No abstract

Orthometric heights, useful for many engineering and geoscience applications, can be obtained by GPS (Global Positioning System) surveys only when an accurate geoid undulation model (that supplies the vertical separation between the geoid and WGS84 ellipsoid) is available for the considered topic area. Global geoid height models (i.e., EGM2008), deriving from satellite gravity measurements suitably integrated with other data are free available on web, but their accuracy is often not sufficient for the user’s purposes. More accurate local models can nevertheless be acquired, but often only for a fee. GPS/levelling surveys are suitable for determining a local, accurate geoid model, but may be too expensive. This paper aims to demonstrate that GNSS (Global Navigation Satellite System) Permanent Station documents (monographs), freely available on the web and supplying orthometric and ellipsoidal heights, permit to calculate precise geoidal undulations useful to perform global geoid modelling on a local area. In fact, in this study 25 GNSS Permanent Stations (GNSS PS), located in North-Western Italy are considered: the differences between GNSS PS geoidal heights and the corresponding EGM2008 1′ × 1′ ones are used as a starting dataset for Ordinary Kriging applications. The resulting model is summed to the EGM2008 1′ × 1′, obtaining a better-performed model of the interest area. The accuracy tests demonstrate that the resulting model is better than EGM2008 grids to produce contours from a GPS dataset for large-scale mapping.

No abstract

Coastline extraction techniques from multispectral satellite images are of great interest for protection and monitoring of coastal areas. In this regard, the Sentinel-2 satellites can give a great contribution thanks to their wide coverage of the earth's surface. These images can be processed by GIS software, so as to detect the sea from all the rest. However, the traditional supervised classification requires the involvement of the operator to create suitable training sites: this approach, in addition to being associated to the operator's skill, often takes a long time to be completed. This contribution presents a study carried out on Sentinel-2 dataset and proposes the application of an unsupervised classification method, the k-means, on four different classification indices. The coastlines extracted by unsupervised classification are therefore compared with the coastline manually vectorized from the RGB composition. The results demonstrate the effectiveness of k-means for distinguishing, in the images produced by the indices application, two clusters (water / no-water) in a reduced time lapse if compared with the traditional supervised techniques.

The goal of this research was the creation of software tools for managing instances of a multi - representation geodatabase, able to define multiple representations and topological constraints, in relation to modeled objects and structures according to the classification of the Italian national technical specifications of the November 10, Italian Ministerial Decree 2011. After the development of a conceptual scheme, encoded in its corresponding logical mode, various computer artifacts were designed and developed from scratch to perform the upload, management and display of data: a Scheme Designer, which allows users to define the logical model and implement the physical model of an instance of Oracle; a Loader, which allows users to populate the database; a GUI, which is a graphical interface to the tools and Schema Designer Loader; a DB Navigator, which is the web interface to the database multi - representation.