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The construction of dams and their impact on cultural heritage are an ever-expanding problem, the more so in times of climate change and narrowly focused development policies. We analyze here a case study represented by three major reservoirs in the Middle Euphrates valley in southeastern Turkey (Atatürk, Birecik and Karkamış). We applied Post-Flooding Damage Assessment (PFDA) to evaluate the impact of dams on archaeological sites. Our PFDA consists of the analysis of cross-correlation of multi-temporal Landsat imagery, geographical spatial datasets and archaeological data from surveys and excavations: it 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. Finally, we suggest an efficient methodology, a critical tool and recommendations for improving future designs of rescue archaeological projects targeting endangered cultural landscapes, with an immediately achievable target of a better-documented cultural heritage threatened by dams. In particular, we see a need to strengthen the existing legislation with specific working protocols providing guidelines on the identification, documentation and safeguard of the cultural heritage. These protocols must be supported by the state, which in turn must require their implementation by the bodies involved in the construction of the dams, such as the World Bank, the International Monetary Fund, the Asian Development Bank or the Inter-American Development Bank. In order to monitor the quality of whole work, the Turkish government should create a commission of international experts in the field of heritage with the purpose of monitoring the various projects from the proposal phase to completion of the last protocol.

Negli ultimi anni le agenzie umanitarie hanno ampliato il campo di utilizzo di immagini satellitari nella gestione delle emergenze - tipicamente impiegate a supporto della risposta a disastri naturali quali terremoti, alluvioni ed incendi - estendendolo alle crisi umanitarie. Il presente contributo è incentrato sull’analisi dell'evoluzione del campo di rifugiati siriani di Za'atari, istituito in territorio giordano nel luglio 2012 da parte della UN Refugee Agency (UNHCR). La metodologia di analisi multi-temporale è stata applicata su tre immagini satellitari ottiche ad alta risoluzione geometrica del campo profughi, elaborate mediante tecniche di classificazione assistita sia pixel-based sia object-based. L’elaborazione delle immagini è stata principalmente finalizzata all’analisi dell’evoluzione del campo ed alla stima della popolazione residente. Si è dimostrato come il telerilevamento satellitare possa fornire informazioni e dati dettagliati per la documentazione oggettiva a supporto della gestione di un'emergenza umanitaria.

Il lavoro si riferisce all’uso delle moderne tecniche geomatiche, in particolare il laser a scansione terrestre, per il rilevamento e la modellazione tridimensionale di una grande placca rocciosa ai fini di una accurata descrizione geometrica, nel supporto ad analisi di carattere geologico e per scopi di monitoraggio. L’esperienza illustrata si riferisce alla rupe su cui sorge l’abitato di San Leo (RN); la cittadina è situata sulla sommità di una placca lapidea di forma quadrangolare, con dimensioni di circa 500x600 m e delimitata da pareti verticali di altezza fino a circa 100 m. L’area è caratterizzata da fenomeni di instabilità dei versanti in evoluzione, il cui evento più recente è la frana che ha interessato la parete nordorientale nel 2014. Nel corso del 2013 è stato eseguito il rilievo dei versanti Sud e Ovest della rupe utilizzando il sistema Riegl VZ400 supportato dalla tecnica GNSS per l’allineamento e la georeferenziazione; il modello tridimensionale ottenuto è stato integrato per i rimanenti due versanti con nuvole di punti di minore densità acquisite da terzi in epoca precedente e per la parte sommitale con i dati altimetrici desunti da base cartografica, integrati e validati con un rilievo GNSS cinematico. La disponibilità di un modello tridimensionale dettagliato e georeferenziato della rupe ha consentito di effettuare analisi finalizzate all’individuazione delle discontinuità sull’intero ammasso roccioso, anche nelle zone difficilmente raggiungibili con i metodi tradizionali di rilievo geomeccanico. L’esperienza maturata, ancora in corso, ha evidenziato come, ad integrazione del rilievo tradizionale, la sinergia delle diverse metodologie adottate possa permettere un’investigazione accurata ed in remoto, in totale sicurezza, delle caratteristiche geologiche e geomorfologiche in contesti operativi che presentano problematiche oggettive di sicurezza ed accessibilità. Nella trattazione vengono descritte le fasi di rilievo ed elaborazione dati, evidenziando le problematiche operative e le soluzioni tecniche adottate, fino alla estrazione dei dati geometrici dal modello 3D della rupe. The work refers to the use of modern geomatic techniques, in particular the terrestrial laser scanning, for surveying and three-dimensional modelling of a large rock plate for the purpose of its accurate geometric description, in support to geological analyses and monitoring. The experience carried out is referred to San Leo’s cliff (RN); the town lays on the top of a quadrangular rock slab, with dimensions of about 500x600 m bounded by vertical walls of height up to about 100 m. The area is characterized by active and dormant slope instability processes, as the landslide which affected the northeastern wall in 2014. The survey of the side walls was performed with a terrestrial laser scanner supported by GNSS measurements for geo-referencing; the 3D model of the summit was completed with elevation data derived from cartographic database, integrated and validated with a kinematic GNSS survey. The availability of a complete three-dimensional model of the cliff, detailed and georeferenced, allowed the rock mass to be analysed, even in dangerous areas, difficult to be surveyed with traditional geomechanical methods. The experience has shown that, complementary to traditional surveys, the synergy of the different adopted approaches may allow an accurate investigation with no-contact – and then in complete safety - of geological and geomorphological characteristics also in contexts with serious accessibility issues. In the paper, the phases of survey and processing of the data will be described, highlighting the operational issues and the technical solutions for the extraction of geometric data from the 3D model of the cliff.

Over 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 disaster, flood catastrophes are considered to be the most costly, devastating, broad extent and frequent, because of the tremendous fatalities, injuries, property damage, 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 thesis. 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.

Una gestione efficiente del territorio richiede oggi la disponibilità di dati geografici esaustivi, accurati, aggiornati e supportati da potenti e complete banche dati; i più recenti sviluppi delle tecnologie geospaziali, sia in termini di hardware che di software, consentono di rispondere a questa richiesta con soluzioni sempre più efficaci. Il lavoro presenta alcuni esempi che evidenziano le grandi potenzialità in questa direzione, soffermandosi in particolare su due tecniche molto recenti e promettenti per applicazioni in ambito urbano, che sfruttano entrambe dati telerilevati: una metodologia ad oggetti per la classificazione del suolo mediante immagini satellitari ed aeree ad altissima risoluzione e l’uso di sistemi aviotrasportati a scansione laser per la modellazione tridimensionale dell’ambiente urbano. Le applicazioni che possono avvalersi di questi sistemi sono molteplici, sia per la mappatura e l’aggiornamento della situazione attuale che per il monitoraggio della sua evoluzione nel tempo.

The availability of multispectral images, with both high spatial and spectral resolution, makes it possible to obtain valuable information about complex urban environment, reducing the need for more expensive surveying techniques. Here, a methodology is tested for the semi-automatic extraction of buildings and the mapping of the main roofing materials over a urban area of approximately 100 km2, including the entire city of Bologna (Italy). The methodology follows an object-oriented approach and exploits a limited number of training samples. After a validation based on field inspections and close-range photos acquired by a drone, the final map achieved an overall accuracy of 94% (producer accuracy 79%) regarding the building extraction and of 91% for the classification of the roofing materials. The proposed approach proved to be flexible enough to catch the strong variability of the urban texture in different districts and can be easily reproducible in other contexts, as only satellite imagery is required for the mapping.

During the last years, remote sensing data along with GIS have been largely employed for supporting emergency management activities. In this context, the use of satellite images and derived map products has become more common also in the different phases of humanitarian crisis response. In this work very high resolution satellite imagery was processed to assess the evolution of Za’atari Refugee Camp, built in Jordan in 2012 by the UN Refugee Agency to host Syrian refugees. Multispectral satellite scenes of the Za’atari area were processed by means of object-based classifications. The main aim of the present work is the development of a semiautomated procedure for multi-temporal camp monitoring with particular reference to the dwellings detection. Whilst in the emergency mapping domain automation of feature extraction is widely investigated, in the field of humanitarian missions the information is often extracted by means of photointerpretation of the satellite data. This approach requires time for the interpretation; moreover, it is not reliable enough in complex situations, where features of interest are often small, heterogeneous and inconsistent. Therefore, the present paper discusses a methodology to obtain information for assisting humanitarian crisis management, using a semi-automatic classification approach applied to satellite imagery.

In this work, two processes related to the onset and the evolution of large-scale rockfalls have been analysed by means of remote sensing techniques. First, the number of rock bridges as a proportion of pre-existing fractures has been estimated in a newly formed landslide scarp by analysing the spectral information of the rock mass in terrestrial laser scanner (TLS) and unmanned aerial vehicle (UAV) photogrammetric point clouds. Second, the fragmentation of the rock mass after failure has been assessed by comparing the percentage of newly formed fractures in the scarp and in the deposit. For this purpose, an orthophoto of the landslide deposit was classified using an object-based method. The presented workflow gained new data on the intact rock breakage during and after failure, and consequently deepened knowledge about rock failure and fragmentation mechanisms.

Various regions in Europe have suffered from severe flooding over the last decades. Flood disasters often have a broad extent and a high frequency. They are considered the most devastating natural hazards because of the tremendous fatalities, injuries, property damages, economic and social disruption that they cause. In this context, Earth Observation techniques have become a key tool for flood risk and damage assessment. In particular, remote sensing facilitates flood surveying, providing valuable information, e.g. flood occurrence, intensity and progress of flood inundation, spurs and embankments affected/threatened. The present work aims to investigate the use of Very High Resolution satellite imagery for mapping flood-affected areas. The case study is the November 2013 flood event which occurred in Sardinia region (Italy), affecting a total of 2,700 people and killing 18 persons. The investigated zone extends for 28 km2 along the Posada river, from the Maccheronis dam to the mouth in the Tyrrhenian sea. A post-event SPOT6 image was processed by means of different classification methods, in order to produce the flood map of the analysed area. The unsupervised classification algorithm ISODATA was tested. A pixel-based supervised technique was applied using the Maximum Likelihood algorithm; moreover, the SPOT 6 image was processed by means of object-oriented approaches. The produced flood maps were compared among each other and with an independent data source, in order to evaluate the performance of each method, also in terms of time demand.

Land Use Land Cover Changes (LULCC) data provide objective information to support environmental policy, urban planning purposes and sustainable land development. Understanding of past land use/cover practices and current landscape patterns is critical to assess the effects of LULCC on the Earth system. Within the framework of soil sealing in Italy, the present study aims to assess the LULCC of the Nola area (Naples metropolitan area, Italy), relating to a thirty year period from 1984 to 2015. The urban sprawl affects this area causing the impervious surface increase, the loss in rural areas and landscape fragmentation. Located near Vesuvio volcano and crossed by artificial filled rivers, the study area is subject to landslide, hydraulic and volcanic risks. Landsat time series has been processed by means of the supervised per-pixel classification in order to produce multitemporal Land Use Land Cover maps. Then, post-classification comparison approach has been applied to quantify the changes occurring between 1984 and 2015, also analyzing the intermediate variations in 1999, namely every fifteen years. The results confirm the urban sprawl. The increase of the built-up areas mainly causes the habitat fragmentation and the agricultural land conversion of the Nola area that is already damaged by unauthorized disposal of urban waste. Moreover, considering the local risk maps, it was verified that some of the new urban areas were built over known hazardous sites. In order to limit the soil sealing, urgent measures and sustainable urban planning are required.

This work focuses on the exploitation of very high-resolution (VHR) satellite imagery coupled with multi-criteria analysis (MCA) to produce flood hazard maps. The methodology was tested over a portion of the Yialias river watershed basin (Nicosia, Cyprus). The MCA methodology was performed selecting five flood-conditioning factors: slope, distance to channels, drainage texture, geology and land cover. Among MCA methods, the analytic hierarchy process technique was chosen to derive the weight of each criterion in the computation of the flood hazard index (FHI). The required information layers were obtained by processing a VHR GeoEye-1 image and a digital elevation model. The satellite image was classified using an object-based technique to extract land use/cover data, while GIS geoprocessing of the DEM provided slope, stream network and drainage texture data. Using the FHI, the study area was finally classified into seven hazard categories ranging from very low to very high in order to generate an easily readable map. The hazard seems to be severe, in particular, in some urban areas, where extensive anthropogenic interventions can be observed. This work confirms the benefits of using remote sensing data coupled with MCA approach to provide fast and cost-effective information concerning the hazard assessment, especially when reliable data are not available.