Search results for " geomatics"
showing 10 items of 479 documents
Hydro-mechanical analysis of volcanic ash slopes during rainfall
2016
Rainfall-induced landslides in volcanic ashes represent a major natural hazard in many regions around the world. Owing to their loose structure, volcanic ash slopes are prone to rainfall-induced landslides. The paper presents a continuum modelling approach for the analysis of wetting-induced instability phenomena at the onset of failure in loose volcanic ash slopes. A numerical simulation of a landslide-prone volcanic slope in Costa Rica is carried out with a two-dimensional hydro-mechanical finite-element slope model. A constitutive model based on the effective stress concept extended to partially saturated conditions is used to reproduce the volcanic ash hydro-mechanical behaviour. The m…
AUGMENTED REALITY FOR CULTURAL HERITAGE: THE REBIRTH OF A HISTORICAL SQUARE
2019
Abstract. The case study, faced in this paper, arises in the context of Interreg Italia-Malta European project named I-Access, dedicated to the improvement of accessibility to Cultural Heritage (CH). Accessibility considered not only as the demolition of physical architectural barriers, but also as the possibility of fruition of CH through technological tools that can increase its perception and knowledge. Last achievements in photogrammetry and terrestrial laser scanner (TLS) technology offered new methods of data acquisition in the field of CH, giving the possibility of monitoring and processing big data, in the form of point clouds. Ever in this field, reverse engineering techniques and …
UAS BASED TREE SPECIES IDENTIFICATION USING THE NOVEL FPI BASED HYPERSPECTRAL CAMERAS IN VISIBLE, NIR AND SWIR SPECTRAL RANGES
2016
Abstract. Unmanned airborne systems (UAS) based remote sensing offers flexible tool for environmental monitoring. Novel lightweight Fabry-Perot interferometer (FPI) based, frame format, hyperspectral imaging in the spectral range from 400 to 1600 nm was used for identifying different species of trees in a forest area. To the best of the authors’ knowledge, this was the first research where stereoscopic, hyperspectral VIS, NIR, SWIR data is collected for tree species identification using UAS. The first results of the analysis based on fusion of two FPI-based hyperspectral imagers and RGB camera showed that the novel FPI hyperspectral technology provided accurate geometric, radiometric and sp…
HYPERSPECTRAL REFLECTANCE SIGNATURES AND POINT CLOUDS FOR PRECISION AGRICULTURE BY LIGHT WEIGHT UAV IMAGING SYSTEM
2018
Abstract. The objective of this investigation was to study the use of a new type of a low-weight unmanned aerial vehicle (UAV) imaging system in the precision agriculture. The system consists of a novel Fabry-Perot interferometer based hyperspectral camera and a high-resolution small-format consumer camera. The sensors provide stereoscopic imagery in a 2D frame-format and they both weigh less than 500 g. A processing chain was developed for the production of high density point clouds and hyperspectral reflectance image mosaics (reflectance signatures), which are used as inputs in the agricultural application. We demonstrate the use of this new technology in the biomass estimation process, w…
VARIABILITY OF REMOTE SENSING SPECTRAL INDICES IN BOREAL LAKE BASINS
2018
Remotely sensed hyperspectral data has widely been used to determine water quality parameters in oceanic waters. However in freshwater basins the dependence between the hyperspectral data and the parameters is more complicated. In this work some ideas are presented concerning the study of this dependence. The data used in this study were collected from the lake Hiidenvesi in southern Finland. The hyperspectral data consists of reflectances in 36 bands in the wavelength area 508…878 nm and the separately measured water quality parameters are turbidity, blue-green algae, chlorophyll, pH and dissolved oxygen. Hyperspectral data was used as bare band reflectances, but also in the …
CHOOSING OF OPTIMAL REFERENCE SAMPLES FOR BOREAL LAKE CHLOROPHYLL A CONCENTRATION MODELING USING AERIAL HYPERSPECTRAL DATA
2018
Abstract. Optical remote sensing has potential to overcome the limitations of point estimations of lake water quality by providing spatial and temporal information. In open ocean waters the optical properties are dominated by phytoplankton density, while the relationship between color and the constituents is more complicated in inland waters varying regionally and seasonally. Concerning the difficulties relating to comprehensive modeling of complex inland and coastal waters, the alternative approach is considered in this paper: the raw digital numbers (DN) recorded using aerial remote hyperspectral sensing are used without corrections and derived by means of regression modeling to predict C…
3D VIRTUAL CH INTERACTIVE INFORMATION SYSTEMS FOR A SMART WEB BROWSING EXPERIENCE FOR DESKTOP PCS AND MOBILE DEVICES
2018
Abstract. Recently, the diffusion of knowledge on Cultural Heritage (CH) has become an element of primary importance for its valorization. At the same time, the diffusion of surveys based on UAV Unmanned Aerial Vehicles (UAV) technologies and new methods of photogrammetric reconstruction have opened new possibilities for 3D CH representation. Furthermore the recent development of faster and more stable internet connections leads people to increase the use of mobile devices. In the light of all this, the importance of the development of Virtual Reality (VR) environments applied to CH is strategic for the diffusion of knowledge in a smart solution. In particular, the present work shows how, s…
Minimal learning machine in anomaly detection from hyperspectral images
2020
Abstract. Anomaly detection from hyperspectral data needs computationally efficient methods to process the data when the data gathering platform is a drone or a cube satellite. In this study, we introduce a minimal learning machine for hyperspectral anomaly detection. Minimal learning machine is a novel distance-based classification algorithm, which is now modified to detect anomalies. Besides being computationally efficient, minimal learning machine is also easy to implement. Based on the results, we show that minimal learning machine is efficient in detecting global anomalies from the hyperspectral data with low false alarm rate.
SURVEY AND VIRTUAL RECONSTRUCTION OF ANCIENT ROMAN FLOORS IN AN ARCHAEOLOGICAL CONTEXT
2019
Abstract. Despite the consistent development of approaches aimed at the virtual reconstruction of whole houses or archaeological monuments, the variety of technologies involved in virtual reconstruction procedures and the complexity of a rigorous process to provide validation models, seems to limit a univocal and shared standards adoption. For example, compared to the large number of contributions on the virtual reconstruction of whole architectures or cultural heritage sites, only a few works have proposed a rigorous workflow specific to mosaics and ancient floors and to their virtual reconstruction. The goal of this work is to present the first results on the virtual reconstruction of the…
DEVELOPING A 3D ROAD CADASTRAL SYSTEM: COMPARING LEGAL REQUIREMENTS AND USER NEEDS
2018
Abstract. Road transport has always played an important role in a country’s growth and, in order to manage road networks and ensure a high standard of road performance (e.g. durability, efficiency and safety), both public and private road inventories have been implemented using databases and Geographical Information Systems. They enable registering and managing significant amounts of different road information, but to date do not focus on 3D road information, data integration and interoperability. In an increasingly complex 3D urban environment, and in the age of smart cities, however, applications including intelligent transport systems, mobility and traffic management, road maintenance an…