Search results for "Spatial data"

showing 10 items of 30 documents

Du producteur à l'utilisateur: identification des trajectoires d'appropriation des données géographiques.

2009

To define, on a non technician face, the life cycle of geographic information, "from captor to decisions" we need, in a actor network theory perspective, to understand the process "from producer to user". In order to give an answer, we choose to study the spatial data appropriation process. This process opens the analysis of how data can be used by a group that has not produced the data itself, as well as in a multi-actor context. Distributed cognition theory offers a framework to understand data as a cognitive and collaborative artefact. Eight exploratory case studies help to identify typical appropriation trajectories, factors and socio-cognitive processes. This article offers a different…

distributed cognitioncognition distribuée[SHS.GEO] Humanities and Social Sciences/Geographydonnées géographiquesspatial datageomatic network[SHS.GEO]Humanities and Social Sciences/Geographyappropriationréseau géomatique[ SHS.GEO ] Humanities and Social Sciences/Geography
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Spatial Rules through Spatial Rule built-ins in SWRL

2010

International audience; The paper presents a method to include spatial rule within rule languages like SWRL to infer spatial rules within semantic web framework. The concept presented here could benefit both geospatial community as they benefit using the adjusted knowledge base to infer spatial rule and semantic web community as the inclusion of spatial data in its framework

[INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB][INFO.INFO-WB] Computer Science [cs]/Web[INFO.INFO-WB]Computer Science [cs]/Web[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM][ INFO.INFO-WB ] Computer Science [cs]/WebSpatial data[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]Knowledge ManagementInference Rules[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]Geospatial AnalysisJGRCS[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM]Semantic Web
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Semantic Issues About 3D Spatial Data Modelling Using CityGML

2015

International audience

[SHS.GEO] Humanities and Social Sciences/Geography[SHS.GEO]Humanities and Social Sciences/Geographyspatial data modellingComputingMilieux_MISCELLANEOUS[ SHS.GEO ] Humanities and Social Sciences/Geography
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Evaluation of deep learning algorithms for national scale landslide susceptibility mapping of Iran

2021

The identification of landslide-prone areas is an essential step in landslide hazard assessment and mitigation of landslide-related losses. In this study, we applied two novel deep learning algorithms, the recurrent neural network (RNN) and convolutional neural network (CNN), for national-scale landslide susceptibility mapping of Iran. We prepared a dataset comprising 4069 historical landslide locations and 11 conditioning factors (altitude, slope degree, profile curvature, distance to river, aspect, plan curvature, distance to road, distance to fault, rainfall, geology and land-sue) to construct a geospatial database and divided the data into the training and the testing dataset. We then d…

010504 meteorology & atmospheric sciencesReceiver operating characteristicbusiness.industryDeep learningSpatial databaselcsh:QE1-996.5Deep learningLandslideIranLandslide susceptibility010502 geochemistry & geophysicsRNN01 natural sciencesConvolutional neural networklcsh:GeologyLandslideRecurrent neural networkGeneral Earth and Planetary SciencesArtificial intelligenceScale (map)businessAlgorithmCNNGeology0105 earth and related environmental sciencesGeoscience Frontiers
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Agglomeration and dispersion of economic activities in and around Paris: An exploratory spatial data analysis

2010

The agglomeration patterns of twenty-six manufacturing and service sectors in and around Paris in 1999 are analysed. The method used measures the intensity of spatial agglomeration and identifies the location patterns of economic sectors. First the locational Gini coefficient and Moran’s I statistics of global spatial autocorrelation are computed. These provide different but complementary information about the spatial agglomeration of the sectors under study. Then exploratory spatial data analysis tools are applied. Moran scatterplots and local indicators of spatial association statistics reveal great diversity in location patterns across sectors.

Parismedia_common.quotation_subjectGeography Planning and Development0211 other engineering and technologies0507 social and economic geography02 engineering and technologySpatial dataEconometrics[ SHS.ECO ] Humanities and Social Sciences/Economies and financesStatistical dispersionEconomic geography[SHS.ECO] Humanities and Social Sciences/Economics and FinanceSpatial analysisComputingMilieux_MISCELLANEOUSGeneral Environmental Sciencemedia_commonGini coefficientEconomies of agglomerationEconomic sector05 social sciences021107 urban & regional planning[SHS.ECO]Humanities and Social Sciences/Economics and FinanceGeographyEconomics activitiesService (economics)050703 geography
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Spatial Econometrics and Spatial Data Pooled over Time: Towards an Adapted Modelling Approach

2013

International audience

spatial data[ SHS.ECO ] Humanities and Social Sciences/Economies and finances[SHS.ECO] Humanities and Social Sciences/Economics and FinanceSpatial econometrics[SHS.ECO]Humanities and Social Sciences/Economics and FinanceComputingMilieux_MISCELLANEOUS
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Toward a socio-cognitive approach of spatial data co-production

2010

The abilities of territorial communities to understand and control their development in a sustainable and equitable way, depend on territorial information sharing. In this context, the paper intends to understand and analyse the issues of spatial data co-production process. It provides understanding and operation elements so that spatial data sharing can progressively evolve into geomatics learning networks, also termed "communities of practice". This communities of practice offer, in our view, one of the most important component of Territorial Intelligence

[SHS.ANTHRO-SE] Humanities and Social Sciences/Social Anthropology and ethnologycommunity of practicecommunauté de pratiqueréseau apprenant.[SHS.ANTHRO-SE]Humanities and Social Sciences/Social Anthropology and ethnology[ SHS.HISPHILSO ] Humanities and Social Sciences/History Philosophy and Sociology of Sciences[SHS.HISPHILSO]Humanities and Social Sciences/History Philosophy and Sociology of Sciencesco-production[ SHS.ANTHRO-SE ] Humanities and Social Sciences/Social Anthropology and ethnology[SHS.HISPHILSO] Humanities and Social Sciences/History Philosophy and Sociology of Sciencesdonnée géographiquespatial dataintelligence territorialelearning networks.territorial intelligence
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Use of Geospatial Analyses for Semantic Reasoning

2010

International audience; This work focuses on the integration of the spatial analyses for semantic reasoning in order to compute new axioms of an existing OWL ontology. To make it concrete, we have defined Spatial Built-ins, an extension of existing Built-ins of the SWRL rule language. It permits to run deductive rules with the help of a translation rule engine. Thus, the Spatial SWRL rules are translated to standard SWRL rules. Once the spatial functions of the Spatial SWRL rules are computed with the help of a spatial database system, the resulting translated rules are computed with a reasoning engine such as Racer, Jess or Pellet.

Geospatial analysisComputer scienceGIS system02 engineering and technologycomputer.software_genreLNCS[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Spatial Knowledge Reasoning0202 electrical engineering electronic engineering information engineering[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]AxiomSWRLcomputer.programming_languageOWLInformation retrieval[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]Spatial databaseBuilt-ins020207 software engineeringWeb Ontology LanguageSemantic reasonerExtension (predicate logic)Spatial function[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]020201 artificial intelligence & image processingcomputerSpatial functions
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ArchaeoKM: Realizing Knowledge of the Archaeologists

2010

The potentiality of ontology within the faculty of archaeology has recently been felt. However, the use of ontology is limited either within the data interoperability for data sharing within various heterogeneous platforms or data integration of heterogeneous dataset. Thus the full potentiality of ontology is still to be realized within the community of archaeology. We are developing a system "ArchaeoKM" which uses ontology beyond data integration. It uses the strength of ontology to reason the knowledge presented within. Additionally, ArchaeoKM involves archaeologists to define their knowledge of an excavation site through domain rules which they define through the descriptions and observa…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]information system[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]spatial data[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]ontologyknowledge management[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI][INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Industrial archaeology
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On How to Build SDI Using Social Networking Principles in the Scope of Spatial Planning and Vocational Education

2011

Several ways how to build a spatial data infrastructure usable for spatial planning domain exist. It must be said that today the area of spatial planning is under the influence of the European INSPIRE directive. It is necessary to spread an awareness about how to build this infrastructure in terms of INSPIRE. The article describes the current ways how to build the spatial data infrastructure. Furthermore, a new approach - GeoPortal4everybody, based also on using of social networking principles is proposed. Next, the paper presents using of GeoPortal4everybody concept as a part of technological framework for vocational education partially developed in the SDI-EDU project. This project aims o…

MetadataEngineering managementSpatial data infrastructureKnowledge managementScope (project management)business.industryComputer scienceData managementVocational educationbusinessSpatial planning
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