Witt A., Malamud B.D., Rossi M., Guzzetti F., Peruccacci S., 2010, Temporal correlation and clustering of landslides.,
Earth surface processes and landforms (Print) 35 (2010): 1138–1156.,
Notarnicola - Mondini, 2010, Use of historical orthophotos and digital elevation model to link watershed land use changes and storm flow response in a Karst environment,
Journal of applied remote sensing (2010). doi_10.1117/1.3284717,
DOI: 10.1117%2F1.3284717
Cardinali M., Santangelo M., Ardizzone F., 2010, Criteri di preparazione delle carte inventario delle frane. Rapporto 1,
2010,
C. Henriques (1) , M. Cardinali (2), P. Reichenbach (2), M. Santangelo (2), F. Guzzetti (2), J. L. Zêzere (1) , 2010, Relação entre movimentos de vertente e a morfo-estrutura na bacia hidrográfica da Tornada (sector Centro-Oeste de Portugal) ,
V Congresso Nacional de Geomorfologia, Porto, 8-11 Dicembre 2010,
Abstract
This paper presents the relationships between the geological and structural settings and the distribution of slope
movements in the Tornada river basin (107 km2
), in Central western Portugal. This basin was chosen for its geological
and tectonic features and for the abundance of slope movements. The study area is situated in a dissected old
quaternary coastal plateau with an evident syncline structure, where crop out mainly upper Jurassic sandstones and
claystones. A detailed structural-geological map at 1_10 000 scale and a ...
This paper presents the relationships between the geological and structural settings and the distribution of slope
movements in the Tornada river basin (107 km2
), in Central western Portugal. This basin was chosen for its geological
and tectonic features and for the abundance of slope movements. The study area is situated in a dissected old
quaternary coastal plateau with an evident syncline structure, where crop out mainly upper Jurassic sandstones and
claystones. A detailed structural-geological map at 1_10 000 scale and a detailed landslide inventory map were
prepared through the interpretation of stereoscopic aerial photographs and extensive field surveys. The landslides
were classified according to the type of movement into shallow and deep-seated failures (mainly translational), and
the relative age into recent and old. The distribution of the landslides and their relationship with lithology and bedding
attitude were studied considering in particular: i) the presence of weak lithological layers; ii) the attitude of planar and
continuous bedding planes dipping towards the free-face of slope; iii) the presence of hydrogeological conditions
favorable to slope instability; and iv) the occurrence of normal faults. The relationship between structural settings,
geological information and landslides was studied in order to understand the factors that mainly explain the instability
conditions of the area.
Palma Blonda, Panyotis Dimopoulos, MAria Petrou, Rob Jongman, Harini Nagendra, Daniela Iasillo, Alain Arnaud, Paola Mairota, Joao Honrado, Emilio Padoa Schioppa, Richard Lucas, Laurent Durieux, Bollanos, LAura Candela, Andrea Baraldi, Jordi Inglada, 2010, FP7-SPA.2010.1.1-04. BIO_SOS_ Biodiversity Multi-source Monitoring System_ from Space to Species GA. 263435,
2010,
Abstract
BIO_SOS (BIOdiversity multi-SOurce monitoring System_ from Space TO Species is a response to the Call ...
BIO_SOS (BIOdiversity multi-SOurce monitoring System_ from Space TO Species is a response to the Call for
proposals FP7- SPACE-2010-1, addressing topic SPACE.2010.1.1-04 "Stimulating the development of GMES
services in specific areas" with application to (B) BIODIVERSITY.
BIO_SOS is a pilot project for effective and timely multi-annual monitoring of NATURA 2000 sites and their
surrounding in support to management decisions in sample areas, mainly in Mediterranean regions and
for the reporting on status and trends according to National and EU obligations. The aim of BIO_SOS is
two-fold: 1) the development and validation of a prototype multi-modular system to provide a reliable long
term biodiversity monitoring service at high to very high-spatial resolution; 2) to embed monitoring information
(changes) in innovative ecological (environmental) modelling for Natura 2000 site management. The system
will be developed and validated within ecologically sensitive 'sampling' sites and their borders exposed to
combined human-induced pressures. Different environmental characteristics of the selected sites have been
considered in order to ensure system robustness. Sites characteristics ranges from mountain rough to flat
coastal morphologies, from rangeland to human dominated landscapes and land uses. BIO_SOS intends to
deeply investigate issues related to very high spatial (VHR) (and spectral) resolution Earth Observation data
(EO) image processing for automatic land cover maps updating and change detection. Such maps are at
the base of biodiversity indicators provision. On the other hand, it intends to develop a modelling framework
to combine multi-scale (high to very high resolution) EO data and in-situ/ancillary data to provide indicators
and their trends. This means the development of more appropriate and accurate models in support to a
deeper understanding, assessment and prediction of the impacts that human induced pressures may have on
biodiversity loss.
Guzzetti F., Fiorucci F., Ardizzone F., Cardinali M., Rossi M., Mondini A.C., Reichenbach P., Santangelo M., Valigi. D., 2010, Landslide volumes and evaluation of landslide mobilization rates in an area in Umbria, central Apennines,
85° Congresso Nazionale della Società Geologica Italiana, pp. 668–669, Pisa, 6-8/09/2010,
Mugnai, A., F. Guzzetti, G. Roth, 2010, Outcomes of the 9th EGU Plinius Conference on Mediterranean Storms (2007),
Natural hazards and earth system sciences (Print) 10 (2010): 875–879.,
Maccioni P., Barbetta S., Tarpanelli A., Melone F., Moramarco T., 2010, Redazione di mappe delle aree allagabili in tratti fluviali reticolo secondario Fiume Tevere – Analisi Idrologica (2° Parte),
2010,
Brocca L., Faruolo M., Coviello I., Lacava T., Melone F., Moramarco T., Pergola N., Tramutoli V., 2010, Soil moisture variations estimation through Robust Satellite Technique on different satellite sensors_ an intecomparison and validation study across Europe,
EGU Leonardo, Luxembourg,Luxembourg., 2010,
Bovenga F., Candela L., Casu F., Fornaro G., Guzzetti F., Lanari R., Nitti D.O., Nutricato R., Reale R., 2010, The COSMO,
2010 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010, Honolulu, Hawaii (USA), 2010,
Mondini A., Morfeo Team, 2010, Piano di procurement (versione 2),
2010,
Torri D., Blonda P., 2010, Cnr activities, results and progress.,
2nd Firesense plenary meeting, Istanbul, 2010,
Mondini A., Morfeo Team, 2010, MANUALE UTENTE E PROCEDURE OPERATIVE (VERSIONE 4),
2010,
Fiorucci F., Cardinali M., Carlà R., Mondini A., Santurri L., Guzzetti F., 2010, Comparison of event-based landslide inventory maps obtained interpreting satellite images and aerial photographs,
EGU General Assembly 2010, Vienna, 2010,
Casagli N., Foti E., Maugeri M., Navarra M., Guzzetti F., 2010, Relazione sulle osservazioni e sui quesiti posti da comitati civici e singoli cittadini sulla perimetrazione del rischio residuo dei centri abitati di cui allOPCM. 3815,
2010,
Mondini A., Morfeo Team, 2010, Report attività dimostrative (Versione 2),
2010,
Mondini A., Morfeo Team, 2010, Report di validazione dei Prodotti EO VHR per il riconoscimento e mappatura delle frane,
2010,
Brocca, L., Melone, F., Moramarco, T., Todini, E., Mazzetti, C., Wagner, W., 2010, Comparing satellite and in-situ soil moisture observations with modeled data in the Tiber basin.,
Int. Conf. EGU Leonardo Topical Conference Series on the hydrological cycle 2010, Luxembourg, 2010,
Barbetta S., Brocca L., Camici S., Corato G., Melone F., Moramarco T., Tarpanelli A., 2010, Analysis of climate changing effects on floods frequency through a continuous hydrological modelling,
Indo-Italian Workshop on Climate change and anthropogenic activities on soil and water resources, Roorkee, India, 2010,
Brocca L., Camici S., Tarpanelli A., Melone F., Moramarco T., 2010, Serie sintetiche di portata per i bacini del Fosso Sciola e dei Torrenti Feo e Rasina ed analisi statistica delle portate al colmo,
2010,
Mondini A., Morfeo Team, 2010, SPECIFICHE ALGORITMICHE (VERSIONE 3),
2010,
Mondini A., Morfeo Team, 2010, Specifiche dei prodotti utente (requisiti e specifiche algoritmiche),
2010,
Mondini A., Morfeo Team, 2010, LOG-BOOK (VERSIONE 2),
2010,
Lacava T; Brocca L; Calice G; Melone F; Moramarco T; Pergola N; Tramutoli V, 2010, Soil moisture variations monitoring by AMSU-based soil wetness indices_ A long-term inter-comparison with ground measurements,
Remote sensing of environment 114 (2010): 2317–2325. doi_10.1016/j.rse.2010.05.008,
DOI: 10.1016%2Fj.rse.2010.05.008
Abstract
Soil moisture controls the partitioning of rainfall into runoff and infiltration and, consequently, the runoff ...
Soil moisture controls the partitioning of rainfall into runoff and infiltration and, consequently, the runoff generation. On the catchment scale its routine monitoring can be performed through remote sensing technologies. Within this framework, the purpose of this study is to investigate the potential of the Advanced Microwave Sounding Unit (AMSU), radiometer on board the NOAA (National Oceanic and Atmospheric Administration) satellites and operating since 1998, for the assessment of soil wetness conditions by comparing soil moisture data with both those measured in situ and provided by a continuous rainfall-runoff model applied to four catchments located in the Upper Tiber River (Central Italy). In particular, in order to perform a robust analysis an extensive and long-term period (nine years) of data was investigated. In detail, the Soil Wetness Variation Index, derived from the AMSU data modified in order to take account of the difference between the soil layer investigated by the satellite sensor and that used as a benchmark, was found to be correlated both with the in-situ and modeled soil moisture variations showing correlation coefficients in the range of 0.42-0.49 and 0.33-0.48, respectively. As far as the soil moisture temporal pattern is concerned, higher correlations were obtained (0.59-0.84 for the in-situ data and 0.82-0.87 for the modeled data set) partly due to the soil moisture seasonal pattem that enhances the correlation. Overall, the root mean square error was found to be less than 0.05 m(3)/m(3) for both the comparisons, thus assessing the potential of the AMSU sensor to quantitatively retrieve soil moisture temporal patterns. Moreover. the AMSU sensor can be considered as a useful tool to provide a reliable and frequently updated global soil moisture data set, considering its higher temporal resolution now available (about 4 passes per day) thanks to the presence of the sensor aboard different satellites.
Mondini A., Morfeo Team, 2010, Disegno di dettaglio del sistema,
2010,
Camici S., Moramarco T., Brocca L., Melone F., Lapenna V., Perrone A., Loperte A., 2010, On mechanisms triggering the levees failure along the Foenna stream on 1st January 2006 and which caused the flooding in the urban area of Sinalunga, Tuscany Region (Italy). A case study.,
EGU 2010, Wien, Austria, 2010,
Brocca L.1; Melone F.1; Moramarco T.1; Wagner W.2; Naeimi V.2,4; Bartalis Z.3; Hasenauer S.2, 2010, Improving runoff prediction through the assimilation of the ASCAT soil moisture product.,
Hydrology and earth system sciences 14 (2010): 1881–1893. doi_10.5194/hess-14-1881-2010,
DOI: 10.5194%2Fhess-14-1881-2010
Abstract
The role and the importance of soil moisture for
meteorological, agricultural and hydrological applications is
widely known. ...
The role and the importance of soil moisture for
meteorological, agricultural and hydrological applications is
widely known. Remote sensing offers the unique capability
to monitor soil moisture over large areas (catchment scale)
with, nowadays, a temporal resolution suitable for hydrological
purposes. However, the accuracy of the remotely sensed
soil moisture estimates has to be carefully checked. The validation
of these estimates with in-situ measurements is not
straightforward due the well-known problems related to the
spatial mismatch and the measurement accuracy. The analysis
of the effects deriving from assimilating remotely sensed
soil moisture data into hydrological or meteorological models
could represent a more valuable method to test their reliability.
In particular, the assimilation of satellite-derived
soil moisture estimates into rainfall-runoff models at different
scales and over different regions represents an important
scientific and operational issue.
In this study, the soil wetness index (SWI) product derived
from the Advanced SCATterometer (ASCAT) sensor
onboard of the Metop satellite was tested. The SWI was
firstly compared with the soil moisture temporal pattern derived
from a continuous rainfall-runoff model (MISDc) to
assess its relationship with modeled data. Then, by using a
simple data assimilation technique, the linearly rescaled SWI
that matches the range of variability of modelled data (denoted
as SWI) was assimilated into MISDc and the model
performance on flood estimation was analyzed. Moreover,
three synthetic experiments considering errors on rainfall,
model parameters and initial soil wetness conditions were
carried out. These experiments allowed to further investigate
the SWI potential when uncertain conditions take place.
The most significant flood events, which occurred in the period
2000-2009 on five subcatchments of the Upper Tiber
River in central Italy, ranging in extension between 100 and
650 km2, were used as case studies. Results reveal that
the SWI derived from the ASCAT sensor can be conveniently
adopted to improve runoff prediction in the study
area, mainly if the initial soil wetness conditions are unknown.
Tullo T., Maccioni P., Tarpanelli A., Barbetta S., Melone F., Moramarco T., 2010, Rio del Bagno_ Aree Allagabili Tempo di Ritorno 500 anni,
2010,
Tullo T., Maccioni P., Tarpanelli A., Barbetta S., Melone F., Moramarco T., 2010, Rio del Bagno_ Aree Allagabili Tempo di Ritorno 200 anni,
2010,
Tullo T., Maccioni P., Tarpanelli A., Barbetta S., Melone F., Moramarco T., 2010, Rio del Bagno_ Fasce Fluviali,
2010,
Tullo T., Maccioni P., Tarpanelli A., Barbetta S., Melone F., Moramarco T., 2010, Torrenti Feo-Rasina: Aree Allagabili Tempo di Ritorno 50 anni,
2010,
Tullo T., Maccioni P., Tarpanelli A., Barbetta S., Melone F., Moramarco T., 2010, Torrenti Feo-Rasina: Aree Allagabili Tempo di Ritorno 100 anni,
2010,
Tullo T., Maccioni P., Tarpanelli A., Barbetta S., Melone F., Moramarco T., 2010, Torrenti Feo-Rasina: Aree Allagabili Tempo di Ritorno 200 anni,
2010,
Tullo T., Maccioni P., Tarpanelli A., Barbetta S., Melone F., Moramarco T., 2010, Torrenti Feo-Rasina: Aree Allagabili Tempo di Ritorno 500 anni,
2010,
Tullo T., Maccioni P., Tarpanelli A., Barbetta S., Melone F., Moramarco T., 2010, Torrenti Feo-Rasina: Fasce Fluviali,
2010,
Tullo T., Maccioni P., Tarpanelli A., Barbetta S., Melone F., Moramarco T., 2010, Torrente Vertola_ Aree Allagabili Tempo di Ritorno 50 anni,
2010,
Tullo T., Maccioni P., Tarpanelli A., Barbetta S., Melone F., Moramarco T., 2010, Torrente Vertola_ Aree Allagabili Tempo di Ritorno 100 anni,
2010,
Tullo T., Maccioni P., Tarpanelli A., Barbetta S., Melone F., Moramarco T., 2010, Torrente Vertola_ Aree Allagabili Tempo di Ritorno 200 anni,
2010,
Tullo T., Maccioni P., Tarpanelli A., Barbetta S., Melone F., Moramarco T., 2010, Torrente Vertola_ Aree Allagabili Tempo di Ritorno 500 anni,
2010,
Tullo T., Maccioni P., Tarpanelli A., Barbetta S., Melone F., Moramarco T., 2010, Torrente Vertola_ Fasce Fluviali,
2010,
Tullo T., Maccioni P., Tarpanelli A., Barbetta S., Melone F., Moramarco T., 2010, Rio del Bagno_ Aree Allagabili Tempo di Ritorno 100 anni,
2010,
Tullo T., Maccioni P., Tarpanelli A., Barbetta S., Melone F., Moramarco T., 2010, Rio del Bagno_ Aree Allagabili Tempo di Ritorno 50 anni,
2010,
Maccioni P., Tarpanelli A., Tullo T., Barbetta S., Melone F., Moramarco T., 2010, Rio Grande (Valfabbrica): Fasce Fluviali,
2010,
Maccioni P., Tarpanelli A., Tullo T., Barbetta S., Melone F., Moramarco T., 2010, Rio Grande (Valfabbrica): Aree Allagabili Tempo di Ritorno 500 anni,
2010,
Maccioni P., Tarpanelli A., Tullo T., Barbetta S., Melone F., Moramarco T., 2010, Rio Grande (Valfabbrica): Aree Allagabili Tempo di Ritorno 500 anni,
2010,
Maccioni P., Tarpanelli A., Tullo T., Barbetta S., Melone F., Moramarco T., 2010, Rio Grande (Valfabbrica): Aree Allagabili Tempo di Ritorno 200 anni,
2010,
Maccioni P., Tarpanelli A., Tullo T., Barbetta S., Melone F., Moramarco T., 2010, Rio Grande (Valfabbrica): Aree Allagabili Tempo di Ritorno 100 anni,
2010,
Maccioni P., Tarpanelli A., Tullo T., Barbetta S., Melone F., Moramarco T., 2010, Rio Grande (Valfabbrica): Aree Allagabili Tempo di Ritorno 50 anni,
2010,
Maccioni P., Tarpanelli A., Tullo T., Barbetta S., Melone F., Moramarco T., 2010, Torrente Maccara_ Fasce Fluviali,
2010,
Maccioni P., Tarpanelli A., Tullo T., Barbetta S., Melone F., Moramarco T., 2010, Torrente Maccara_ Aree Allagabili Tempo di Ritorno 500 anni,
2010,
