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

Assessing Fire Severity in Semiarid Environments with the DNBR and RDNBR Indices

Available remote sensing historical Landsat TM images allow identifying of first order effects of wildfires also in huge and inaccessible regions. In this paper the usefulness of the best known satellitederived severity indices was tested on a large wildfire occurred in January 1999 in a steppe of Northwestern Patagonia. The main objective of the work was to analyze and compare the behavior of dNBR and RdNBR in their ability to discriminate the degrees of fire severity in semiarid ecosystems principally dominated by herbaceous vegetation. For this purpose the values of the two indexes were compared in all vegetation communities (shrubl and, meadow, grassland and forestation). To interpret the results, we considered the variability of the principal factors that influence the fire severity, as fire intensity, fire duration and vegetation susceptibility to fire. The analysis showed that the interaction between fire and vegetation changes the fire effects because the vegetation parameter as fuel load, moisture content, species composition, horizontal continuity and the topography affect the fire behavior and then the fire severity. Furthermore the results suggest that dNBR and RdNBR provide substantially different information respectively related to the effects on soil and vegetation. This work is an important contribution to the utilization of fire severity indexes in ecosystems dominated by herbaceous species that change more subtly the post-fire biomass than ecosystems dominated by woody species.Fil: 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; ArgentinaFil: Lanorte, Antonio. Consiglio Nazionale delle Ricerche; Italia. Istituto di Metodologie per l Analisi Ambientale; ItaliaFil: Oddi, Facundo José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural. - Universidad Nacional de Rio Negro. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural; ArgentinaFil: Lasaponara, Rosa. Consiglio Nazionale delle Ricerche; Italia. Istituto di Metodologie per l Analisi Ambientale; Itali