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Spatially oriented convolutional neural network for spatial relation extraction from natural language texts / Qinjun Qiu in Transactions in GIS, vol 26 n° 2 (April 2022)  

Public [article]  inTransactions in GIS > vol 26 n° 2 (April 2022) . - pp 839 - 866 Titre : Spatially oriented convolutional neural network for spatial relation extraction from natural language texts Type de document : Article/Communication Auteurs : Qinjun Qiu, Auteur ; Zhong Xie, Auteur ; Kai Ma, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 839 - 866 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] appariement sémantique [Termes IGN] apprentissage dirigé [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] données d'entrainement (apprentissage automatique) [Termes IGN] exploration de données [Termes IGN] langage naturel (informatique) [Termes IGN] proximité sémantique [Termes IGN] relation spatiale [Termes IGN] relation topologique [Termes IGN] site wiki [Termes IGN] spatial metrics [Termes IGN] système à base de connaissances Résumé : (auteur) Spatial relation extraction (e.g., topological relations, directional relations, and distance relations) from natural language descriptions is a fundamental but challenging task in several practical applications. Current state-of-the-art methods rely on rule-based metrics, either those specifically developed for extracting spatial relations or those integrated in methods that combine multiple metrics. However, these methods all rely on developed rules and do not effectively capture the characteristics of natural language spatial relations because the descriptions may be heterogeneous and vague and may be context sparse. In this article, we present a spatially oriented piecewise convolutional neural network (SP-CNN) that is specifically designed with these linguistic issues in mind. Our method extends a general piecewise convolutional neural network with a set of improvements designed to tackle the task of spatial relation extraction. We also propose an automated workflow for generating training datasets by integrating new sentences with those in a knowledge base, based on string similarity and semantic similarity, and then transforming the sentences into training data. We exploit a spatially oriented channel that uses prior human knowledge to automatically match words and understand the linguistic clues to spatial relations, finally leading to an extraction decision. We present both the qualitative and quantitative performance of the proposed methodology using a large dataset collected from Wikipedia. The experimental results demonstrate that the SP-CNN, with its supervised machine learning, can significantly outperform current state-of-the-art methods on constructed datasets. Numéro de notice : A2022-365 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1111/tgis.12887 Date de publication en ligne : 27/12/2021 En ligne : https://doi.org/10.1111/tgis.12887 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100584 [article]

Urban slum detection using texture and spatial metrics derived from satellite imagery / Divyani Kohli in Journal of spatial science, vol 61 n° 2 (December 2016)  

Public [article]  inJournal of spatial science > vol 61 n° 2 (December 2016) . - pp 405 - 426 Titre : Urban slum detection using texture and spatial metrics derived from satellite imagery Type de document : Article/Communication Auteurs : Divyani Kohli, Auteur ; Robert Sliuzas, Auteur ; Alfred Stein, Auteur Année de publication : 2016 Article en page(s) : pp 405 - 426 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse d'image orientée objet [Termes IGN] détection du bâti [Termes IGN] image Quickbird [Termes IGN] Maharashtra (Inde ; état) [Termes IGN] ontologie [Termes IGN] spatial metrics [Termes IGN] texture d'image [Termes IGN] ville Résumé : (auteur) Slum detection from satellite imagery is challenging due to the variability in slum types and definitions. This research aimed at developing a method for slum detection based on the morphology of the built environment. The method consists of segmentation followed by hierarchical classification using object-oriented image analysis and integrating expert knowledge in the form of a local slum ontology. Results show that textural feature contrast derived from a grey-level co-occurrence matrix was useful for delineating segments of slum areas or parts thereof. Spatial metrics such as the size of segments and proportions of vegetation and built-up were used for slum detection. The percentage of agreement between the reference layer and slum classification was 60 percent. This is lower than the accuracy achieved for land cover classification (80.8 percent), due to large variations. We conclude that the method produces useful results and has potential for successful application in contexts with similar morphology. Numéro de notice : A2016--147 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/14498596.2016.1138247 Date de publication en ligne : 05/05/2016 En ligne : http://dx.doi.org/10.1080/14498596.2016.1138247 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86334 [article]

Stand volume models based on stable metrics as from multiple ALS acquisitions in Eucalyptus plantations / Eric Bastos Görgens in Annals of Forest Science, vol 72 n° 4 (June 2015)  

Public [article]  inAnnals of Forest Science > vol 72 n° 4 (June 2015) . - pp 489 - 498 Titre : Stand volume models based on stable metrics as from multiple ALS acquisitions in Eucalyptus plantations Type de document : Article/Communication Auteurs : Eric Bastos Görgens, Auteur ; Petteri Packalen, Auteur ; André Gracioso Peres da Silva, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 489 - 498 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] cubage de peuplement [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] données multisources [Termes IGN] Eucalyptus (genre) [Termes IGN] semis de points [Termes IGN] spatial metrics Résumé : (auteur) Key message : The selection of stable metrics can generate reliable models between different data sets. The height metrics provide the greatest stability, specifically the higher percentiles and the mode. Height metrics transfer more predictive power than density metrics. Context : In forestry, there is an increasing development of aerial laser scanning (ALS). The flight missions that permit to record ALS point clouds are not yet standardized. Therefore, there is a need to identify the metrics that permit to infer robust forest stand estimates from the different point cloud acquisitions. Aims : The aim of this study is to identify stable metrics derived from different ALS data sets to be used as independent variable in stand volume models. Methods : Three different ALS data sets were taken from the same Eucalyptus plantation on the same day, each differing from the others in terms of flight altitude, laser power, and pulse frequency rate. Two sets of best predictive models were obtained for each data set based on two approaches: a basic approach using noncollinear metrics and an exhaustive search, and a second approach that added a pairwise Kolmogorov-Smirnov test to select stable metrics. Results : Height metrics proved more stable, especially higher percentiles (>50 %) and the mode. Models developed with stable metrics had similar performance compared to the basic approach. Conclusion : Percentiles higher than 50 % and the mode proved stable for that 6-year-old Eucalyptus plantation with a very homogeneous vertical structure. Further research widening the scope in terms of age and heterogeneity of vertical profiles is needed. Numéro de notice : A2015-426 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1007/s13595-015-0457-x Date de publication en ligne : 28/01/2015 En ligne : https://doi.org/10.1007/s13595-015-0457-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77015 [article]

Modeling ambiguity in census microdata allocations to improve demographic small area estimates / Stefan Leyk in Transactions in GIS, vol 17 n° 3 (June 2013)  

Public [article]  inTransactions in GIS > vol 17 n° 3 (June 2013) . - pp 406 - 425 Titre : Modeling ambiguity in census microdata allocations to improve demographic small area estimates Type de document : Article/Communication Auteurs : Stefan Leyk, Auteur ; Barbara P. Buttenfield, Auteur ; Nicholas N. Nagle, Auteur Année de publication : 2013 Article en page(s) : pp 406 - 425 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] allocation [Termes IGN] données démographiques [Termes IGN] estimation statistique [Termes IGN] recensement démographique [Termes IGN] résolution d'ambiguïté [Termes IGN] spatial metrics Résumé : (Auteur) This article describes a methodology for allocating demographic microdata to small enumeration areas such as census tracts, in the presence of underlying ambiguities. Maximum Entropy methods impute population weights that are constrained to match a set of census tract-level summary statistics. Once allocated, the household characteristics are summarized to revise estimates of tract-level demographic summary statistics, and to derive measures of ambiguity. The revised summary statistics are compared with original tract summaries within a context of expected variation. Allocation ambiguity is quantified for each household as a function of the distribution of imputed sample weights over all census tracts, and by computed metrics of confusion and variety of allocation to any census tract. The process reported here allows differentiation of households with regard to inherent ambiguity in the allocation decision. Ambiguity assessment represents an important component that has been neglected in spatial allocation work to date but can be seen as important additional knowledge for demographers and users of small area estimates. For the majority of tested variables, the revised tract level summaries correlate highly with original tract summary statistics. In addition to assessments for individual households, it is also possible to compute average allocation ambiguity for individual tracts, and to associate this with demographic characteristics not utilized in the allocation process. Numéro de notice : A2013-291 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/j.1467-9671.2012.01366.x Date de publication en ligne : 07/01/2013 En ligne : https://doi.org/10.1111/j.1467-9671.2012.01366.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32429 [article]

Modelling house unit density from land cover metrics: a Midwestern US example / P. Hardin in Geocarto international, vol 23 n° 5 (October - November 2008)  

Public [article]  inGeocarto international > vol 23 n° 5 (October - November 2008) . - pp 393 - 411 Titre : Modelling house unit density from land cover metrics: a Midwestern US example Type de document : Article/Communication Auteurs : P. Hardin, Auteur ; M. Jackson, Auteur ; R. Jensen, Auteur Année de publication : 2008 Article en page(s) : pp 393 - 411 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse discriminante [Termes IGN] densité de population [Termes IGN] densité du bâti [Termes IGN] données socio-économiques [Termes IGN] estimation statistique [Termes IGN] image Landsat-ETM+ [Termes IGN] Indiana (Etats-Unis) [Termes IGN] régression multiple [Termes IGN] spatial metrics Résumé : (Auteur) Geographic applications frequently require the gathering and analysis of socioeconomic data. For many nations, these data are normally collected through a census. However, during the intercensal period (5-10 years), these data lose their currency and must be updated. The objective of this project was to estimate housing unit density from Landsat ETM+ imagery in the Terre Haute, IN, USA, region. Modelling was done for 1945 census blocks in the study area containing 30 972 housing units. Landtype, as represented by six cluster classes, was used as the primary surrogate for housing unit density. The percentage of each landtype within the census blocks was calculated. Other landscape metrics representing landtype patch dominance and diversity were also calculated on a per-block basis. Housing unit density within the census block was then modelled as a function of those percentages and metrics using discriminant analysis and multiple regression. The simple correlation between the observed and modelled housing unit density was 0.79. The mean residual error produced by the model was 0.37 housing units per hectare. Copyright Taylor & Francis Numéro de notice : A2008-465 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106040801950344 Date de publication en ligne : 05/09/2008 En ligne : https://doi.org/10.1080/10106040801950344 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29534 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-08051	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Algorithms for nearest neighbor search on moving object trajectories / E. Frentzos in Geoinformatica, vol 11 n° 2 (June - August 2007)  

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Data fusion of high-resolution satellite imagery and Lidar data for automatic building extraction / Gunho Sohn in ISPRS Journal of photogrammetry and remote sensing, vol 62 n° 1 (May 2007)  

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Spatial-temporal specific neighbourhood rules for cellular automata land-use modelling / Stan Geertman in International journal of geographical information science IJGIS, vol 21 n° 5 (may 2007)  

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Metric details of topological line-line relations / K.A. Nedas in International journal of geographical information science IJGIS, vol 21 n° 1-2 (january 2007)  

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Agent-based modelling of shifting cultivation field patterns, Vietnam / M.R. Jepsen in International journal of geographical information science IJGIS, vol 20 n° 9 (october 2006)  

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Complexity metrics to quantify semantic accuracy in segmented Landsat images / Alfred Stein in International Journal of Remote Sensing IJRS, vol 26 n° 14 (July 2005)  

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Calibrating a neural network-based urban change model for two metropolitan areas of the upper Midwest of the United States / B.C. Pijanowski in International journal of geographical information science IJGIS, vol 19 n° 2 (february 2005)  

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Spatio-temporal dynamics in California's central valley: empirical links to urban theory / C. Dietzel in International journal of geographical information science IJGIS, vol 19 n° 2 (february 2005)  

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