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Spatial eigenvector filtering for spatiotemporal crime mapping and spatial crime analysis / Marco Helbich in Cartography and Geographic Information Science, Vol 42 n° 2 (April 2015)
[article]
Titre : Spatial eigenvector filtering for spatiotemporal crime mapping and spatial crime analysis Type de document : Article/Communication Auteurs : Marco Helbich, Auteur ; Jamal Jokar Arsanjani, Auteur Année de publication : 2015 Article en page(s) : pp 134 - 148 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse diachronique
[Termes IGN] carte thématique
[Termes IGN] données spatiotemporelles
[Termes IGN] filtrage statistique
[Termes IGN] Houston (Texas)
[Termes IGN] infraction
[Termes IGN] valeur propreRésumé : (auteur) Spatial and spatiotemporal analyses are exceedingly relevant to determine criminogenic factors. The estimation of Poisson and negative binomial models (NBM) is complicated by spatial autocorrelation. Therefore, first, eigenvector spatial filtering (ESF) is introduced as a method for spatiotemporal mapping to uncover time-invariant crime patterns. Second, it is demonstrated how ESF is effectively used in criminology to invalidate model misspecification, i.e., residual spatial autocorrelation, using a nonviolent crime dataset for the metropolitan area of Houston, Texas, over the period 2005–2010. The results suggest that local and regional geography significantly contributes to the explanation of crime patterns. Furthermore, common space-time eigenvectors selected on an annual basis indicate striking spatiotemporal patterns persisting over time. The findings about the driving forces behind Houston’s crime show that linear and nonlinear, spatially filtered, NBMs successfully absorb latent autocorrelation and, therefore, prevent parameter estimation bias. The consideration of a spatial filter also increases the explanatory power of the regressions. It is concluded that ESF can be highly recommended for the integration in spatial and spatiotemporal modeling toolboxes of law enforcement agencies. Numéro de notice : A2015-238 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2014.893839 En ligne : https://doi.org/10.1080/15230406.2014.893839 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76495
in Cartography and Geographic Information Science > Vol 42 n° 2 (April 2015) . - pp 134 - 148[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 032-2015021 RAB Revue Centre de documentation En réserve L003 Disponible Characterization of neighborhood sensitivity of an irregular cellular automata model of urban growth / Khila R. Dahal in International journal of geographical information science IJGIS, vol 29 n° 3 (March 2015)
[article]
Titre : Characterization of neighborhood sensitivity of an irregular cellular automata model of urban growth Type de document : Article/Communication Auteurs : Khila R. Dahal, Auteur ; T. Edwin Chow, Auteur Année de publication : 2015 Article en page(s) : pp 475 - 497 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] analyse de sensibilité
[Termes IGN] automate cellulaire
[Termes IGN] centroïde
[Termes IGN] croissance urbaine
[Termes IGN] dynamique spatiale
[Termes IGN] milieu urbain
[Termes IGN] parcelle cadastrale
[Termes IGN] simulation
[Termes IGN] système d'information géographique
[Termes IGN] Texas (Etats-Unis)
[Termes IGN] utilisation du sol
[Termes IGN] voisinage (relation topologique)
[Termes IGN] zone tamponRésumé : (Auteur) The neighborhood definition, which determines the influence on a cell from its nearby cells within a localized region, plays a critical role in the performance of a cellular automaton (CA) model. Raster CA models use a cellular grid to represent geographic space, and are sensitive to the cell size and neighborhood configuration. However, the sensitivity of vector-based CAs, an alternative to the raster-based counterpart, to neighborhood type and size remains uninvestigated. The present article reports the results of a detailed sensitivity analysis of an irregular CA model of urban land use dynamics. The model uses parcel data at the cadastral scale to represent geographic space, and was implemented to simulate urban growth in Central Texas, USA. Thirty neighborhood configurations defined by types and sizes were considered in order to examine the variability in the model outcome. Results from accuracy assessments and landscape metrics confirmed the model’s sensitivity to neighborhood configurations. Furthermore, the centroid intercepted neighborhood with a buffer of 120 m produced the most accurate simulation result. This neighborhood produced scattered development while the centroid extent-wide neighborhood resulted in a clustered development predominantly near the city center. Numéro de notice : A2015-585 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2014.987779 En ligne : https://doi.org/10.1080/13658816.2014.987779 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77872
in International journal of geographical information science IJGIS > vol 29 n° 3 (March 2015) . - pp 475 - 497[article]An entropy-based multispectral image classification algorithm / Di Long in IEEE Transactions on geoscience and remote sensing, vol 51 n° 12 (December 2013)
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Titre : An entropy-based multispectral image classification algorithm Type de document : Article/Communication Auteurs : Di Long, Auteur ; Vijay P. Singh, Auteur Année de publication : 2013 Article en page(s) : pp 5225 - 5238 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] carte d'occupation du sol
[Termes IGN] classificateur
[Termes IGN] entropie maximale
[Termes IGN] Houston (Texas)
[Termes IGN] image Landsat-ETM+Résumé : (Auteur) Employing the entropy theory, this paper presents a new and robust multispectral image classification algorithm. The digital number (DN) in remotely sensed multispectral images is considered as a random variable when judging the allocation of unknown pixels into predefined training classes. If an unknown pixel shows a similar DN vector as the pixels in a training class, it will increase the global entropy defined as the sum of DN probabilities multiplied by the logarithm of DN probabilities for all pixels within the training class. The unknown pixel is to be assigned to the class for which the entropy of the training class is increased most due to the inclusion of the pixel. The proposed entropy-based classification (EC) is compared with the maximum likelihood classification (MLC), parallelepiped classification, minimum distance classification, Mahalanobis distance classification (MDC), iterative self-organizing data analysis technique (ISODATA) classification, and K-means classification. These classifiers were applied to a Landsat Enhanced Thematic Mapper Plus image covering Houston, Texas, USA, acquired on October 16, 1999. A reference land cover map from the National Land Cover Data 2001 of the same area was taken as a ground reference to assess the accuracy of classification results, suggesting that the EC showed comparable overall accuracy as MDC, and they both outperformed other classifiers. The results of MLC can be improved by substituting the multivariate lognormal or gamma distribution for the multivariate normal distribution involved in its assumption. The EC algorithm has the potential to produce reliable land cover maps regardless of the distribution of DN vectors and relevant parameters of probability density functions involved in other classifiers. Numéro de notice : A2013-694 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2272560 En ligne : https://doi.org/10.1109/TGRS.2013.2272560 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32830
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 12 (December 2013) . - pp 5225 - 5238[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2013121 RAB Revue Centre de documentation En réserve L003 Disponible Developing an object-based hyperspatial image classifier with a case study using WorldView-2 data / Harini Sridharan in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 11 (November 2013)
[article]
Titre : Developing an object-based hyperspatial image classifier with a case study using WorldView-2 data Type de document : Article/Communication Auteurs : Harini Sridharan, Auteur ; Fang Qiu, Auteur Année de publication : 2013 Article en page(s) : pp 1027 - 1036 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement de formes
[Termes IGN] classification floue
[Termes IGN] Dallas (Texas)
[Termes IGN] image Worldview
[Termes IGN] milieu urbainRésumé : (Auteur) Recent advancements in remote sensing technology have provided a plethora of very high spatial resolution images. From pixel-based processing designed for low spatial resolution data, image processing has shifted towards object-based analysis in order to adapt to the hyperspatial nature of currently available remote sensing data. However, standard object-based classifiers work with only object-level summary statistics of the reflectance values and do not sufficiently exploit within-object reflectance pattern. In this research, a novel approach of utilizing the object-level distribution of reflectance values is presented. A fuzzy Kolmogorov-Smirnov based classifier is proposed to provide an object-to-object matching of the empirical distribution of the reflectance values of each object and derive a fuzzy membership grade to each class. This object-based classifier is tested for urban objects recognition from WorldView-2 data. Results indicate at least 10 percent increase in overall classification accuracy using the proposed classifier in comparison to various popular object- and pixel-based classifiers. Numéro de notice : A2013-597 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.79.11.1027 En ligne : https://doi.org/10.14358/PERS.79.11.1027 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32733
in Photogrammetric Engineering & Remote Sensing, PERS > vol 79 n° 11 (November 2013) . - pp 1027 - 1036[article]The electronically steerable flash Lidar : A full waveform scanning system for topographic and ecosystem structure applications / H. Duong in IEEE Transactions on geoscience and remote sensing, vol 50 n° 11 Tome 2 (November 2012)
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Titre : The electronically steerable flash Lidar : A full waveform scanning system for topographic and ecosystem structure applications Type de document : Article/Communication Auteurs : H. Duong, Auteur Année de publication : 2012 Article en page(s) : pp 4809 - 4820 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Colorado (Etats-Unis)
[Termes IGN] couvert forestier
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt tempérée
[Termes IGN] forêt tropicale
[Termes IGN] forme d'onde pleine
[Termes IGN] hauteur de la végétation
[Termes IGN] Lidar
[Termes IGN] Texas (Etats-Unis)Résumé : (Auteur) The electronically steerable flash lidar (ESFL) is a waveform lidar sensor that incorporates two advances relevant to the design of future spaceborne lidar sensors. The first is a nonmechanical scanner that splits a single incoming beam into a variable number of output beams that can be aligned independently across track; the transmitted beam pattern can be changed up to 60 Hz. The second is a flash focal plane array (FFPA) capable of recording waveforms simultaneously from a 128 x 128 pixel grid with individual footprints spread over multiple pixels. In this paper, the incoming beam was used to illuminate eight 8.4-m footprints which were imaged simultaneously on 12 x 12 pixel subsets of the FFPA. The FFPA digitizes waveforms at a vertical resolution of 75 cm over 41 vertical bins to create waveforms of 30.75-m depth. Multiple waveforms obtained using range-gating were combined for these analyses. ESFL data were collected at Manitou Experimental Forest (MEF), located in the Pikes Peak National Forest, Colorado, USA and the Stephen F. Austin Experimental Forest (AEF), located in the Angelina Forest, Nacogdoches, TX. We evaluated the use of individual pixel-level and aggregated footprint-level waveforms and alternate approaches to define the extent of each footprint in the focal plane array. Using discrete return lidar data as a reference, we evaluated the ability of ESFL lidar to estimate canopy height and compared the two sensors' rates of penetration to the terrain surface. We found the footprint-level waveforms were better suited for use with existing waveform processing techniques, although techniques for processing at the pixel-level appear feasible. Relationships between height estimates from each lidar data set were most closely related when footprint-level ESFL waveforms were calculated after removing pixels that had less than 50% of the maximum energy within that footprint. Regressions between ESFL and reference lidar data estimates - f height explained 84% (AEF) and 85% (MEF) of variance; this study could not say definitively which method yielded the more accurate estimate of height. Numéro de notice : A2012-593 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2193588 Date de publication en ligne : 16/05/2012 En ligne : https://doi.org/10.1109/TGRS.2012.2193588 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32039
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 11 Tome 2 (November 2012) . - pp 4809 - 4820[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2012111B RAB Revue Centre de documentation En réserve L003 Disponible An automated system for image-to-vector georeferencing / Y. Li in Cartography and Geographic Information Science, vol 39 n° 4 (October 2012)PermalinkQuantifying urban land cover change between 2001 and 2006 in the Gulf of Mexico region / George Xian in Geocarto international, vol 27 n° 6 (October 2012)PermalinkPermalinkThe development of a web-based demographic data extraction tool for population monitoring / T. Chow in Transactions in GIS, vol 15 n° 4 (August 2011)PermalinkMapping an annual weed with colour-infared aerial photography and image analysis / James H. Everitt in Geocarto international, vol 25 n° 1 (February 2010)PermalinkObservations of urban and suburban environments with global satellite scatterometer data / Son V. Nghiem in ISPRS Journal of photogrammetry and remote sensing, vol 64 n° 4 (July - August 2009)PermalinkMorphology-based building detection from airborne Lidar data / X. Meng in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 4 (April 2009)PermalinkRaster-network regionalization for watershed data processing / T.L. Whiteaker in International journal of geographical information science IJGIS, vol 21 n° 3-4 (march - april 2007)PermalinkSpectral analysis of coastal vegetation and land cover using AISA+ hyperspectral data / R. Jensen in Geocarto international, vol 22 n° 1 (March - May 2007)PermalinkA uniform sky illumination model to enhance shading of terrain and urban areas / Patrick Kennelly in Cartography and Geographic Information Science, vol 33 n° 1 (January 2006)Permalink