Descripteur
Documents disponibles dans cette catégorie (2536)
![](./images/expand_all.gif)
![](./images/collapse_all.gif)
Etendre la recherche sur niveau(x) vers le bas
Genetic algorithms for the calibration of cellular automata urban growth modeling / J. Shan in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 10 (October 2008)
![]()
[article]
Titre : Genetic algorithms for the calibration of cellular automata urban growth modeling Type de document : Article/Communication Auteurs : J. Shan, Auteur ; S. Alkheder, Auteur ; Jing Wang, Auteur Année de publication : 2008 Article en page(s) : pp 1267 - 1277 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] automate cellulaire
[Termes IGN] classification par algorithme génétique
[Termes IGN] croissance urbaineRésumé : (Auteur) This paper discusses the use of genetic algorithms to enhance the efficiency of transition rule calibration in cellular automata urban growth modeling. The cellular automata model is designed as a function of multitemporal satellite imagery and population density. Transition rules in the model identify the required neighborhood urbanization level for a test pixel to develop to urban. Calibration of the model is initially performed by exhaustive search, where the entire solution space is examined to find the best set of rule values. This method is computationally extensive and needs to consider all possible combinations for the transition rules. The rise in the number of variables will exponentially increase the time required for running and calibrating the model. This study introduces genetic algorithms as an effective solution to the calibration problem. It is shown that the genetic algorithms are able to produce modeling results close to the ones obtained from the exhaustive search in a time effective manner. Optimal rule values can be reached within the early generations of genetic algorithms. It is expected that genetic algorithms will significantly benefit urban modeling problems with larger set of input data and bigger solution spaces. Copyright ASPRS Numéro de notice : A2008-376 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.74.10.1267 En ligne : https://doi.org/10.14358/PERS.74.10.1267 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29369
in Photogrammetric Engineering & Remote Sensing, PERS > vol 74 n° 10 (October 2008) . - pp 1267 - 1277[article]Knowledge discovery from area-class resource maps: capturing prototype effects / F. Qi in Cartography and Geographic Information Science, vol 35 n° 4 (October 2008)
![]()
[article]
Titre : Knowledge discovery from area-class resource maps: capturing prototype effects Type de document : Article/Communication Auteurs : F. Qi, Auteur ; A - Xing Zhu, Auteur ; Tao Pei, Auteur ; et al., Auteur Année de publication : 2008 Article en page(s) : pp 223 - 237 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] classification à base de connaissances
[Termes IGN] exploration de données
[Termes IGN] extraction de données
[Termes IGN] objet géographique
[Termes IGN] outil de découverte de connaissancesRésumé : (Auteur) This paper presents a knowledge discovery approach to extracting knowledge from area-class resource maps. Prototype theory forms the basis of the approach which consists of two major components: (1) a scheme for organizing knowledge used in categorizing geographic entities which allows for the modeling of indeterminate boundaries and non-uniform memberships within categories; and (2) a data mining method using the Expectation Maximization (EM) algorithm for extracting such knowledge from area-class maps. A case study on knowledge discovery from a soil map demonstrates the details of the approach. The study shows that knowledge for classifying geographic entities with indeterminate boundaries is embedded in area-class maps and can be extracted through data mining; and that continuous spatial variation of geographic entities can be better modeled if the knowledge discovery process retains knowledge of within-class variations as well as transitions between classes. Copyright CaGISociety Numéro de notice : A2008-437 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1559/152304008786140533 En ligne : https://doi.org/10.1559/152304008786140533 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29506
in Cartography and Geographic Information Science > vol 35 n° 4 (October 2008) . - pp 223 - 237[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 032-08041 RAB Revue Centre de documentation En réserve L003 Disponible Neuro-fuzzy based analysis of hyperspectral imagery / F. Qiu in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 10 (October 2008)
![]()
[article]
Titre : Neuro-fuzzy based analysis of hyperspectral imagery Type de document : Article/Communication Auteurs : F. Qiu, Auteur Année de publication : 2008 Article en page(s) : pp 1235 - 1247 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Chine
[Termes IGN] classification floue
[Termes IGN] classification hybride
[Termes IGN] classification par réseau neuronal
[Termes IGN] découverte de connaissances
[Termes IGN] image EO1-Hyperion
[Termes IGN] image hyperspectraleRésumé : (Auteur) A neuro-fuzzy system, namely Gaussian Fuzzy Learning Vector Quantization (GFLVQ), was developed based on the synergy of a neural network and a fuzzy system. GFLVQ is both a fuzzy neural network and a neural fuzzy system with supervised learning and unsupervised self-organizing capabilities. In this paper, GFLVQ was further improved to efficiently and effectively process hyperspectral data through training data informed initialization and a simplified fuzzy learning algorithm. A geovisualization tool was developed to facilitate knowledge discovery and understanding of the hyperspectral image. A case study was conducted using a Hyperion image. The results obtained from the improved neuro-fuzzy system were found to be significantly better than those from conventional statistics-based and endmember-based classifiers. The fuzzy spectral profiles produced from the geovisualization tool provided an extra insight into the neuro-fuzzy learning process, further opening up the black box of the neural network. Copyright ASPRS Numéro de notice : A2008-375 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.74.10.1235 En ligne : https://doi.org/10.14358/PERS.74.10.1235 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29368
in Photogrammetric Engineering & Remote Sensing, PERS > vol 74 n° 10 (October 2008) . - pp 1235 - 1247[article]Simulating complex adaptative geographic systems: a geographically aware intelligent agent approach / W. Tang in Cartography and Geographic Information Science, vol 35 n° 4 (October 2008)
![]()
[article]
Titre : Simulating complex adaptative geographic systems: a geographically aware intelligent agent approach Type de document : Article/Communication Auteurs : W. Tang, Auteur Année de publication : 2008 Article en page(s) : pp 239 - 263 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] agent (intelligence artificielle)
[Termes IGN] apprentissage automatique
[Termes IGN] classe d'objets
[Termes IGN] classification à base de connaissances
[Termes IGN] conception orientée objet
[Termes IGN] modèle de simulation
[Termes IGN] système d'information géographique
[Termes IGN] système multi-agentsRésumé : (Auteur) The objective of this paper is to present a spatially explicit agent-based simulation framework with a supporting software package to explore complex adaptive geographic systems. This framework is particularly suitable for modeling entities that are contextually aware, knowledge driven, and adaptive because it represents them as geographically aware intelligent agents. Fundamental advances in the explicit representation of contextual information, knowledge structures, and learning processes are needed for modeling intelligent agents situated within geographic systems. The representation of these agents requires the integration of agent-based models, machine learning, and GIS. Existing software packages for agent-based modeling, however, often provide insufficient support for this integration. The agent-based simulation package presented here is specifically designed to achieve such integration by assisting the development of agent-based models from the simulation framework. Object-oriented modeling techniques were used to implement this simulation package, which includes four modules: simulation, visualization, learning, and geoprocessing. In particular, the learning and geoprocessing modules facilitate the representation of adaptive behavior in agents within spatially explicit environments. The utility of the agent-based simulation package is illustrated using two simulation models: one of adaptive elk behavior and another of pedestrian movement. The successful design of the simulation models suggests that the modeling framework with the supporting software package is well suited to the resolution of complex adaptive geographic problems. Copyright CaGISociety Numéro de notice : A2008-438 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1559/152304008786140551 En ligne : https://doi.org/10.1559/152304008786140551 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29507
in Cartography and Geographic Information Science > vol 35 n° 4 (October 2008) . - pp 239 - 263[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 032-08041 RAB Revue Centre de documentation En réserve L003 Disponible Subpixel urban land cover estimation: comparing cubist, random forests, and support vector regression / J. Walton in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 10 (October 2008)
![]()
[article]
Titre : Subpixel urban land cover estimation: comparing cubist, random forests, and support vector regression Type de document : Article/Communication Auteurs : J. Walton, Auteur Année de publication : 2008 Article en page(s) : pp 1213 - 1222 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] image Landsat-ETM+
[Termes IGN] milieu urbain
[Termes IGN] occupation du sol
[Termes IGN] régression
[Termes IGN] séparateur à vaste marge
[Termes IGN] surface imperméableRésumé : (Auteur) Three machine learning subpixel estimation methods (Cubist, Random Forests, and support vector regression) were applied to estimate urban cover. Urban forest canopy cover and impervious surface cover were estimated from Landsat-7 ETM+ imagery using a higher resolution cover map resampled to 30 m as training and reference data. Three different band combinations (reflectance, tasseled cap, and both reflectance and tasseled cap plus thermal) were compared for their effectiveness with each of the methods. Thirty different training site number and size combinations were also tested. Support vector regression on the tasseled cap bands was found to be the best estimator for urban forest canopy cover, while Cubist performed best using the reflectance plus tasseled cap band combination when predicting impervious surface cover. More training data partitioned in many small training sites generally produces better estimation results. Copyright ASPRS Numéro de notice : A2008-374 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.74.10.1213 En ligne : https://doi.org/10.14358/PERS.74.10.1213 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29367
in Photogrammetric Engineering & Remote Sensing, PERS > vol 74 n° 10 (October 2008) . - pp 1213 - 1222[article]Efficient implementation techniques for topological predicates on complex spatial objects / R. Praing in Geoinformatica, vol 12 n° 3 (September - November 2008)
PermalinkGeneralization-oriented road line classification by means of an artificial neural network / J.L. Garcia Balboa in Geoinformatica, vol 12 n° 3 (September - November 2008)
PermalinkModélisation du ruissellement érosif par automate cellulaire / D. Gaillard in Revue internationale de géomatique, vol 18 n° 3 (septembre - novembre 2008)
PermalinkDes roselières et des hommes / R. Mathevet in Revue internationale de géomatique, vol 18 n° 3 (septembre - novembre 2008)
PermalinkToward self-generalizing objects and On-the-Fly map generalization / M. Sabo in Cartographica, vol 43 n° 3 (September 2008)
PermalinkEarthquake-induced landslide hazard monitoring and assessment using SOM and PROMETHEE techniques: a case study at the Chiufenershan area in Central Taiwan / W.T. Lin in International journal of geographical information science IJGIS, vol 22 n° 8-9 (august 2008)
PermalinkImage-based quality assessment of road databases / Markus Gerke in International journal of geographical information science IJGIS, vol 22 n° 8-9 (august 2008)
PermalinkProducing geo-historical context from implicit sources: a geovisual analytics approach / B. Tomaszewski in Cartographic journal (the), vol 45 n° 3 (August 2008)
PermalinkThe time wave: a new method of visual exploration of geo-data in timespace / X. Li in Cartographic journal (the), vol 45 n° 3 (August 2008)
PermalinkUsing neural networks and cellular automata for modelling intra-urban land-use dynamics / C.M. Almeida in International journal of geographical information science IJGIS, vol 22 n° 8-9 (august 2008)
PermalinkA framework of region-based spatial relations for non-overlapping features and its application in object based image analysis / Y. Liu in ISPRS Journal of photogrammetry and remote sensing, vol 63 n° 4 (July - August 2008)
PermalinkUn algorithme génétique pour le transport à la demande en convergence : application au territoire de la communauté d'agglomération du Pays de Montbéliard / R. Chevrier in Revue internationale de géomatique, vol 18 n° 2 (juin - aout 2008)
PermalinkRegionalization with dynamically constrained agglomerative clustering and partitioning (REDCAP) / D. Guo in International journal of geographical information science IJGIS, vol 22 n° 6-7 (june 2008)
PermalinkE-11 - Extraction et gestion des connaissances EGC'2008 (2 volumes) (Bulletin de Revue des Nouvelles Technologies de l'Information, E-11 [01/04/2008]) / Fabrice Guillet
PermalinkReducing uninteresting spatial association rules in geographic databases using background knowledge: a summary of results / Vania Bogorny in International journal of geographical information science IJGIS, vol 22 n° 4-5 (april 2008)
PermalinkWeb cellular automata: forest fire modeling approach and prototype tool / S. Yassemi in Cartography and Geographic Information Science, vol 35 n° 2 (April 2008)
PermalinkAide à la décision pour la conception de systèmes complexes: une approche SMA / M. Augeraud in Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI, vol 13 n° 2 (mars - avril 2008)
PermalinkEstimation automatique de l'orientation relative : une approche directe basée sur la résolution de systèmes polynomiaux multivariables / Mahzad Kalantari in Revue Française de Photogrammétrie et de Télédétection, n° 189 (Mars 2008)
PermalinkEstimation automatique de l'orientation relative en imagerie terrestre / Mahzad Kalantari in XYZ, n° 114 (mars - mai 2008)
PermalinkLand-cover classification using ASTER: multi-band combinations based on wavelet fusion and SOM neural network / H. Bagan in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 3 (March 2008)
Permalink