scholarly journals Measuring the Impact of Natural Hazards with Citizen Science: The Case of Flooded Area Estimation Using Twitter

2021 ◽  
Vol 13 (6) ◽  
pp. 1153
Author(s):  
Pierrick Bruneau ◽  
Etienne Brangbour ◽  
Stéphane Marchand-Maillet ◽  
Renaud Hostache ◽  
Marco Chini ◽  
...  
Keyword(s):  
Natural Hazards ◽  
Spatial Data ◽  
Spatial Information ◽  
Temporal Frequency ◽  
Geographic Information ◽  
Area Measurement ◽  
Remotely Sensed Data ◽  
Aggregation Techniques ◽  
Flooded Area ◽  
The Impact

Twitter has significant potential as a source of Volunteered Geographic Information (VGI), as its content is updated at high frequency, with high availability thanks to dedicated interfaces. However, the diversity of content types and the low average accuracy of geographic information attached to individual tweets remain obstacles in this context. The contributions in this paper relate to the general goal of extracting actionable information regarding the impact of natural hazards on a specific region from social platforms, such as Twitter. Specifically, our contributions describe the construction of a model classifying whether given spatio-temporal coordinates, materialized by raster cells in a remote sensing context, lie in a flooded area. For training, remotely sensed data are used as the target variable, and the input covariates are built on the sole basis of textual and spatial data extracted from a Twitter corpus. Our contributions enable the use of trained models for arbitrary new Twitter corpora collected for the same region, but at different times, allowing for the construction of a flooded area measurement proxy available at a higher temporal frequency. Experimental validation uses true data that were collected during Hurricane Harvey, which caused significant flooding in the Houston urban area between mid-August and mid-September 2017. Our experimental section compares several spatial information extraction methods, as well as various textual representation and aggregation techniques, which were applied to the collected Twitter data. The best configuration yields a F1 score of 0.425, boosted to 0.834 if restricted to the 10% most confident predictions.

scholarly journals INTEGRATION OF REMOTELY SENSED DATA INTO GEOSPATIAL REFERENCE INFORMATION DATABASES. UN-GGIM NATIONAL APPROACH

2016 ◽  
Vol XLI-B4 ◽  
pp. 721-725
Author(s):  
A. Arozarena ◽  
G. Villa ◽  
N. Valcárcel ◽  
B. Pérez
Keyword(s):  
Spatial Data ◽  
Spatial Information ◽  
Remotely Sensed ◽  
Geographic Information ◽  
Earth Observation ◽  
Institutional Arrangements ◽  
Observation System ◽  
Remotely Sensed Data ◽  
Geospatial Information ◽  
Reference Information

Remote sensing satellites, together with aerial and terrestrial platforms (mobile and fixed), produce nowadays huge amounts of data coming from a wide variety of sensors. These datasets serve as main data sources for the extraction of Geospatial Reference Information (GRI), constituting the “skeleton” of any Spatial Data Infrastructure (SDI). <br><br> Since very different situations can be found around the world in terms of geographic information production and management, the generation of global GRI datasets seems extremely challenging. Remotely sensed data, due to its wide availability nowadays, is able to provide fundamental sources for any production or management system present in different countries. After several automatic and semiautomatic processes including ancillary data, the extracted geospatial information is ready to become part of the GRI databases. <br><br> In order to optimize these data flows for the production of high quality geospatial information and to promote its use to address global challenges several initiatives at national, continental and global levels have been put in place, such as European INSPIRE initiative and Copernicus Programme, and global initiatives such as the Group on Earth Observation/Global Earth Observation System of Systems (GEO/GEOSS) and United Nations Global Geospatial Information Management (UN-GGIM). These workflows are established mainly by public organizations, with the adequate institutional arrangements at national, regional or global levels. Other initiatives, such as Volunteered Geographic Information (VGI), on the other hand may contribute to maintain the GRI databases updated. <br><br> Remotely sensed data hence becomes one of the main pillars underpinning the establishment of a global SDI, as those datasets will be used by public agencies or institutions as well as by volunteers to extract the required spatial information that in turn will feed the GRI databases. <br><br> This paper intends to provide an example of how institutional arrangements and cooperative production systems can be set up at any territorial level in order to exploit remotely sensed data in the most intensive manner, taking advantage of all its potential.

Geographic Information System and Big Spatial Data

2020 ◽  
Vol 16 (4) ◽  
pp. 101-145
Author(s):  
Raja Sher Afgun Usmani ◽  
Ibrahim Abaker Targio Hashem ◽  
Thulasyammal Ramiah Pillai ◽  
Anum Saeed ◽  
Akibu Mahmoud Abdullahi
Keyword(s):  
Information System ◽  
Big Data ◽  
Geographic Information System ◽  
Spatial Data ◽  
Spatial Information ◽  
Geographic Information ◽  
Data Sources ◽  
Spatial Datasets ◽  
Big Data Technologies ◽  
The Impact

Geographic information system (GIS) is designed to generate maps, manage spatial datasets, perform sophisticated “what if” spatial analyses, visualize multiple spatial datasets simultaneously, and solve location-based queries. The impact of big data is in every industry, including the GIS. The location-based big data also known as big spatial data has significant implications as it forces the industry to contemplate how to acquire and leverage spatial information. In this study, a comprehensive taxonomy is created to provide a better understanding of the uses of GIS and big spatial data. The taxonomy is made up of big data technologies, GIS data sources, tools, analytics, and applications. The authors look into the importance of big spatial data and its implications, review the data sources, and GIS analytics, applications, and GIS tools. Furthermore, in order to guide researchers interested in GIS, the challenges that require substantial research efforts are taken into account. Lastly, open issues in GIS that require further observation are summarized.

scholarly journals INTEGRATION OF REMOTELY SENSED DATA INTO GEOSPATIAL REFERENCE INFORMATION DATABASES. UN-GGIM NATIONAL APPROACH

2016 ◽  
Vol XLI-B4 ◽  
pp. 721-725
Author(s):  
A. Arozarena ◽  
G. Villa ◽  
N. Valcárcel ◽  
B. Pérez
Keyword(s):  
Spatial Data ◽  
Spatial Information ◽  
Remotely Sensed ◽  
Geographic Information ◽  
Earth Observation ◽  
Institutional Arrangements ◽  
Observation System ◽  
Remotely Sensed Data ◽  
Geospatial Information ◽  
Reference Information

Remote sensing satellites, together with aerial and terrestrial platforms (mobile and fixed), produce nowadays huge amounts of data coming from a wide variety of sensors. These datasets serve as main data sources for the extraction of Geospatial Reference Information (GRI), constituting the “skeleton” of any Spatial Data Infrastructure (SDI). &lt;br&gt;&lt;br&gt; Since very different situations can be found around the world in terms of geographic information production and management, the generation of global GRI datasets seems extremely challenging. Remotely sensed data, due to its wide availability nowadays, is able to provide fundamental sources for any production or management system present in different countries. After several automatic and semiautomatic processes including ancillary data, the extracted geospatial information is ready to become part of the GRI databases. &lt;br&gt;&lt;br&gt; In order to optimize these data flows for the production of high quality geospatial information and to promote its use to address global challenges several initiatives at national, continental and global levels have been put in place, such as European INSPIRE initiative and Copernicus Programme, and global initiatives such as the Group on Earth Observation/Global Earth Observation System of Systems (GEO/GEOSS) and United Nations Global Geospatial Information Management (UN-GGIM). These workflows are established mainly by public organizations, with the adequate institutional arrangements at national, regional or global levels. Other initiatives, such as Volunteered Geographic Information (VGI), on the other hand may contribute to maintain the GRI databases updated. &lt;br&gt;&lt;br&gt; Remotely sensed data hence becomes one of the main pillars underpinning the establishment of a global SDI, as those datasets will be used by public agencies or institutions as well as by volunteers to extract the required spatial information that in turn will feed the GRI databases. &lt;br&gt;&lt;br&gt; This paper intends to provide an example of how institutional arrangements and cooperative production systems can be set up at any territorial level in order to exploit remotely sensed data in the most intensive manner, taking advantage of all its potential.

scholarly journals SPATIAL DATA: FROM CARTOGRAPHY TO GEODATABASE

2017 ◽  
Vol 43 (4) ◽  
pp. 142-146 ◽  
Author(s):  
Ugo FALCHI
Keyword(s):  
Spatial Data ◽  
Common Good ◽  
Spatial Information ◽  
Geographic Information ◽  
The Public ◽  
Significant Acceleration ◽  
Management And Development ◽  
The Status ◽  
History Of ◽  
Essential Knowledge

The final goal of this paper was to fix a brief summary on the status of geographic information in Italy due to the technological steps and national regulations. The acquisition, processing and sharing of spatial data has experienced a significant acceleration thanks to the development of computer technology and the acknowledgment of the need for standardization and homogenization of information held by pub­lic authorities and individuals. The spatial data represents the essential knowledge in the management and development of a territory both in terms of planning for safety and environmental prevention. In Italy there is an enormous heritage of spatial information which is historically affected by a problem of consistency and uniformity, in order to make it often contradictory in its use by the public decision-maker and private par­ties. The recent history of geographic information is characterized by a significant effort aimed at optimiz­ing this decisive technical and cultural heritage allowing the use of it to all citizens in a logic of sharing and re-use and may finally represent a common good available to all.

scholarly journals Sistem Informasi Geografis Berbasis Web Digitasi Persil Bangunan

2015 ◽  
Vol 1 (1) ◽  
pp. 20-28
Author(s):  
Arief Susanto
Keyword(s):  
Information System ◽  
Spatial Data ◽  
Local Governments ◽  
Spatial Information ◽  
Geographic Information ◽  
Process Data ◽  
Desktop Application ◽  
Gis Data ◽  
Google Map Api ◽  
Advanced Development

Geographic Information Systems ( GIS abbreviated as Geographic Information System ) is a specialized information system that manages data having spatial information . Most to process data in the form of GIS data are still many who use desktop application or can only run on one computer while the more advanced development requires us to produce information more easily is to develop a GIS online ( via the Internet ) and can be accessed Anywhere You . This application is designed using DFD modeling and created using the programming language PHP with MySQL database as well as utilizing Google Map API . As well as to facilitate the collection of data by the field of local government development . Moreover , the existence of GIS aims to help local governments in the search for building plots parcels and ownership of data previously not been structured to be more structural and facilitate spatial data collection .

scholarly journals Przyszłość systemów rejestracji nieruchomości wobec rozwoju inteligentnych technologii. Wybrane problemy prawne na tle wniosków z konferencji „Common Vision Conference 2016. Migration to a Smart World”, Amsterdam, 5–7 czerwca 2016 roku

2017 ◽  
Vol 15 (2) ◽  
pp. 301-320
Author(s):  
Maria Kaczorowska
Keyword(s):  
Spatial Data ◽  
Data Exchange ◽  
Spatial Information ◽  
Smart Cities ◽  
Information Service ◽  
Advanced Technology ◽  
Technological Advancement ◽  
Land Registration ◽  
The Impact ◽  
Common Vision

The development of information technologies offers new possibilities of use of information collected in public registers, such as land registers and cadastres, which play a significant role in establishing the infrastructure for spatial information. Efficient use of spatial information systems with the purpose of a sustainable land management shall be based on en suring the interconnection of different information resources, data exchange, as well as a broad access to data. The role of land registration systems in the context of technological advancement was the subject of the Common Vision Conference 2016. Migration to a Smart World, held on 5–7 June 2016 in Amsterdam. The conference was organized by Europe’s five leading mapping, cadastre and land registry associations, cooperating within a “Common Vision” agreement: EuroGeographics, Permanent Committee on Cadastre, European Land Registries Association, European Land Information Service and Council of European Geodetic Surveyors. The discussion during the conference focused on topics regarding the idea of smart cities, marine cadastre, interoperability of spatial data, as well as the impact of land registers and cadastres on creating the infrastructure for spatial information and developing e-government, at both national and European levels. The paper aims to present an overview of issues covered by the conference and also to highlight some important problems arising from implementing advanced technology solutions in the field of land registration.

Different Roles and Definitions of Spatial Data Fusion

2012 ◽  
pp. 105-111 ◽  
Author(s):  
Patrik Skogster
Keyword(s):  
Data Fusion ◽  
Spatial Data ◽  
Spatial Information ◽  
Geographic Information ◽  
Modern Business ◽  
Computerized System

Geographic information is created by manipulating geographic (or spatial) data (generally known by the abbreviation geodata) in a computerized system. Geo-spatial information and geomatics are issues of modern business and research. It is essential to provide their different definitions and roles in order to get an overall picture of the issue. This article discusses about the problematic of definitions, but also the technologies and challenges within spatial data fusion.

scholarly journals Effective 3-D surface modeling for geographic information systems

2016 ◽  
Vol 16 (1) ◽  
pp. 123-133 ◽  
Author(s):  
K. Yüksek ◽  
M. Alparslan ◽  
E. Mendi
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Spatial Data ◽  
Spatial Information ◽  
Surface Modeling ◽  
Geographic Information ◽  
Main Memory ◽  
Replacement Policy ◽  
Multimedia Database ◽  
Image Size

Abstract. In this work, we propose a dynamic, flexible and interactive urban digital terrain platform with spatial data and query processing capabilities of geographic information systems, multimedia database functionality and graphical modeling infrastructure. A new data element, called Geo-Node, which stores image, spatial data and 3-D CAD objects is developed using an efficient data structure. The system effectively handles data transfer of Geo-Nodes between main memory and secondary storage with an optimized directional replacement policy (DRP) based buffer management scheme. Polyhedron structures are used in digital surface modeling and smoothing process is performed by interpolation. The experimental results show that our framework achieves high performance and works effectively with urban scenes independent from the amount of spatial data and image size. The proposed platform may contribute to the development of various applications such as Web GIS systems based on 3-D graphics standards (e.g., X3-D and VRML) and services which integrate multi-dimensional spatial information and satellite/aerial imagery.

scholarly journals Web-Based Geographic Information System Development of Hotspots Distribution for Monitoring Forest and Land Fires Using Leaflet JavaScript Library (Case Study: Ogan Komering Ilir Regency, South Sumatera)

2021 ◽  
Vol 936 (1) ◽  
pp. 012010
Author(s):  
Bangun Muljo Sukojo ◽  
Diya Rochima Lisakiyanto
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Infrared Imaging ◽  
Spatial Information ◽  
Detection System ◽  
System Development ◽  
Geographic Information ◽  
Burned Area ◽  
Web Based ◽  
The Impact

Abstract Forest and land fires are a disaster that occurs almost every year on Sumatra Island. Ogan Komering Ilir is one of the regencies in South Sumatra Province with a high number of hotspots causing forest and land fires every year. Prevention efforts are important to reduce the impact caused by forest and land fires on various aspects of life. One of them is by building a web-based Geographic Information System (WebGIS) for the distribution of hotspots as a form of early warning and detection system by utilizing VIIRS Nightfire (VNF) data from the remote sensing technology of the Suomi-NPP satellite which has Visible Infrared Imaging Radiometer Suite (VIIRS) active sensors which have been processed with the Nightfire algorithm. The Leaflet JavaScript library plays an important role in adding to the functionality of WebGIS with a wide selection of available plugins and easy-to-read source code to make web-based spatial information more interactive. The prototype of WebGIS with the name OKIApi has been successfully developed and has several key features such as displaying information on the distribution of hotspots that have been classified by temperature; the priority level of firefighting areas and the vulnerability level of flammable areas based on the type of land cover; route to the hotspot or the fire department locations; a chart of the estimated burned area from the source footprint of hotspot; and a chart of the number of hotspots per day that have been classified by temperature. The percentage value of the web feasibility for the functionality test to 13 WebGIS features is 100% with a very good predicate, the usability test is 91.5% with a very good predicate, and the portability test on 18 web browsers applications is 100% with a very good predicate.

THE NEXT GENERATION SPATIAL DATA WAREHOUSE

2002 ◽  
Vol 42 (1) ◽  
pp. 633
Author(s):  
A.J. Yardley
Keyword(s):  
Spatial Data ◽  
Spatial Information ◽  
Essential Element ◽  
Spatial Location ◽  
Geographic Information ◽  
Environmental Data ◽  
Next Generation ◽  
Data Types ◽  
Political Boundaries ◽  
Access To Data

Woodside Energy, based in Perth, Western Australia, has commenced the implementation of its next generation spatial data warehousing and visualisation system. The warehouse facilitates access to data in various corporate geoscience data sets, as well as up-to-date cultural and environmental data. It expands the capabilities of the existing geoscience database by providing a facility to handle spatial data at the database level rather than in files and maps. Spatial data can now be kept in the database, in its correct spatial location, and with a known provenance.Woodside’s worldwide exploration, development and production activities require the use of a wide variety of geographic data such as seismic, bathymetry, wells, permits, coastlines, political boundaries, navigation charts, remote sensing and geological interpretations.Geo-spatial data comes to Woodside in a variety of formats, datums and conditions. The Geomatics Department, through the Geoscience Database and Spatial Information Management teams, loads, maintains and manages all data considered to be corporate. It is quality controlled and placed into the warehouse, where it is readily accessible to technical and administrative staff.Location is an essential element in most Woodside decisions. Because of the new spatial capabilities, a number of geographic information processes are now possible. Additionally information can also be made available through the internet if required.Reliable geographic information will become more widely available in the organisation, and be more easily merged with traditional data types, enhancing the decision-making process.

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