151 research outputs found
On the use of satellite Sentinel 2 data for automatic mapping of burnt areas and burn severity
In this paper, we present and discuss the preliminary tools we devised for the automatic recognition of burnt areas and burn severity developed in the framework of the EU-funded SERV_FORFIRE project. The project is focused on the set up of operational services for fire monitoring and mitigation specifically devised for decision-makers and planning authorities. The main objectives of SERV_FORFIRE are: (i) to create a bridge between observations, model development, operational products, information translation and user uptake; and (ii) to contribute to creating an international collaborative community made up of researchers and decision-makers and planning authorities. For the purpose of this study, investigations into a fire burnt area were conducted in the south of Italy from a fire that occurred on 10 August 2017, affecting both the protected natural site of Pignola (Potenza, South of Italy) and agricultural lands. Sentinel 2 data were processed to identify and map different burnt areas and burn severity levels. Local Index for Statistical Analyses LISA were used to overcome the limits of fixed threshold values and to devise an automatic approach that is easier to re-apply to diverse ecosystems and geographic regions. The validation was assessed using 15 random plots selected from in situ analyses performed extensively in the investigated burnt area. The field survey showed a success rate of around 95%, whereas the commission and omission errors were around 3% of and 2%, respectively. Overall, our findings indicate that the use of Sentinel 2 data allows the development of standardized burn severity maps to evaluate fire effects and address post-fire management activities that support planning, decision-making, and mitigation strategies.Fil: Lasaponara, Rosa. Consiglio Nazionale delle Ricerche; ItaliaFil: Tucci, Biagio. Consiglio Nazionale delle Ricerche; ItaliaFil: Ghermandi, Luciana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina. Universidad Nacional del Comahue. Centro Regional Universitario Bariloche. Laboratorio de Ecotono; Argentin
Immagini satellitari ad alta risoluzione e ricerca archeologica: applicazioni e casi di studio con riprese pancromatiche e multispettrali di QuickBird
The paper concerns the research activities of the IBAM-CNR and the IMAA-CNR in the field of archaeological remote sensing with the use of very high resolution images of QuickBird, the satellite with the greatest geometrical resolution available for civil use. These images have an enormous potential in the study of ancient urban and territorial contexts and for the identification and spatial characterization of archaeological sites, particularly when aerial photos and recent detailed maps are not available. During the archaeological research in Hierapolis of Phrygia (Turkey) and in southern Italy (Monte Irsi, Monte Serico, Jure Vetere and Metaponto), the examination and the study of panchromatic and multispectral images of QuickBird made it possible to detect surface anomalies and traces linked to ancient buried structures or to paleo-environmental elements; moreover, panchromatic images were georeferenced and used as the base field maps for the survey in Hierapolis, together with GPS systems. The satellite images were analysed both for the identification of archaeological features and for the characterisation of the contexts in which these elements were found. During field work, the traces and the anomalies identified in the images were constantly verified, so as to determine their actual relevance to archaeological elements, to interpret them and, where possible, to specify their chronology, thus avoiding misunderstandings and errors. The images were used in all phases of the research (field work, documentation, data processing and management in GIS environment), in combination with the aerial photographs and the available maps; they were also used for presentation of the results and were draped on DEM for the 3D visualization of the territories and of the archaeological features. In order to highlight particular archaeological traces and anomalies some image processing methodologies were adopted: multispectral processing and algorithms of data fusion (with the integration of the high spatial resolution of panchromatic images with the spectral capability of multispectral images), of enhancement (such as PCA, NDVI and TCT) and edge detection
Characterization and Mapping of Fuel Types for the Mediterranean Ecosystems of Pollino National Park in Southern Italy by Using Hyperspectral MIVIS Data
Abstract
The characterization and mapping of fuel types is one of the most important factors that should be taken into consideration for wildland fire prevention and prefire planning. This research aims to investigate the usefulness of hyperspectral data to recognize and map fuel types in order to ascertain how well remote sensing data can provide an exhaustive classification of fuel properties. For this purpose airborne hyperspectral Multispectral Infrared and Visible Imaging Spectrometer (MIVIS) data acquired in November 1998 have been analyzed for a test area of 60 km2 selected inside Pollino National Park in the south of Italy. Fieldwork fuel-type recognitions, performed at the same time as remote sensing data acquisition, were used as a ground-truth dataset to assess the results obtained for the considered test area. The method comprised the following three steps: 1) adaptation of Prometheus fuel types for obtaining a standardization system useful for remotely sensed classification of fuel types and properties in the considered Mediterranean ecosystems; 2) model construction for the spectral characterization and mapping of fuel types based on a maximum likelihood (ML) classification algorithm; and 3) accuracy assessment for the performance evaluation based on the comparison of MIVIS-based results with ground truth. Results from our analysis showed that the use of remotely sensed data at high spatial and spectral resolution provided a valuable characterization and mapping of fuel types being that the achieved classification accuracy was higher than 90%
On the Use of Google Earth Engine and Sentinel Data to Detect “Lost” Sections of Ancient Roads. The Case of Via Appia
The currently available tools and services as open
and free cloud resources to process big satellite data opened
up a new frontier of possibilities and applications including
archeological research. These new research opportunities also
pose several challenges to be faced, as, for example, the data
processing and interpretation. This letter is about the assessment
of different methods and data sources to support a visual
interpretation of EO imagery. Multitemporal Sentinel 1 and
Sentinel 2 data sets have been processed to assess their capability
in the detection of buried archeological remains related to some
lost sections of the ancient Via Appia road (herein selected
as case study). The very subtle and nonpermanent features
linked to buried archeological remains can be captured using
multitemporal (intra- and inter-year) satellite acquisitions, but
this requires strong hardware infrastructures or cloud facilities,
today also available as open and free tools as Google Earth Engine
(GEE). In this study, a total of 2948 Sentinel 1 and 743 Sentinel
2 images were selected (from February 2017 to August 2020)
and processed using GEE to enhance and unveil archeological
features. Outputs obtained from both Sentinel 1 and Sentinel
2 have been successfully compared with in situ analysis and
high-resolution Google Earth images
Archeologia preventiva: il ruolo delle analisi spaziali e del remote sensing nei modelli predittivi
In questo lavoro viene presentata la redazione di uno stato
dell'arte relativo alle applicazioni delle ICT, in particolare i
Dynamic Fire Danger Mapping from Satellite Imagery and Meteorological Forecast Data
Abstract
This study aims at ascertaining if and how remote sensing data can improve fire danger estimation based on meteorological variables. With this goal in mind, a dynamic estimation of fire danger was performed using an approach based on the integration of satellite information within a comprehensive fire danger rating system. The performances obtained with and without using satellite data were carried out for fires that occurred during the fire season in the year 2003 in the Calabria region (southern Italy). This study area was selected, first, because it is highly representative of Mediterranean ecosystems and, second, because it is an interesting test case for wildfire occurrences within the Mediterranean basin.
The results obtained have shown that the use of satellite data reduced efficiently the overestimated danger areas, thus improving at least by 10% the fire forecasting rate obtained without using satellite-based maps. Such findings can be directly extended to other similar Mediterranean ecosystems
Deformation analysis of a metropolis from C- to X-band PSI: proof-of-concept with Cosmo-Skymed over Rome, Italy
Stability of monuments and subsidence of residential
quarters in Rome (Italy) are depicted based on geospatial
analysis of more than 310,000 Persistent Scatterers (PS)
obtained from Stanford Method for Persistent Scatterers
(StaMPS) processing of 32 COSMO-SkyMed 3m-resolution
HH StripMap ascending mode scenes acquired between 21
March 2011 and 10 June 2013. COSMO-SkyMed PS
densities and associated displacement velocities are
compared with almost 20 years of historical C-band ERS-
1/2, ENVISAT and RADARSAT-1/2 imagery. Accounting
for differences in image processing algorithms and satellite
acquisition geometries, we assess the feasibility of ground
motion monitoring in big cities and metropolitan areas by
coupling newly acquired and legacy SAR in full time series.
Limitations and operational benefits of the transition from
medium resolution C-band to high resolution X-band PS
data are discussed, alongside the potential impact on the
management of expanding urban environments
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