mean-square error (RMSE) of 37 on average. Therefore, the coupling of the two sensors provides, with a good level of accuracy, the hydraulic quantities to use for discharge estimation. These results are particularly significant for the forthcoming European Space Agency Sentinel-3 mission, in which a visible-near infrared multispectral sensor and an altimeter will be onboard the same satellite platform providing significant improvements in terms of vertical accuracy and spatial-temporal resolution.

Real time monitoring of flooded areas by a multi-temporal analysis of optical satellite data

Optical sensors aboard meteorological satellites are an excellent tool to monitor floods and support the flood risk management cycle, mainly thanks to their high temporal resolution, which allow us to obtain real time and frequently updated information on environmental changes. The RST (Robust Satellite Techniques) approach, an automatic change detection scheme, has been already applied using AVHRR (Advanced very High Resolution Radiometer) and MODIS (Moderate Resolution Imaging Spectroradiometer) data to detect and monitor flooded areas. Results achieved have shown its capability in automatically identify flooded areas with a low rate of false alarms, also discriminating permanent water from actual inundated areas. In this paper, in order to further assess the reliability and the sensitivity of the proposed approach in different conditions of observation, the RST methodology has been used to analyze the July 2007 and October 2008 floods occurred in the South Africa and Algeria regions.

Thermal Monitoring of Eyjafjöll Volcano Eruptions by Means of Infrared MODIS Data

In the evening of 20 March 2010, after about two centuries of quiescence, an effusive eruption took place at Eyjafjöll (Iceland) volcano, from a small vent localized on the northeast flank (Fimmvörduháls Pass) of the volcano edifice. On 31 March, a new eruptive fissure opened on the same region emitting lava. About 2 weeks later, on 14 April, a strong explosive eruption took place under the Eyjafjallajökull glacier, injecting copious amounts of ash in the atmosphere and causing an unprecedented air traffic disruption in Northern and Central Europe. In this paper, the changes in thermal signals occurring at Eyjafjöll volcano during 1 March-20 April 2010 are investigated, testing the RSTVOLC algorithm for the first time in a subpolar environment. Outcomes of this retrospective study, performed by means of infrared Moderate Resolution Imaging Spectroradiometer (MODIS) data, show that both effusive and explosive eruptions of the Eyjafjöll volcano could be identified in a timely manner and well monitored from space. Moreover, in spite of a lack of pre-eruptive hot spots detection, this paper reveals a general increasing trend of the middle infrared signal at crater area, beginning 2 weeks before the explosion, stimulating and suggesting further investigations devoted to better characterize the thermal behavior of the monitored volcano.

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.

A Multitemporal Investigation of AMSR-E C-Band Radio-Frequency Interference

Radio-frequency interference (RFI) is increasingly a severe problem for present and future microwave satellite missions. RFI at C- and X-bands can contaminate remotely sensed measurements, as experienced with the Advanced Microwave Scanning Radiometer (AMSR-E) and the WindSat sensor. In this work, the multitemporal Robust Satellite Techniques approach has been implemented on C-band AMSR-E data in order to identify areas systematically affected by different levels of RFI, trying to discriminate them from natural geophysical variability zones. To the scope, nine years of AMSR-E data have been investigated, allowing us also to better infer RFI impact on data acquired during ascending or descending passes, as well as in horizontal or vertical polarization. In detail, two analyses were carried out: one considering only measurements at C-band and another one taking into account a combination between C- and X-band measurements. The results of this study will be shown and discussed in this paper.

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.

River discharge estimation through MODIS data

River discharge is an important quantity of the hydrologic cycle because it is essential for both scientific and operational applications related to water resources management and flood risk prevention. Streamflow measurements are sparse and for few sites along natural channels and, hence, they are not able to detect adequately the complexity of variation in surface water systems. Therefore, in recent years, the possibility to obtain river discharge estimates through remote sensing monitoring has received a great interest. In this context, the capability of the MODerate resolution Imaging Spectroradiometer (MODIS) for river discharge estimation is investigated here. Thanks to a very short revisiting time interval and a moderate spatial resolution (up to 250 m), MODIS has a significant potential for mapping flooded area extent and flow dynamics. Specifically, for the estimation of river discharge, the ratio of the MODIS channel 2 reflectance values between two pixels located within and outside the river is used. Time series of daily discharge between 2006 and 2010 measured at two gauging stations located along the Upper Tiber River basin (central Italy) are employed to test the procedure. The agreement between MODIS-derived and in situ discharge time series is found to be fairly good with correlation coefficient values close to 0.8.

A multi-sensor (SMOS, AMSR-E and ASCAT) satellite-based soil moisture products inter-comparison

Soil Moisture (SM), being one of the main variables within the system that controls the hydrological interactions among soil, vegetation and atmosphere, plays a key role in the water cycle. Satellite systems, both active and passive, have already demonstrated their capability to provide reliable SM measurements. The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) mission, launched in November 2009, was the first specific SM satellite mission. In this work we assessed the capability of SMOS data to accurately capture SM dynamics over a long time period by comparing them with in situ observations. To better assess the performance of such results, they were also compared with those obtained with alternative satellite-based SM products, considering in particular those generated by Advanced Microwave Sounding Radiometer (AMSR-E) and Advanced SCATterometer (ASCAT) data.

PRE-EARTHQUAKES, an FP7 project for integrating observations and knowledges on earthquake precursors: Preliminary results and strategy

PRE-EARTHQUAKES (Processing Russian and European EARTH observations for earthQUAKE precursors Studies) EU-FP7 project is devoted to demonstrate - integrating different observational data, comparing and improving different data analysis methods - how it is possible to progressively increase reliability of short term seismic risk assessment. Three main testing area were selected (Italy, Turkey and Sakhalin) in order to concentrate observations and integration efforts starting with a learning phase on selected events in the past devoted to identify the most suitable parameters, observations technologies, data analysis algorithms. For these areas, different ground (80 radon and 29 spring water stations in Turkey region, 2 magneto-telluric in Italy) and satellite (18 different systems) based observations, 11 data analysis methods, for 7 measured parameters, have been compared and integrated. A specific integration platform (PEG, Pre-Earthquakes Geoportal) based on OGC (Open Geospatial Consortium) standards, was developed to operate a products integration, cross-validation and scientific interpretation.

On the use of temporal vegetation indices in support of eligibility controls for EU aids in agriculture

ABSTRACT The use of remote sensing in the context of the Common Agricultural Policy (CAP) has progressively become an official method to support European (EU) Member States in carrying out controls about declarations of farmers requiring EU subsidies in agriculture. Reliable automatic or semi-automatic methodologies aiming at crop identification are still being developed and the only technique, which is officially accepted in the CAP context, remains photo interpretation of high/very high (satellite or aerial) orthoimages. To verify past situations, only orthophotos can be used but, unfortunately, they are not always available. In these cases, the use of satellite sensors with adequate spatial, spectral, and temporal resolutions, together with a reliable data analysis technique, could support or even substitute orthophoto interpretation. In this study, we propose a multi-temporal, multispectral algorithm exploiting the Thematic Mapper/Enhanced Thematic Mapper Plus data on Landsat platforms to identify different land covers in the context of CAP. Here it is presented to discriminate arable from non-arable lands. Assessment of the methodology was carried out using Corine 2012 and more than 1500 validation points over Basilicata region (Southern Italy). A general good agreement was found (74%), which increases to 82% in the specific case of arable land identification.