1,720,971 research outputs found
A reference data access service in support of emergency management. Data quality assessment protocol, publication and exploitation of the results
Full text linkIn the field of natural disasters recovery and reduction and of emergency management geo-referenced information is strongly needed. In my personal experience obtained in the three years period spent at ITHACA, during the shorter at GFDRR Labs and through the work done indirectly with UN-WFP, after a natural disaster occurs, the experts in geomatics are often asked to provide answers to questions such as: where did it occur? How many people have been involved? How many infrastructures have been damaged and to what extent? How much is the economical loss? Geomatics can give answer to all these questions or give significant help in addressing operations in order to get the answers. The goal can be reached both with the use of base reference data, the ones usually contained in the classic cartography, and by exploiting value added information coming from satellite and aerial data processing, classic surveys and GPS/GNSS acquisition on the field. The activities object of this thesis have been performed in the framework of a European project that aim to provide services for Earth Observation: it is called Global Monitoring for Environment and Security. The document is organized in order to follow the project logical line rather than covering the respective timelin
Call for tenders No ENTR/2009/27 Lot 2 - Implementation of an initial GMES service for geospatial reference data access covering areas outside Europe D11.1 - Task 11 Data quality analysis protocol (M30)
No full textThe purpose of the present document is to provide a report on the activities performed in the framework of the project "Reference Data Access (RDA) covering areas outside Europe". The report is focused on the Task 11, "Analysis of non-European reference data quality and consistency" and the main outcomes related to the definition of indicators for quality, the relevant methodology and protocol to apply these to data sets and the analysis of these indicators versus the user requirements will be thoroughly described. The present report is the Deliverable D11.1, according to the Annex I of the Service Contract SI2.54784
A public platform for geospatial data sharing for disaster risk management
No full textSeveral studies have been conducted in Africa to assist local governments in addressing the risk situation related to natural hazards. Geospatial data containing information on vulnerability, impacts, climate change, disaster risk reduction is usually part of the output of such studies and is valuable to national and international organizations to reduce the risks and mitigate the impacts of disasters. Nevertheless this data isn't efficiently widely distributed and often resides in remote storage solutions hardly reachable. Spatial Data Infrastructures are technical solutions capable to solve this issue, by storing geospatial data and making them widely available through the internet. Among these solutions, GeoNode, an open source online platform for geospatial data sharing, has been developed in recent years. GeoNode is a platform for the management and publication of geospatial data. It brings together mature and stable open-source software projects under a consistent and easy-to-use interface allowing users, with little training, to quickly and easily share data and create interactive maps. GeoNode data management tools allow for integrated creation of data, metadata, and map visualizations. Each dataset in the system can be shared publicly or restricted to allow access to only specific users. Social features like user profiles and commenting and rating systems allow for the development of communities around each platform to facilitate the use, management, and quality control of the data the GeoNode instance contains (geonode.org). This paper presents a case study scenario of setting up a Web platform based on GeoNode. It is a public platform called MASDAP and promoted by the Government of Malawi in order to support development of the country and build resilience against natural disasters. A substantial amount of geospatial data has already been collected about hydrogeological risk, as well as several other-disasters related information. Moreover this platform will help to ensure that the data created by a number of past or ongoing projects is maintained and that this information remains accessible and useful. An Integrated Flood Risk Management Plan for a river basin has already been included in the platform and other data from future disaster risk management projects will be added as wel
Improving an Extreme Rainfall Detection System with GPM IMERG data
Full text linkMany studies have shown a growing trend in terms of frequency and severity of extreme events. As never before, having tools capable to monitor the amount of rain that reaches the Earth’s surface has become a key point for the identification of areas potentially affected by floods. In order to guarantee an almost global spatial coverage, NASA Global Precipitation Measurement (GPM) IMERG products proved to be the most appropriate source of information for precipitation retrievement by satellite. This study is aimed at defining the IMERG accuracy in representing extreme rainfall events for varying time aggregation intervals. This is performed by comparing the IMERG data with the rain gauge ones. The outcomes demonstrate that precipitation satellite data guarantee good results when the rainfall aggregation interval is equal to or greater than 12 h. More specifically, a 24-h aggregation interval ensures a probability of detection (defined as the number of hits divided by the total number of observed events) greater than 80%. The outcomes of this analysis supported the development of the updated version of the ITHACA Extreme Rainfall Detection System (ERDS: erds.ithacaweb.org). This system is now able to provide near real-time alerts about extreme rainfall events using a threshold methodology based on the mean annual precipitation
ERDS: un sistema open source per il monitoraggio di eventi di pioggia intensa
Full text linkGli eventi di pioggia intensa sono universalmente riconosciuti come la causa scatenante di molti dei più catastrofici disastri naturali. Negli ultimi decenni, numerosi gruppi di ricerca hanno cercato di sfruttare le potenzialità di alcuni open data resi disponibili in tempo reale per sviluppare sistemi di monitoraggio e allerta per piogge intense e/o eventi alluvionali. Al fine di poter identificare in tempo reale le aree interessate da tali fenomeni, ITHACA ha sviluppato un sistema chiamato Extreme Rainfall Detection System (ERDS) che, utilizzando dati open con copertura spaziale globale, fornisce, per specifici intervalli temporali, sia informazioni relative alle cumulate di pioggia sia allerte di pioggia intensa.
Due diversi approcci vengono utilizzati all’interno di tale progetto: il primo prevede l’utilizzo di dati acquisiti da satellite per fornire informazioni in tempo reale sulla quantità di pioggia precipitata mentre il secondo prevede l’utilizzo di un modello di previsione per stimare la pioggia che verrà registrata al suolo nei giorni a venire.
Nello specifico, il monitoraggio in tempo reale viene compiuto utilizzando una misura di precipitazione effettuata da satellite fornita della missione NASA/JAXA Global Precipitation Measurement (GPM). Il dato GPM IMERG early run data, disponibile 4 ore dopo l’acquisizione, garantisce al sistema una copertura globale caratterizzata da una risoluzione spaziale di 0.1° ed una risoluzione temporale di 30 minuti. Per quanto riguarda le previsioni di pioggia, il sistema utilizza gli output del modello Global Forecast System (GFS) prodotto dal National Centers for Environmental Prediction (NCEP). Tale dato fornisce una previsione di pioggia con risoluzione spaziale di 0.25°.
Entrambe le informazioni vengono cumulate su specifici intervalli di aggregazione (12, 24, 48, 72 e 96 ore) e vengono utilizzate per fornire allerte nei punti in cui la pioggia cumulata supera uno specifico valore di soglia. Tali soglie rappresentano un valore di precipitazione necessario a creare le condizioni scatenanti un’alluvione e sono state calcolate al fine di fornire, per ogni punto della superficie terrestre, allerte alla stessa risoluzione del dato di input. La calibrazione di tali soglie è stata effettuata seguendo un approccio empirico, analizzando eventi di pioggia che nel passato hanno portato a disastri di natura idrometeorologica. Le allerte così identificate possono essere utilizzate per l’identificazione e/o il pre-tasking di immagini satellitari da usare per una rapida valutazione delle aree più colpite.
Al fine di rendere operativo tale sistema, una serie di moduli è stata sviluppata ad hoc in Python 3 sfruttando le librerie numpy, h5py, GDAL, datetime, ftplib e urllib. L’intero codice è disponibile su GitHub (https://github.com/ITHACA-org/gpm-accumul e https://github.com/ITHACA-org/gfs-accumul).
Gli output prodotti da ERDS sono resi disponibili gratuitamente agli utenti in diversi formati attraverso un’applicazione WebGIS (erds.ithacaweb.org). Nello specifico, i dati vengono prodotti e resi scaricabili in formato Geotiff, garantendo quindi agli utilizzatori di poterli visualizzare in ambiente GIS e di utilizzarli per eseguire ulteriori analisi. Tali dati sono inoltre disponibili attraverso un Web Map Service (WMS) sfruttando GeoServer, rendendoli così consultabili anche da utenti non esperti. Lato client, invece, i raster vengono visualizzati utilizzando [email protected]
How distributed geodata solutions improve emergency management efficiency
No full textBeing prepared for natural and complex emergencies is a top priority for the UN World Food Programme (WFP). In order to efficiently provide adequate support, WFP has a strong local presence, with more than 80 Country Offices (CO) around the world. The WFP Emergency Preparedness team, in strict cooperation with leading academic institutions and technology experts, develops innovative early warning systems and rapid impact analysis tools and products. An emergency response phase requires an extremely well-organized communication between different actors, providing information timely and in an immediately understandable and not misleading format. WFP acquires, analyzes, distributes and displays data and information, gathered either on the field or retrieved from global monitoring systems. Data retrieved from global monitoring systems are managed centrally at WFP HQ, but need to be accessible to local offices. Similarly, data acquired on the field by local staff should be available at headquarters level for further and global analysis. This organizational model requires the set-up and maintenance of an effective solution for data managing and sharing: the adoption of a common data model further improve data sharing mechanisms, data interpretation and analysis. Additionally, Standard symbology rules and automated map templates helps in enforcing a brand perception and in increasing output quality, timeliness and readabilit
A low cost mobile mapping system (LCMMS) for field data acquisition: a potential use to validate aerial/satellite building damage assessment
No full textAmong the major natural disasters that occurred in 2010, the Haiti earthquake was a real turning point concerning the availability, dissemination and licensing of a huge quantity of geospatial data. In a few days several map products based on the analysis of remotely sensed data-sets were delivered to users. This demonstrated the need for reliable methods to validate the increasing variety of open source data and remote sensing-derived products for crisis management, with the aim to correctly spatially reference and interconnect these data with other global digital archives. As far as building damage assessment is concerned, the need for accurate field data to overcome the limitations of both vertical and oblique view satellite and aerial images was evident. To cope with the aforementioned need, a newly developed Low-Cost Mobile Mapping System (LCMMS) was deployed in Port-au-Prince (Haiti) and tested during a five-day survey in FebruaryMarch 2010. The system allows for acquisition of movies and single georeferenced frames by means of a transportable device easily installable (or adaptable) to every type of vehicle. It is composed of four webcams with a total field of view of about 180 degrees and one Global Positioning System (GPS) receiver, with the main aim to rapidly cover large areas for effective usage in emergency situations. The main technical features of the LCMMS, the operational use in the field (and related issues) and a potential approach to be adopted for the validation of satellite/aerial building damage assessments are thoroughly described in the articl
A low cost Mobile mapping System for field data acquisition to support emergency response
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Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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