1,720,968 research outputs found
The use of satellite remote sensing for flood risk and management
No full textOver the last decades the impact of natural disasters to the global environment is becoming more and more severe. The number of disasters has dramatically increased, as well as the cost to the global economy and the number of people affected. Among the natural disasters, flood catastrophes are considered to be the most costly, devastating, broad extent and frequent, because of the tremendous fatalities, injuries, property damages, economic and social disruption they cause to the humankind. In the last thirty years, the World has suffered from severe flooding and the huge impact of floods has caused hundreds of thousands of deaths, destruction of infrastructures, disruption of economic activity and the loss of property for worth billions of dollars.
In this context, satellite remote sensing, along with Geographic Information Systems (GIS), has become a key tool in flood risk management analysis.
Remote sensing for supporting various aspects of flood risk management was investigated in the present work. In particular, the research focused on the use of satellite images for flood mapping and monitoring, damage assessment and risk assessment. The contribution of satellite remote sensing for the delineation of flood prone zones, the identification of damaged areas and the development of hazard maps was explored referring to selected cases of study
TWI computation: a comparison of different open source GISs
Full text linkThe opportunities of retrieving geospatial datasets as open data and the reliability of Free and Open Source Software (FOSS) GIS increased the possibilities of performing a large number of geospatial analyses. In particular, the worldwide availability of Digital Elevation Model (DEM) permits to compute several topographic indexes able to characterize the land morphology.
In this paper, we evaluate the performances of different open source GIS in the calculation of the Topographic Wetness Index (TWI), a widespread index in hydrological analysis that describes the tendency of an area to accumulate water. Nowadays, there is a large number of available open source desktop GIS, maintained as FOSS projects, each of them focusing on developing specific goals. Therefore, from user point of view, the choice of the best software in solving a particular task is influenced by the GIS specific features.
The test was performed computing the TWI for the Rio Sinigo basin, in northern Italy. The DEM of the test area has been processed with GRASS GIS, Whitebox GAT and SAGA GIS. In order to identify equal workflows, all the combinations of available algorithms and parameters have been studied for each considered GIS. The final TWI maps produced as output were compared and discussed
Mappatura dei materiali di copertura degli edifici da immagini WorldView-3
No full textLa disponibilità di immagini satellitari ad alta risoluzione sia spettrale che spaziale amplia notevolmente la gamma di applicazioni del telerilevamento in ambito urbano. In particolare, le immagini WorldView-3 (WV3) si compongono di una banda pancromatica con risoluzione spaziale di 0,3 m, 8 bande nel visibile e infrarosso vicino (VNIR) a 1,2 m e 8 bande nell’infrarosso ad onde corte (SWIR) a 3,4 m. Il presente studio si propone di valutare le potenzialità di queste immagini per l’identificazione di edifici e la classificazione dei materiali di copertura. L’area di studio scelta per la sperimentazione comprende l’intera area urbana di Bologna (100 km2), su cui sono state acquisite due coppie stereoscopiche pancromatiche e multispettrali ed una immagine nello SWIR. Per l’estrazione degli edifici, si è scelto un approccio orientato a oggetti, basato sia sulle informazioni morfologiche derivanti dal DSM che sulle informazioni spettrali e tessiturali derivanti dalle immagini multispettrali. Le classi identificate comprendono i principali materiali di copertura utilizzati nell’area, cioè coppi in argilla, guaine bituminose, fogli metallici di diverse colorazioni e coperture in ghiaia (lavata o sciolta). Ai fini del training del classificatore e della successiva validazione, è stato compilato un database di verità a terra riguardante circa 150 edifici, sulla base di rilievi in situ effettuati con un drone e alcuni sopralluoghi diretti. Dalla matrice di confusione è risultata un’accuratezza complessiva pari al 91% (K 0,89) sulla classificazione dei materiali di copertura. La procedura proposta si basa unicamente sulle immagini satellitari acquisite e può quindi essere facilmente replicata in qualsiasi contesto urbano
Archaeology and Dams in Southeastern Turkey: Post-Flooding Damage Assessment and Safeguarding Strategies on Cultural Heritage
Full text linkThe construction of dams is an ever-growing threat to cultural heritage, particularly in an age of climate change and narrowly focused development policies. In analyzing as a case study three major reservoirs in the Middle Euphrates river valley in southeastern Turkey (Atatürk, Birecik and Karkamış), we developed a Post-Flooding Damage Assessment (PFDA) to evaluate the impact of dams on archaeological sites. Our PFDA, consisting of an analysis of cross-correlations between multi-temporal Landsat imagery, geographical spatial datasets and archaeological data from surveys and excavations, provides an unprecedented detailed overview of the loss of especially significant cultural landscapes, and also highlights the limited accuracy of pre-flooding archaeological surveys and excavations. We conclude with recommendations for improving how rescue archaeological projects targeting endangered cultural landscapes are designed, with an immediately achievable target of better documenting cultural heritage threatened by dams
Applicazioni in ambito urbano di stereo-coppie WorldView-3
Full text linkIl satellite WorldView-3 (WV3) è l’ultimo in ordine cronologico della costellazione DigitalGlobe di satelliti ad altissima risoluzione sia spaziale che spettrale. In particolare le stereo-coppie nella banda del pancromatico presentano una risoluzione geometrica al nadir di 0.31 m, che rende questo il satellite commerciale con la più alta risoluzione ad oggi disponibile. Queste caratteristiche aprono la strada a nuove applicazioni specialmente in area urbana, dove la complessità della morfologia richiede un più elevato grado di dettaglio. Il lavoro presentato si propone di analizzare e descrivere le performance in termini di accuratezza di questo dato satellitare sia per la generazione di Digital Elevation Model (DEM) di aree urbane, sia per l’estrazione automatica di feature di interesse come edifici e materiali di copertura attraverso tecniche di classificazione object-oriented. In particolare il dataset comprende sei immagini WV3 della città di Bologna; per la validazione dei DEM sono stati utilizzati dati LIDAR e un modello fotogrammetrico ottenuto da immagini oblique, mentre per la validazione delle classificazioni si è fatto riferimento alla carta tecnica comunale e ad alcune ispezioni da drone. La sperimentazione condotta ha evidenziato come le caratteristiche morfologiche dell’area rilevata e la geometria di acquisizione influenzino notevolmente i risultati ottenibili, in termini di completezza e accuratezza; in particolare alcune problematiche sono emerse in corrispondenza di strade strette e di particolari edifici, come le torri. I buoni risultati ottenuti invece in corrispondenza dei tetti (accuratezza nell’ordine di 1-2 pixel) rendono i DEM prodotti idonei per la generazione di ortofoto e successive operazioni di classificazione
Use of Landsat imagery to detect land cover changes for monitoring soil sealing; case study: Bologna province (Italy)
No full textLandsat archives (made accessible by USGS at no charge since 2011) have made available to the scientific community a large amount of satellite multispectral images, providing new opportunities for environmental information, such as the analysis of land use/cover changes, which represent important tools for planning and sustainable land management. Processing a time series images, the creation of land cover maps has been improved in order to analyze phenomena such as the soil sealing. The main topic of this work is in fact the detection of roads and buildings construction or everything that involve soil removing. This subject is highly relevant, given the impact of the phenomenon on land use planning, environmental sustainability, agricultural policies and urban runoff. The analysis, still in progress, has been applied to Bologna Province (Emilia-Romagna Region, Italy) that covers 3703 Km2. This area is strongly urbanized: 8,9% of the total surface is sealed against a national value of 6,7%, with the soil sealing rate which has been defined from recent studies as the fourth Italian value in the 2001/2011 period. Other information available for this territory derive from CORINE Land Cover and Copernicus Projects. In the first one, the minimum mapping unit is 25 ha and the one for change is 5 ha; these values are too large for an accurate detection of the soil sealing dynamics. On the other hand, the Copernicus Project provides an imperviousness layer with a better resolution (20x20 m2), but its maps start from 2006. Therefore, the potential of multispectral remote sensing analysis over large areas and the multitemporal Landsat availability have been combined for a better knowledge about land cover changes. For this work, Landsat 5 and Landsat 8 images have been acquired between 1987 and 2013, according to basic requirements as low cloud cover and a common acquisition season (summer). A supervised pixel-based classification has been performed, with maximum likelihood algorithm. Due to landscape heterogeneity, classification has been improved with auxiliary data, such as NDVI. Therefore, the obtained maps have been compared with a post-classification change detection procedure in order to quantify land use changes, with particular attention to the soil sealing increase
Remote sensing analysis for flood risk management in urban sprawl contexts
No full textRemote sensing can play a key role in risk assessment and management, especially when several concurrent factors coexist, such as a predisposition to natural disasters and the urban sprawl, spreading over highly vulnerable areas. In this context, multitemporal analysis can provide decision-makers with tools and information to reduce the impacts of disasters (e.g. flooding) and to encourage a sustainable development. The present work focuses on the employment of multispectral satellite imagery to produce multitemporal land use/cover maps for the city of Dhaka, which is subject to frequent flooding events. In particular, the evaluation of the urban growth, the analysis of the annual dynamics of flooding and the study of the 2004 catastrophic event were performed. For the change-detection procedure, Landsat images were used. These images allow the quantification of the very rapid growth of the metropolis, with an increase in built-up areas from 75 to 111 km2. The image of 2009 showed that an ordinary flood affects about 115 km2 (on a studied area of 591 km2). On the other hand, the analysis of the 2004 extreme flooding event, performed on a wider area, showed that the affected lands added up to 750 km2 (on about 3845 km2)
Integration of different geospatial data in urban areas: a case of study
No full textEfficient management of the territory requires today the availability of comprehensive geographical data, accurate and up to date, supported by powerful databases. In this context, remote sensing data are used for a variety of applications related to urban areas; some examples are land use/cover mapping, urban growth and soil sealing evaluation, detection of green areas, updating of existing maps, energy applications and detection and characterization of buildings. This work aims to highlight how different geomatic techniques and data acquired from heterogeneous surveys can be today used together for producing or updating a digital cartography inside a GIS. The study has been conducted in the urban area of Bologna, Emilia-Romagna region, located in the North of Italy. A high resolution WorldView-2 satellite image and the DSM/DTM, obtained by airborne LiDAR, have been used to obtain a vector layer of the buildings. In particular, to distinguish the buildings among all the elements present in the study area, such as roads, trees, vegetated areas, etc., an object-oriented classification has been performed. This approach, working on groups of pixels (image objects), allows to expand the information content of the basic unit of classification. Therefore, features such as shape, texture and contextual information, coupled with spectral characteristics, potentially allow cartographers to generate products that are competitive, in terms of thematic contents, with those derived from the photo-interpretation. A first application described in this work is to perform a quick change analysis procedure based on the results of the classification compared to an existing numerical cartographic base or a previous classification
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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