One-Page Multimedia Interactive Map

The relevance of local knowledge in cultural heritage is by now acknowledged. It helps to determine many community-based projects by identifying the material to be digitally maintained in multimedia collections provided by communities of volunteers, rather than for-profit businesses or government entities. Considering that the search and browsing of texts, images, video, and 3D models related to places is more essential than using a simple text-based search, an interactive multimedia map was implemented in this study. The map, which is loaded on a single HyperText Markup Language (HTML) page using AJAX (Asynchronous JavaScript and XML), with a client-side control mechanism utilising jQuery components that are both freely available and ad-hoc developed, is updated according to user interaction. To simplify the publication of geo-referenced information, the application stores all the data in a Geographic JavaScript Object Notation (GeoJSON) file rather than in a database. The multimedia contents—associated with the selected Points of Interest (PoIs)—can be selected through text search and list browsing as well as by viewing their previews one by one in a sequence all together in a scrolling window (respectively: “Table”, “Folder”, and “Tile” functions). PoIs—visualised on the map with multi-shape markers using a set of unambiguous colours—can be filtered through their categories and types, accessibility status and timeline, thus improving the system usability. The map functions are illustrated using data collected in a Comenius project. Notes on the application software and architecture are also presented in this paper

The Albanian Cultural Heritage on the Internet

EnThe paper discusses the production of an interactive map (both for desktop and for mobile) aiming to support the promotion of the cultural heritage, using an authoring system. At present, the tools feature 13 heritage sites across the County of Tirana, which are supported by text and photographs supplied by IMK - Instituti i Monumenteve te Kultures ‘Gani Strazimiri’ (Institute for Cultural Monuments) within the project ‘S.O.S. – Squiperia Open Source’, funded by the Apulia Region. We include experience of developing the tools as a possible benefit to other developers in the cultural sector.ItL'articolo illustra la produzione di una mappa interattiva (per sistemi 'desktop' e 'mobile') finalizzata a dare supporto alla promozione del patrimonio culturale, realizzata mediante un sistema autore. Attualmente il sistema gestisce 13 siti di interesse culturale collocati nel distretto di Tirana in Albania, con testi e fotografie fornite da IMK - Instituti i Monumenteve te Kultures 'Gani Strazimiri' (Istituto per i Monumenti della Cultura) nell'ambito del progetto 'S.O.S. - Squiperia Open Source', finanziato dalla Regione Puglia. La descrizione del sistema può essere utile agli sviluppatori che operano nel settore culturale.

Smart Tirana

Albania represents an interesting case of a newly emerging destination in the international tourist market, with intensive pressures coming from seasonal visit flows and the related impacts on the environment. The Albanian Culture Marketing Strategy, while correctly focusing on heritage for the de-seasoning of visits in congested areas and for awareness-raising about the country’s cultural identity among tourists and residents, presents some limitations in the definition of application patterns and concrete solutions. In particular, the active contribution of potential users, of ICTs and, in particular, the potentialities of widespread tools such as mobile apps seem to be overlooked. In this article, the current scenario of the Albanian tourism sector, with particular emphasis on the cultural segment, is presented through a detailed analysis of relevant program documents in order to outline strengths and weaknesses of the underlying approach. Then, the potential contribution of mobile apps to the sustainable development of destinations are analyzed and the market of available technologies is presented through a taxonomy of a consistent number of representative cases. Finally, the SOS-Tirana app is presented and its adequateness to the context is discussed

Flood Susceptibility Mapping Using SAR Data and Machine Learning Algorithms in a Small Watershed in Northwestern Morocco

Flood susceptibility mapping plays a crucial role in flood risk assessment and management. Accurate identification of areas prone to flooding is essential for implementing effective mitigation measures and informing decision-making processes. In this regard, the present study used high-resolution remote sensing products, i.e., synthetic aperture radar (SAR) images for flood inventory preparation and integrated four machine learning models (Random Forest: RF, Classification and Regression Trees: CART, Support Vector Machine: SVM, and Extreme Gradient Boosting: XGBoost) to predict flood susceptibility in Metlili watershed, Morocco. Initially, 12 independent variables (elevation, slope angle, aspect, plan curvature, topographic wetness index, stream power index, distance from streams, distance from roads, lithology, rainfall, land use/land cover, and normalized vegetation index) were used as conditioning factors. The flood inventory dataset was divided into 70% and 30% for training and validation purposes using a popular library, scikit-learn (i.e., train_test_split) in Python programming language. Additionally, the area under the curve (AUC) was used to evaluate the performance of the models. The accuracy assessment results showed that RF, CART, SVM, and XGBoost models predicted flood susceptibility with AUC values of 0.807, 0.780, 0.756, and 0.727, respectively. However, the RF model performed better at flood susceptibility prediction compared to the other models applied. As per this model, 22.49%, 16.02%, 12.67%, 18.10%, and 31.70% areas of the watershed are estimated as being very low, low, moderate, high, and very highly susceptible to flooding, respectively. Therefore, this study showed that the integration of machine learning models with radar data could have promising results in predicting flood susceptibility in the study area and other similar environments

Hybrid Machine Learning Approach for Gully Erosion Mapping Susceptibility at a Watershed Scale

Gully erosion is a serious threat to the state of ecosystems all around the world. As a result, safeguarding the soil for our own benefit and from our own actions is a must for guaranteeing the long-term viability of a variety of ecosystem services. As a result, developing gully erosion susceptibility maps (GESM) is both suggested and necessary. In this study, we compared the effectiveness of three hybrid machine learning (ML) algorithms with the bivariate statistical index frequency ratio (FR), named random forest-frequency ratio (RF-FR), support vector machine-frequency ratio (SVM-FR), and naïve Bayes-frequency ratio (NB-FR), in mapping gully erosion in the GHISS watershed in the northern part of Morocco. The models were implemented based on the inventory mapping of a total number of 178 gully erosion points randomly divided into 2 groups (70% of points were used for training the models and 30% of points were used for the validation process), and 12 conditioning variables (i.e., elevation, slope, aspect, plane curvature, topographic moisture index (TWI), stream power index (SPI), precipitation, distance to road, distance to stream, drainage density, land use, and lithology). Using the equal interval reclassification method, the spatial distribution of gully erosion was categorized into five different classes, including very high, high, moderate, low, and very low. Our results showed that the very high susceptibility classes derived using RF-FR, SVM-FR, and NB-FR models covered 25.98%, 22.62%, and 27.10% of the total area, respectively. The area under the receiver (AUC) operating characteristic curve, precision, and accuracy were employed to evaluate the performance of these models. Based on the receiver operating characteristic (ROC), the results showed that the RF-FR achieved the best performance (AUC = 0.91), followed by SVM-FR (AUC = 0.87), and then NB-FR (AUC = 0.82), respectively. Our contribution, in line with the Sustainable Development Goals (SDGs), plays a crucial role for understanding and identifying the issue of “where and why” gully erosion occurs, and hence it can serve as a first pathway to reducing gully erosion in this particular area

Remote Sensing Data for Geological Mapping in the Saka Region in Northeast Morocco: An Integrated Approach

Together with geological survey data, satellite imagery provides useful information for geological mapping. In this context, the aim of this study is to map geological units of the Saka region, situated in the northeast part of Morocco based on Landsat Oli-8 and ASTER images. Specifically, this study aims to: (1) map the lithological facies of the Saka volcanic zone, (2) discriminate the different minerals using Landsat Oli-8 and ASTER imagery, and (3) validate the results with field observations and geological maps. To do so, in this study we used different techniques to achieve the above objectives including color composition (CC), band ratio (BR), minimum noise fraction (MNF), principal component analysis (PCA), and spectral angle mapper (SAM) classification. The results obtained show good discrimination between the different lithological facies, which is confirmed by the supervised classification of the images and validated by field missions and the geological map with a scale of 1/500,000. The classification results show that the study area is dominated by Basaltic rocks, followed by Trachy andesites then Hawaites. These rocks are encased by quaternary sedimentary rocks and an abundance of Quartz, Feldspar, Pyroxene, and Amphibole minerals

SCIRES-IT Volume 3, Issue 2 (2013)

SCIRES-IT, e-ISSN 2239-4303, provides a forum for the exchange and sharing of know-how in the areas of Digitalization and Multimedia Technologies and Information & Communication Technology (ICT) in support of Cultural and environmental Heritage (CH) documentation, preservation and fruition. It publishes comprehensive reviews on specific fields, regular research papers and short communications in a timely fashion