Integrating elevation data and multispectral high-resolution images for an improved hybrid Land Use/Land Cover mapping

ABSTRACTThe combination of elevation data together with multispectral high-resolution images is a new methodology for obtaining land use/land cover classification. It represents a step forward for both the accuracy and automation of LULC applications and allows users to setup thematic assignments through rules based on feature attributes and human expert interpretation of land usage. The synergy between different types of information means that LiDAR can give new hints at both the segmentation and hybrid classification steps, leading to a joint use of multispectral, spatial and elevation data. The output is a thematic map characterized by a custom-designed legend that is able to discriminate between land cover classes with similar spectral characteristics (level 3 of the CLC legend). Experimental results from a hilly farmland area with some urban structures (Musone river basin, Ancona, Italy) are used to highlight how the proposed methodology enhances land cover classification in heterogeneous environments

SIT-REM: An Interoperable and Interactive Web Geographic Information System for Fauna, Flora and Plant Landscape Data Management

none10The main goal of the SIT-REM project is the design and the development of an interoperable web-GIS environment for the information retrieval and data editing/updating of the geobotanical and wildlife map of Marche Region. The vegetation, plant landscape and faunistic analysis allow the realization of a regional information system for wildlife-geobotanical data. A main characteristic of the SIT-REM is its flexibility and interoperability, in particular, its ability to be easily updated with the insertion of new types of environmental, faunal or socio-economic data and to generate analyses at any geographical (from regional to local) or quantitative level of detail. Different query levels obtain the latter: spatial queries, hybrid query builder and WMSs usable by means of a GIS. SIT-REM has been available online for more than a year and its use over this period has produced extensive data about users' experiences.. © 2014 by the authors; licensee MDPI, Basel, SwitzerlandFrontoni, Emanuele; Mancini, Adriano; Zingaretti, Primo; Malinverni, Eva; Pesaresi, Simone; Biondi, Edoardo; Pandolfi, Massimo; Marseglia, Maria; Sturari, Mirco; Zabaglia, ClaudioFrontoni, Emanuele; Mancini, Adriano; Zingaretti, Primo; Malinverni, Eva Savina; Pesaresi, Simone; Biondi, Edoardo; Pandolfi, Massimo; Marseglia, Maria; Sturari, Mirco; Zabaglia, Claudi

Processing and visualization of multi-source data in next-generation geospatial applications

Le applicazioni geospaziali di nuova generazione come dati non usano semplicemente punti, linee e poligoni, ma oggetti complessi o evoluzioni di fenomeni che hanno bisogno di tecniche avanzate di analisi e visualizzazione per essere compresi. Le caratteristiche di queste applicazioni sono l'uso di dati multi-sorgente con diverse dimensioni spaziali, temporali e spettrali, la visualizzazione dinamica e interattiva con qualsiasi dispositivo e quasi ovunque, anche sul campo. L'analisi dei fenomeni complessi ha utilizzato fonti dati eterogenee per formato/tipologia e per risoluzione spaziale/temporale/spettrale, che rendono problematica l'operazione di fusione per l'estrazione di informazioni significative e immediatamente comprensibili. L'acquisizione dei dati multi-sorgente può avvenire tramite diversi sensori, dispositivi IoT, dispositivi mobili, social media, informazioni geografiche volontarie e dati geospaziali di fonti pubbliche. Dato che le applicazioni geospaziali di nuova generazione presentano nuove caratteristiche, per visualizzare i dati grezzi, i dati integrati, i dati derivati e le informazioni è stata analizzata l'usabilità di tecnologie innovative che ne consentano la visualizzazione con qualsiasi dispositivo: dashboard interattive, le viste e le mappe con dimensioni spaziali e temporali, le applicazioni di Augmented e Virtual Reality. Per l'estrazione delle informazioni in modo semi-automatico abbiamo impiegato varie tecniche all'interno di un processo sinergico: segmentazione e identificazione, classificazione, rilevamento dei cambiamenti, tracciamento e clustering dei percorsi, simulazione e predizione. All'interno di un workflow di elaborazione, sono stati analizzati vari scenari e implementate soluzioni innovative caratterizzate dalla fusione di dati multi-sorgente, da dinamicità e interattivà. A seconda dell'ambito applicativo le problematiche sono differenziate e per ciascuno di questi sono state implementate le soluzioni più coerenti con suddette caratteristiche. In ciascuno scenario presentato sono state trovate soluzioni innovative che hanno dato buoni risultati, alcune delle quali in nuovi ambiti applicativi: (i) l'integrazione di dati di elevazione e immagini multispettrali ad alta risoluzione per la mappatura Uso del Suolo / Copertura del Suolo, (ii) mappatura con il contributo volontario per la protezione civile e la gestione delle emergenze (iii) la fusione di sensori per la localizzazione e il tracciamento in ambiente retail, (iv) l'integrazione dei dati in tempo reale per la simulazione del traffico nei sistemi di mobilità, (v) la combinazione di informazioni visive e di nuvole di punti per la rilevazione dei cambiamenti nell'applicazione della sicurezza ferroviaria. Attraverso questi esempi, i suggerimenti potranno essere applicati per realizzare applicazioni geospaziali anche in ambiti diversi. Nel futuro sarà possibile aumentare l'integrazione per realizzare piattaforme data-driven come base per sistemi intelligenti: un'interfaccia semplice per l'utente che metta a disposizione funzionalità avanzate di analisi costruite su algoritmi affidabili ed efficienti.Next-generation geospatial applications as data do not simply use dots, lines, and polygons, but complex objects or evolution of phenomena that need advanced analysis and visualization techniques to be understood. The features of these applications are the use of multi-source data with different spatial, temporal and spectral dimensions, dynamic and interactive visualization with any device and almost anywhere, even in the field. Complex phenomena analysis has used heterogeneous data sources for format/typology and spatial/temporal/spectral resolution, which challenging combining operation to extract meaningful and immediately comprehensible information. Multi-source data acquisition can take place through various sensors, IoT devices, mobile devices, social media, voluntary geographic information and geospatial data from public sources. Since next-generation geospatial applications have new features to view raw data, integrated data, derived data, and information, wh have analysed the usability of innovative technologies to enable visualization with any device: interactive dashboards, views and maps with spatial and temporal dimensions, Augmented and Virtual Reality applications. For semi-automatic data extraction we have used various techniques in a synergistic process: segmentation and identification, classification, change detection, tracking and path clustering, simulation and prediction. Within a processing workflow, various scenarios were analysed and implemented innovative solutions characterized by the fusion of multi-source data, dynamism and interactivity. Depending on the application field, the problems are differentiated and for each of these the most coherent solutions have been implemented with the aforementioned characteristics. Innovative solutions that have yielded good results have been found in each scenario presented, some of which are in new applications: (i) integration of elevation data and multispectral high-resolution images for Land Use/Land Cover mapping, (ii) crowd-mapping for civil protection and emergency management, (iii) sensor fusion for indoor localization and tracking, (iv) integration real-time data for traffic simulation in mobility systems, (v) mixing visual and point cloud informations for change detection on railways safety and security application. Through these examples, given suggestions can be applied to create geospatial applications even in different areas. In the future, integration can be enhanced to build data-driven platforms as the basis for intelligent systems: a user-friendly interface that provides advanced analysis capabilities built on reliable and efficient algorithms

Whistland: An augmented reality crowd-mapping system for civil protection and emergency management

The prevention and correct management of natural disaster event sequences play a key role in saving human lives. The availability of embedded and mobile smart computing systems opens new roads for the management of land and infrastructures by civil protection operators. To date, research has explored the use of social networks for the management of disasters connected to meteorological/hydrogeological events or earthquakes, but without emphasis on the importance of an integrated system. The main feature of the Whistland system proposed in this paper is to make synergistic use of augmented reality (AR), crowd-mapping (CM), social networks, the Internet of Things (IoT) and wireless sensor networks (WSN) by exploiting technologies and frameworks of Web 2.0 and GIS 2.0 to make informed decisions about the chain of events. The Whistland system is composed of a geo-server, a mobile application with AR and an analytics dashboard. The geo-server acts as the hub of the sensor and social networks. The abstracted concept in this sense is the transformation of the user domain into “intelligent sensors” for the whole scope of crisis management. The social network integration is made through an efficient pointer-like mechanism that keeps the storage requirement low through a mobile application based on an augmented reality engine and provides qualitative information that sensors are unable to capture. Real-time analyses, geo-searches and the capability to examine event histories with an augmented reality engine all help the stakeholders to understand better the state of the resources under observation/monitoring. The system has been extensively tested in the programmed maintenance of river basins, where it is necessary to log maintenance activities in order to keep the riverbank clean: a significant use-case in many countries affected by hydro-geological instability

Robotic platform for deep change detection for rail safety and security

Felix is the first robot measuring switch dimension parameters and geometrical railway ones together with potentially dangerous situations. It increases the quality and the consistency of the measures and offers the chance to increase the safety of operators and ultimately of final users. This paper presents a novel approach mixing visual and point cloud information for effective change detection for railways safety and security application. Main contributions are on the proposed data platform and on the mix of point-based measurements (switch dimensions) and on surrounding change detection (dangerous trees or abnormal railway trawlers) based multi-view camera and linear laser, processed by a classification process. Results, coming from a real rail scenario using the Felix platform, show the feasibility of the approach and the fast surveying capabilities with strong implications on safety and security

Documentation & detection of colour changes of bas relieves using close range photogrammetry

The digitization of complex buildings, findings or bas relieves can strongly facilitate the work of archaeologists, mainly for in depth analysis tasks. Notwithstanding, whether new visualization techniques ease the study phase, a classical naked-eye approach for determining changes or surface alteration could bring towards several drawbacks. The research work described in these pages is aimed at providing experts with a workflow for the evaluation of alterations (e.g. color decay or surface alterations), allowing a more rapid and objective monitoring of monuments. More in deep, a pipeline of work has been tested in order to evaluate the color variation between surfaces acquired at different ´epoques. The introduction of reliable tools of change detection in the archaeological domain is needful; in fact, the most widespread practice, among archaeologists and practitioners, is to perform a traditional monitoring of surfaces that is made of three main steps: production of a hand-made map based on a subjective analysis, selection of a sub-set of regions of interest, removal of small portion of surface for in depth analysis conducted in laboratory. To overcome this risky and time consuming process, digital automatic change detection procedure represents a turning point. To do so, automatic classification has been carried out according to two approaches: a pixel-based and an object-based method. Pixel-based classification aims to identify the classes by means of the spectral information provided by each pixel belonging to the original bands. The object-based approach operates on sets of pixels (objects/regions) grouped together by means of an image segmentation technique. The methodology was tested by studying the bas-relieves of a temple located in Peru, named Huaca de la Luna. Despite the data sources were collected with unplanned surveys, the workflow proved to be a valuable solution useful to understand which are the main changes over time