Entity

Time filter

Source Type

Sesto Fiorentino, Italy

Disperati L.,University of Siena | Disperati L.,CNR Institute of Geosciences and Earth Resources | Gregori F.,University of Siena | Perna M.,CNR Institute for Biometeorology | And 3 more authors.
Rendiconti Online Societa Geologica Italiana | Year: 2016

This paper presents the results of implementation of bi-temporal change analysis methods to RapidEye satellite imagery to support the detection, at regional scale, of landslides caused by two intense rainfall events of 2009 and 2011, in Northern Tuscany. Image geometric and radiometric pre-processing were applied. Then, bitemporal image ratioing of Difference Vegetation Index (DVI) and bitemporal spectral transformations (Principal Component Analysis - PCA; Independent Component Analysis - ICA) were implemented. Finally, unsupervised and supervised classification allowed us to obtain thematic representation of areas of changes which supported the identification of almost hundred landslides in the study area. © Società Geologica Italiana, Roma 2016.


Oberto E.,ARPA Piemonte | Milelli M.,ARPA Piemonte | Pasi F.,Consorzio LAMMA | Gozzini B.,CNR Institute for Biometeorology
Natural Hazards and Earth System Sciences | Year: 2012

The demand for verification of numerical models is still very high, especially for what concerns the operational Quantitative Precipitation Forecast (QPF) used, among others, for evaluating the issuing of warnings to the population. In this study, a comparative verification of the QPF, predicted by two operational Limited Area Models (LAMs) for the Italian territory is presented: COSMO-I7 (developed in the framework of the COSMO Consortium) and WRF-NMM (developed at NOAA-NCEP). The observational dataset is the precipitation recorded by the high-resolution non-GTS rain gauges network of the National Civil Protection Department (NCPD) over two years (2007-2008). Observed and forecasted precipitation have been treated as areal quantity (areal average of the values accumulated in 6 and 24 h periods) over the 102 "warning areas", defined by the NCPD both for administrative and hydrological purposes. Statistics are presented through a series of conventional indices (BIAS, POD and POFD) and, in addition, the Extreme Dependency Score (EDS) and the Base Rate (BS or 1-BS) have been used for keeping into account the vanishing of the indices as the events become rare. Results for long-period verification (the whole 2 yr) with increasing thresholds, seasonal trend (3 months period), diurnal error cycle and error maps, are presented. Results indicate that WRF has a general tendency of QPF overestimation for low thresholds and underestimation for higher ones, while COSMO-I7 tends to overestimate for all thresholds. Both models show a seasonal trend, with a bigger overestimation during summer and spring, while during autumn and winter the models tend to be more accurate. © 2012 Author(s).


Massi L.,University of Florence | Santini C.,CNR Institute for Biometeorology | Pieri M.,Consorzio LAMMA | Nuccio C.,University of Florence | Maselli F.,University of Florence
Italian Journal of Remote Sensing / Rivista Italiana di Telerilevamento | Year: 2011

MODIS data have been widely used for the study of marine waters and particularly for the estimation of chlorophyll concentration [CHL]. The [CHL] retrieval algorithms which are applied to MODIS imagery show various degrees of accuracy depending on the presence of Case 1 and Case 2 waters (C1W and C2W). The current paper presents the adaptation of a recently proposed algorithm based on Spectral Angle Mapping (SAM) to characterize water types using MODIS data. The algorithm is applied to 26 MODIS images taken over the Western Mediterranean basin from 2003 to 2009. The value of a SAM indicator of proximity to Case 1 waters is first assessed towards in situ measurements collected during the same period. The results confirm that the fuzzy categorization into C1-C2W can be used to guide the application of different algorithms. In this way, the accuracy of [CHL] estimation is decidedly enhanced both in oceanic and coastal areas.


Melani S.,CNR Institute for Biometeorology | Pasqui M.,CNR Institute for Biometeorology | Guarnieri F.,CNR Institute for Biometeorology | Antonini A.,Consorzio LAMMA | And 2 more authors.
Atmospheric Research | Year: 2010

Instantaneous rainfall intensities retrieved by a multi-sensor precipitation estimation algorithm based on the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard Meteosat and on the Special Sensor Microwave Imager (SSM/I) data are used to investigate the dynamics and phenomenology associated with the African monsoon regime. A 5-year (2004-2008) climatology during the warm season (June-August) of coherent precipitation patterns is presented with emphasis on the intraseasonal and interannual variability of the tropical northern African Monsoon for the investigation of the longitudinal distribution of rainfall and the zonal component of motion. The coherence and phase speed of rain streaks are also quantified by means of a two-dimensional autocorrelation analysis to derive the zonal-span and the duration properties of the identified rain systems. The periodicity of the precipitating episodes is finally investigated through harmonic analysis performed in different longitudinal bands of the studied domain.Rainfall episodes tend to initiate in the lee of steep topography (maxima in correspondence of the Ethiopian highlands), consistently with the thermal heating forcing from elevated terrain. Such an organized convection consists of coherent sequences of precipitation episodes, which span an average distance of about 460. km and last about 10. h. The diurnal cycle of summer precipitation is characterised by afternoon and early evening maxima located mainly downwind of the major mountain chains, as also the spectral analysis has clearly highlighted. © 2010 Elsevier B.V.


Lazzara L.,University of Florence | Marchese C.,University of Florence | Massi L.,University of Florence | Nuccio C.,University of Florence | And 4 more authors.
Italian Journal of Remote Sensing / Rivista Italiana di Telerilevamento | Year: 2010

The annual cycle of pelagic primary production (PP) from ocean colour is analysed in a transition area between Ligurian and Tyrrhenian waters, where a general oligo-mesotrophic status is seasonally modified by anthropic impact near the Tuscany coast. Based on the common ecological features six different zones were delimited. Remote sensing data from different satellites (Meteosat, Aqua) were used as input in a primary production model. The daily production of the entire area was computed on pixel by pixel basis (4×4 km) using a modified GIS software. Overwhelming importance of oceanic bloom and high spatial variance of PP (90 ±54 gC m -2 y r -1) show that remote sensed data can allow a better estimation of carbon budget even in optically complex waters.

Discover hidden collaborations