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Regionalization of youth and adolescent weight metrics for the continental United States using contiguity-constrained clustering and partitioning / Samuel Adu-Prah in Cartographica, vol 50 n° 2 (Summer 2015)
[article]
Titre : Regionalization of youth and adolescent weight metrics for the continental United States using contiguity-constrained clustering and partitioning Type de document : Article/Communication Auteurs : Samuel Adu-Prah, Auteur ; T. Oyana, Auteur Année de publication : 2015 Article en page(s) : pp 61 - 70 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] analyse de groupement
[Termes IGN] carte sanitaire
[Termes IGN] partitionnement
[Termes IGN] régionalisation (segmentation)
[Termes IGN] santé
[Termes IGN] visualisation de donnéesRésumé : (auteur) Les techniques de collecte, les analyses et les présentations de données spatiales contemporaines ont offert de nouvelles possibilités pour les analyses de la santé publique, possibilités qui rendent parfois inappropriées les limites administratives et statistiques existantes. L'article présente un algorithme appliqué, celui de la régionalisation avec regroupement et partitionnement d'agglomérations à restrictions dynamiques (REDCAP), pour créer des régions autres que les régions prédéfinies. Les régions créées dans l'étude concernaient le poids des jeunes de la zone continentale des États-Unis. L'algorithme REDCAP intègre une restriction de contiguïté spatiale afin de créer des régions ayant les mêmes caractéristiques et la même valeur, surmontant ainsi l'obstacle existant en cartographie quant à l'utilisation courante de régions administratives et statistiques dans la présentation des résultats. L'étude a produit des régions de 10 à 25 catégories reflétant les valeurs basses et élevées de la prévalence de l'obésité chez les jeunes des États-Unis sans recourir aux limites des comtés ni aux frontières des États existantes. Les résultats offrent de nouvelles perspectives sur les régions formées de comtés ciblés comme ayant une prévalence forte de l'obésité, dont une partie n'avait pas été consignée dans des études antérieures. Cette méthode comporte un avantage considérable, puisqu'elle réduit au minimum le biais inhérent à l'utilisation des régions administratives et statistiques existantes, ce qui pose un défi en cartographie. En outre, cette méthode crée efficacement des régions fondées sur un thème précis et une fonction objective. Numéro de notice : A2015-271 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.3138/cart.50.2.2507 En ligne : http://www.utpjournals.press/doi/full/10.3138/cart.50.2.2507 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76384
in Cartographica > vol 50 n° 2 (Summer 2015) . - pp 61 - 70[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 031-2015021 RAB Revue Centre de documentation En réserve L003 Disponible Spectral–spatial classification for hyperspectral data using rotation forests with local feature extraction and markov random fields / Junshi Xia in IEEE Transactions on geoscience and remote sensing, vol 53 n° 5 (mai 2015)
[article]
Titre : Spectral–spatial classification for hyperspectral data using rotation forests with local feature extraction and markov random fields Type de document : Article/Communication Auteurs : Junshi Xia, Auteur ; Jocelyn Chanussot, Auteur ; Peijun Du, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 2532 - 2546 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] analyse en composantes principales
[Termes IGN] champ aléatoire de Markov
[Termes IGN] classification et arbre de régression
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image hyperspectrale
[Termes IGN] performance
[Termes IGN] Rotation Forest classificationRésumé : (Auteur) In this paper, we propose a new spectral-spatial classification strategy to enhance the classification performances obtained on hyperspectral images by integrating rotation forests and Markov random fields (MRFs). First, rotation forests are performed to obtain the class probabilities based on spectral information. Rotation forests create diverse base learners using feature extraction and subset features. The feature set is randomly divided into several disjoint subsets; then, feature extraction is performed separately on each subset, and a new set of linear extracted features is obtained. The base learner is trained with this set. An ensemble of classifiers is constructed by repeating these steps several times. The weak classifier of hyperspectral data, classification and regression tree (CART), is selected as the base classifier because it is unstable, fast, and sensitive to rotations of the axes. In this case, small changes in the training data of CART lead to a large change in the results, generating high diversity within the ensemble. Four feature extraction methods, including principal component analysis (PCA), neighborhood preserving embedding (NPE), linear local tangent space alignment (LLTSA), and linearity preserving projection (LPP), are used in rotation forests. Second, spatial contextual information, which is modeled by MRF prior, is used to refine the classification results obtained from the rotation forests by solving a maximum a posteriori problem using the α-expansion graph cuts optimization method. Experimental results, conducted on three hyperspectral data with different resolutions and different contexts, reveal that rotation forest ensembles are competitive with other strong supervised classification methods, such as support vector machines. Rotation forests with local feature extraction methods, including NPE, LLTSA, and LPP, can lead to higher classification accuracies than that achieved by PCA. With the help of MRF, the proposed algorithms can improve the classification accuracies significantly, confirming the importance of spatial contextual information in hyperspectral spectral-spatial classification. Numéro de notice : A2015-519 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2361618 En ligne : https://doi.org/10.1109/TGRS.2014.2361618 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77526
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 5 (mai 2015) . - pp 2532 - 2546[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015051 RAB Revue Centre de documentation En réserve L003 Disponible CAESAR: an approach based on covariance matrix decomposition to improve multibaseline–multitemporal interferometric SAR processing / Gianfranco Fornaro in IEEE Transactions on geoscience and remote sensing, vol 53 n° 4 (April 2015)
[article]
Titre : CAESAR: an approach based on covariance matrix decomposition to improve multibaseline–multitemporal interferometric SAR processing Type de document : Article/Communication Auteurs : Gianfranco Fornaro, Auteur ; Simona Verde, Auteur ; Diego Reale, Auteur ; Antonio Pauciullo, Auteur Année de publication : 2015 Article en page(s) : pp 2050 - 2065 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] analyse en composantes principales
[Termes IGN] décomposition d'image
[Termes IGN] image Cosmo-Skymed
[Termes IGN] image radar moirée
[Termes IGN] interferométrie différentielle
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] matrice de covariance
[Termes IGN] surveillance géologique
[Termes IGN] tomographie radarRésumé : (Auteur) Synthetic aperture radar (SAR) tomography has been strongly developed in the last years for the analysis at fine scale of data acquired by high-resolution interferometric SAR sensors as a technique alternative to classical persistent scatterer interferometry and able to resolve also multiple scatterers. SqueeSAR is a recently proposed solution which, in the context of SAR interferometry at the coarse scale analysis stage, allows taking advantage of the multilook operation to filter interferometric stacks by extracting, pixel by pixel, equivalent scattering mechanisms from the set of all available interferometric measurement collected in the data covariance matrix. In this paper, we investigate the possibilities to extend SqueeSAR by allowing the identification of multiple scattering mechanisms from the analysis of the covariance matrix. In particular, we present a new approach, named “Component extrAction and sElection SAR” algorithm, that allows taking advantage of the principal component analysis to filter interferograms relevant to the decorrelating scatterer, i.e., scatterers that may exhibit coherence losses depending on the spatial and temporal baseline distributions, and to detect and separate scattering mechanisms possibly interfering in the same pixel due to layover directly at the interferogram generation stage. The proposed module allows providing options useful for classical interferometric processing to monitor ground deformations at lower resolution (coarse scale), as well as for possibly aiding the data calibration preliminary for the subsequent full-resolution interferometric/tomographic (fine scale) analysis. Results achieved by processing high-resolution Cosmo-SkyMed data, characterized by the favorable features of a large baseline span, are presented to explain the advantages and validate this new interferometric processing solution. Numéro de notice : A2015-178 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2352853 Date de publication en ligne : 29/09/2014 En ligne : https://doi.org/10.1109/TGRS.2014.2352853 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75897
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 4 (April 2015) . - pp 2050 - 2065[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015041 RAB Revue Centre de documentation En réserve L003 Disponible Co-clustering geo-referenced time series: exploring spatio-temporal patterns in Dutch temperature data / Xiaojing Wu in International journal of geographical information science IJGIS, vol 29 n° 4 (April 2015)
[article]
Titre : Co-clustering geo-referenced time series: exploring spatio-temporal patterns in Dutch temperature data Type de document : Article/Communication Auteurs : Xiaojing Wu, Auteur ; Raul Zurita-Milla, Auteur ; Menno-Jan Kraak, Auteur Année de publication : 2015 Article en page(s) : pp 624 - 642 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] analyse spatio-temporelle
[Termes IGN] exploration de données géographiques
[Termes IGN] regroupement de données
[Termes IGN] série temporelle
[Termes IGN] température de l'air
[Termes IGN] visualisation de donnéesRésumé : (Auteur) Clustering allows considering groups of similar data elements at a higher level of abstraction. This facilitates the extraction of patterns and useful information from large amounts of spatio-temporal data. Till now, most studies have focused on the extraction of patterns from a spatial or a temporal aspect. Here we use the Bregman block average co-clustering algorithm with I-divergence (BBAC_I) to enable the simultaneous analysis of spatial and temporal patterns in geo-referenced time series (time evolving values of a property observed at fixed geographical locations). In addition, we present three geovisualization techniques to fully explore the co-clustering results: heatmaps offer a straightforward overview of the results; small multiples display the spatial and temporal patterns in geographic maps; ringmaps illustrate the temporal patterns associated to cyclic timestamps. To illustrate this study, we used Dutch daily average temperature data collected at 28 weather stations from 1992 to 2011. The co-clustering algorithm was applied hierarchically to understand the spatio-temporal patterns found in the data at the yearly, monthly and daily resolutions. Results pointed out that there is a transition in temperature patterns from northeast to southwest and from ‘cold’ to ‘hot’ years/months/days with only 3 years belonging to ‘cool’ or ‘cold’ years. Because of its characteristics, this newly introduced algorithm can concurrently analyse spatial and temporal patterns by identifying location-timestamp co-clusters that contain values that are similar along both the spatial and the temporal dimensions. Numéro de notice : A2015-590 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2014.994520 En ligne : http://www.tandfonline.com/doi/full/10.1080/13658816.2014.994520 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77876
in International journal of geographical information science IJGIS > vol 29 n° 4 (April 2015) . - pp 624 - 642[article]Object-based assessment of burn severity in diseased forests using high-spatial and high-spectral resolution MASTER airborne imagery / Gang Chen in ISPRS Journal of photogrammetry and remote sensing, vol 102 (April 2015)
[article]
Titre : Object-based assessment of burn severity in diseased forests using high-spatial and high-spectral resolution MASTER airborne imagery Type de document : Article/Communication Auteurs : Gang Chen, Auteur ; Margaret R. Metz, Auteur ; David M. Rizzo, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 38 - 47 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] analyse en composantes principales
[Termes IGN] Californie (Etats-Unis)
[Termes IGN] délimitation
[Termes IGN] houppier
[Termes IGN] image à ultra haute résolution
[Termes IGN] image aérienne
[Termes IGN] image MASTER
[Termes IGN] impact sur l'environnement
[Termes IGN] incendie de forêt
[Termes IGN] maladie phytosanitaire
[Termes IGN] réflectance végétaleRésumé : (auteur) Forest ecosystems are subject to a variety of disturbances with increasing intensities and frequencies, which may permanently change the trajectories of forest recovery and disrupt the ecosystem services provided by trees. Fire and invasive species, especially exotic disease-causing pathogens and insects, are examples of disturbances that together could pose major threats to forest health. This study examines the impacts of fire and exotic disease (sudden oak death) on forests, with an emphasis on the assessment of post-fire burn severity in a forest where trees have experienced three stages of disease progression pre-fire: early-stage (trees retaining dried foliage and fine twigs), middle-stage (trees losing fine crown fuels), and late-stage (trees falling down). The research was conducted by applying Geographic Object-Based Image Analysis (GEOBIA) to MASTER airborne images that were acquired immediately following the fire for rapid assessment and contained both high-spatial (4 m) and high-spectral (50 bands) resolutions. Although GEOBIA has gradually become a standard tool for analyzing high-spatial resolution imagery, high-spectral resolution data (dozens to hundreds of bands) can dramatically reduce computation efficiency in the process of segmentation and object-based variable extraction, leading to complicated variable selection for succeeding modeling. Hence, we also assessed two widely used band reduction algorithms, PCA (principal component analysis) and MNF (minimum noise fraction), for the delineation of image objects and the subsequent performance of burn severity models using either PCA or MNF derived variables. To increase computation efficiency, only the top 5 PCA and MNF and top 10 PCA and MNF components were evaluated, which accounted for 10% and 20% of the total number of the original 50 spectral bands, respectively. Results show that if no band reduction was applied the models developed for the three stages of disease progression had relatively similar performance, where both spectral responses and texture contributed to burn assessments. However, the application of PCA and MNF introduced much greater variation among models across the three stages. For the early-stage disease progression, neither band reduction algorithms improved or retained the accuracy of burn severity modeling (except for the use of 10 MNF components). Compared to the no-band-reduction scenario, band reduction led to a greater level of overestimation of low-degree burns and underestimation of medium-degree burns, suggesting that the spectral variation removed by PCA and MNF was vital for distinguishing between the spectral reflectance from disease-induced dried crowns (still retaining high structural complexity) and fire ash. For the middle-stage, both algorithms improved the model R2 values by 2–37%, while the late-stage models had comparable or better performance to those using the original 50 spectral bands. This could be explained by the loss of tree crowns enabling better signal penetration, thus leading to reduced spectral variation from canopies. Hence, spectral bands containing a high degree of random noise were correctly removed by the band reduction algorithms. Compared to the middle-stage, the late-stage forest stands were covered by large piles of fallen trees and branches, resulting in higher variability of MASTER imagery. The ability of band reduction to improve the model performance for these late-stage forest stands was reduced, because the valuable spectral variation representing the actual late-stage forest status was partially removed by both algorithms as noise. Our results indicate that PCA and MNF are promising for balancing computation efficiency and the performance of burn severity models in forest stands subject to the middle and late stages of sudden oak death disease progression. Compared to PCA, MNF dramatically reduced image spectral variation, generating larger image objects with less complexity of object shapes. Whereas, PCA-based models delivered superior performance in most evaluated cases suggesting that some key spectral variability contributing to the accuracy of burn severity models in diseased forests may have been removed together with true spectral noise through MNF transformations. Numéro de notice : A2015-475 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.01.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.01.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77183
in ISPRS Journal of photogrammetry and remote sensing > vol 102 (April 2015) . - pp 38 - 47[article]Data-driven feature learning for high resolution urban land-cover classification / Piotr Andrzej Tokarczyk (2015)PermalinkPermalinkSubspace-based technique for speckle noise reduction in SAR images / Norashikin Yahya in IEEE Transactions on geoscience and remote sensing, vol 52 n° 10 tome 1 (October 2014)PermalinkA user study of experimental maps for outdoor activities / Juha Oksanen in Cartographica, vol 49 n° 3 (September 2014)PermalinkNovel Folded-PCA for improved feature extraction and data reduction with hyperspectral imaging and SAR in remote sensing / Jaime Zabalza in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)PermalinkDiscrimination des unités géologiques et structurales du socle précambrien de l'Afrique de l'ouest à l'aide de transformations multispectrales : cas du degré carré de Korhogo au nord de la Côte d'Ivoire / K. Kouamé in Photo interprétation, European journal of applied remote sensing, vol 50 n° 2 (juin 2014)PermalinkLes effets de l'oscillation Nord-Atlantique sur les transferts de masse, vus par géodésie / Pierre Valty in XYZ, n° 139 (juin - août 2014)PermalinkMapping large spatial flow data with hierarchical clustering / Xi Zhu in Transactions in GIS, vol 18 n° 3 (June 2014)PermalinkCombining Geo-SOM and hierarchical clustering to explore geospatial data / Chen-Chieh Feng in Transactions in GIS, vol 18 n° 1 (February 2014)PermalinkAbstracting geographic information in a data rich world, ch. 3. Modelling geographic relationships in automated environments / Guillaume Touya (2014)PermalinkPermalinkSpatiotemporal filtering of regional GNSS network’s position time series with missing data using principle component analysis / Yunzhong Shen in Journal of geodesy, vol 88 n° 1 (January 2014)PermalinkProcessing and calibration of submillimeter Fourier transform radiometer spectra from the RHUBC-II campaign / Scott N. Paine in IEEE Transactions on geoscience and remote sensing, vol 51 n° 12 (December 2013)PermalinkScale-specific automated line simplification by vertex clustering on a hexagonal tessellation / Paulo Raposo in Cartography and Geographic Information Science, vol 40 n° 5 (November 2013)PermalinkLa combinaison d'indicateurs de changement pour le suivi de l'évolution de l'occupation du sol à partir d'imagerie satellitale / Faten Katlane in Revue Française de Photogrammétrie et de Télédétection, n° 203 (Juillet 2013)PermalinkContribution des données ALOS et Landsat dans la cartographie et l'analyse des linéaments dans le Sahel central (Maroc occidental) / Adnane Habib in Revue Française de Photogrammétrie et de Télédétection, n° 203 (Juillet 2013)PermalinkAssessing the impact of hydrocarbon leakages on vegetation using reflectance spectroscopy / I.D. Sanches in ISPRS Journal of photogrammetry and remote sensing, vol 78 (April 2013)PermalinkFootprint generation using fuzzy-neighborhood clustering / Jonathon K. Parker in Geoinformatica, vol 17 n° 2 (April 2013)PermalinkSpatio-temporal polygonal clustering with space and time as first-class citizens / Deepti Joshi in Geoinformatica, vol 17 n° 2 (April 2013)PermalinkClassification and reconstruction from random projections for hyperspectral imagery / W. Li in IEEE Transactions on geoscience and remote sensing, vol 51 n° 2 (February 2013)PermalinkTrajectories of moving objects on a network: detection of similarities, visualization of relations, and classification of trajectories / Yukio Sadahiro in Transactions in GIS, vol 17 n° 1 (February 2013)PermalinkEstimation de la qualité des résultats [d'une] classification sous ENVI / Nidal Aburajab (2013)PermalinkManual of photogrammetry, sixth edition / J. Chris Mcglone (2013)PermalinkSemisupervised learning of hyperspectral data with unknown land-cover classes / G. Jun in IEEE Transactions on geoscience and remote sensing, vol 51 n° 1 Tome 1 (January 2013)PermalinkContribution des images ASTER à la connaissance des aquifères fracturés de la région de Duékoué (Ouest de la Côte d'Ivoire) / Aimé Koudou in Photo interprétation, European journal of applied remote sensing, vol 48 n° 4 (décembre 2012)PermalinkTélédétection de la trame verte arborée en haute résolution par morphologie mathématique / E. Maire in Revue internationale de géomatique, vol 22 n° 4 (décembre 2012 – février 2013)PermalinkBuilt-up and vegetation extraction and density mapping using WorldView-II / A. Kumar in Geocarto international, vol 27 n° 7 (November 2012)PermalinkCluster recognition in spatial-temporal sequences: the case of forest fires / C. Vega Orozco in Geoinformatica, vol 15 n° 4 (October 2012)PermalinkSemisupervised classification of remote sensing images with active queries / Jordi Munoz-Mari in IEEE Transactions on geoscience and remote sensing, vol 50 n° 10 Tome 1 (October 2012)PermalinkUtilisation de la télédétection et de données socio-économiques et écologiques pour comprendre l'impact des dynamiques de l'occupation des sols à Pacaja (Brésil) / J. Oszwald in Revue Française de Photogrammétrie et de Télédétection, n° 198 - 199 (Septembre 2012)PermalinkClassification of urban tree species using hyperspectral imagery / R. Jensen in Geocarto international, vol 27 n° 5 (August 2012)PermalinkHyperspectral band clustering and band selection for urban land cover classification / H. Su in Geocarto international, vol 27 n° 5 (August 2012)PermalinkMemory-based cluster sampling for remote sensing image classification / Michele Volpi in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)PermalinkSatellite image time series analysis under time warping / F. Petitjean in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)PermalinkTrees detection from laser point clouds acquired in dense urban areas by a mobile mapping system / Fabrice Monnier in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol I-3 (2012)PermalinkSeparation of global time-variable gravity signals into maximally independent components / E. Forootan in Journal of geodesy, vol 86 n° 7 (July 2012)PermalinkDiscovering spatial patterns in origin-destination mobility data / D. Guo in Transactions in GIS, vol 16 n° 3 (June 2012)PermalinkEfficient parallel algorithm for pixel classification in remote sensing imagery / U. Maulik in Geoinformatica, vol 16 n° 2 (April 2012)PermalinkFuzzy analysis for modeling regional delineation and development: The case of the Sardinian mining geopark / G. Manca in Transactions in GIS, vol 16 n° 1 (February 2012)PermalinkCartographie du déboisement à partir de données à haute résolution spatiale / Yannick Philippets (2012)PermalinkTraitements numériques des images de télédétection, Vol. 3. Traitements appliqués à la photo-interprétation / Olivier de Joinville (2012)PermalinkClustering of detected changes in high-resolution satellite imagery using a stabilized competitive agglomeration algorithm / O. Sjahputera in IEEE Transactions on geoscience and remote sensing, vol 49 n° 12 Tome 1 (December 2011)PermalinkPixel unmixing in hyperspectral data by means of neural networks / Giorgio Licciardi in IEEE Transactions on geoscience and remote sensing, vol 49 n° 11 Tome 1 (November 2011)PermalinkSpatial patterns and eco-epidemiological systems – part 1: multi-scale spatial modelling of the occurrence of Chagas disease insect vectors / Emmanuel Roux in Geospatial Health, vol 6 n° 1 (November 2011)PermalinkSpatial patterns and eco-epidemiological systems – part 2: multi-scale spatial modelling of the occurrence of Chagas disease insect vectors / Emmanuel Roux in Geospatial Health, vol 6 n° 1 (November 2011)Permalink