Descripteur
Documents disponibles dans cette catégorie (25)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
µ-shapes: Delineating urban neighborhoods using volunteered geographic information / Matt Aadland in Journal of Spatial Information Science, JoSIS, n° 12 (March 2016)
[article]
Titre : µ-shapes: Delineating urban neighborhoods using volunteered geographic information Type de document : Article/Communication Auteurs : Matt Aadland, Auteur ; Christopher Farah, Auteur ; Kevin Magee, Auteur Année de publication : 2016 Article en page(s) : pp 29 - 43 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] analyse de variance
[Termes IGN] centroïde
[Termes IGN] délimitation
[Termes IGN] données localisées des bénévoles
[Termes IGN] matrice de confusion
[Termes IGN] répertoire toponymique
[Termes IGN] sous ensemble flou
[Termes IGN] traitement de données localisées
[Termes IGN] voisinage (relation topologique)
[Termes IGN] zone urbaineRésumé : (auteur) Urban neighborhoods are a unique form of geography in that their boundaries rely on a social definition rather than a well-defined physical or administrative boundary. Currently, geographic gazetteers capture little more than then the centroid of a neighborhood, limiting potential applications of the data. In this paper, we present µ-shapes, an algorithm that employs fuzzy-set theory to model neighborhood boundaries suitable for populating gazetteers using volunteered geographic information (VGI). The algorithm is evaluated using a reference dataset and VGI from the Map Kibera Project. A confusion matrix comparison between the reference dataset and µ-shape's output demonstrated high sensitivity and accuracy. Analysis of variance indicated that the algorithm was able to distinguish between boundary and interior blocks. This suggests that, given the existing state of GIS technology, the µ-shapes algorithm can enable neighborhood-related queries that incorporate spatial uncertainty, e.g., find all restaurants within the core of a neighborhood. Numéro de notice : A2016-954 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : sans En ligne : http://dx.doi.org/10.5311/JOSIS.2016.12.240 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83466
in Journal of Spatial Information Science, JoSIS > n° 12 (March 2016) . - pp 29 - 43[article]Overcoming lidar’s Big data problem / Rick Harrison in GEO: Geoconnexion international, vol 14 n° 9 (October 2015)
[article]
Titre : Overcoming lidar’s Big data problem Type de document : Article/Communication Auteurs : Rick Harrison, Auteur Année de publication : 2015 Article en page(s) : pp 27 - 28 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] délimitation
[Termes IGN] données massives
[Termes IGN] filtrage numérique d'image
[Termes IGN] semis de points
[Termes IGN] zone d'intérêtRésumé : (éditeur) Lidar can measure surfaces incredibly accurately, but it can produce huge amounts of data as a result, slowing down software, sometimes to the point of unusability. Here, Rick Harrison reveals eight simple steps to cut the problem down to size Numéro de notice : A2015-655 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78259
in GEO: Geoconnexion international > vol 14 n° 9 (October 2015) . - pp 27 - 28[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]Mathematical morphology pre-processing for enhanced segmentation of heterogeneous spatial regions / Julien Radoux in Revue Française de Photogrammétrie et de Télédétection, n° 208 (Octobre 2014)
[article]
Titre : Mathematical morphology pre-processing for enhanced segmentation of heterogeneous spatial regions Type de document : Article/Communication Auteurs : Julien Radoux, Auteur ; Pierre Defourny, Auteur Année de publication : 2014 Conférence : Pleiades Days 2014 01/04/2014 03/04/2014 Toulouse France Article en page(s) : pp 33 - 38 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] délimitation
[Termes IGN] image Pléiades
[Termes IGN] morphologie mathématique
[Termes IGN] segmentation d'imageRésumé : (Auteur) The very high spatial resolution of Pleiades images allows for the detection of small spatial objects such as buildings or isolated trees. However, the delineation of spatial regions, defined as associations between different spatial objects (such as open canopy forests or urban areas), becomes more challenging with the high level of details. On one hand, automated image segmentation algorithms often yield over-segmented polygons due to due to the high spectral heterogeneity of those regions. On the other hand, manual delineation was shown to end up with a significant bias from the interpreter and even a lack of consistency when the same person works more than one hour on the same task. In this study, we aimed at implementing a new filter to increase the contextual consistency of automated segmentation while preserving the geometric precision of the delineation of spectrally homogeneous spatial regions. A new mathematical morphology approach is proposed, which consists in applying a set of rules to an image based on the presence of absence of vegetation pixels within a structuring element. Two composite filters were then built based on the new filters. The opening filter removes isolated vegetation patches inside heterogeneous spatial regions, while the closing filter fills the gaps between those vegetation patches. The filters have been tested on a Pleiades images located in Belgium around the city of Leuven. A composite image was then created with the NIR and Red filtered bands stacked with the original image bands. The composite and the original bands were then segmented using e-Cognition software with the same parameters. The results show that the segmentation of the filtered images is spatially more consistent than the segmentation based on the unfiltered image. The over-segmentation is reduced in the heterogeneous areas, while the precision of the delineation is improved. The objects derived from the filtered images are thus more appropriate for the monitoring of spatial regions. Numéro de notice : A2014-605 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.52638/rfpt.2014.133 En ligne : https://doi.org/10.52638/rfpt.2014.133 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74905
in Revue Française de Photogrammétrie et de Télédétection > n° 208 (Octobre 2014) . - pp 33 - 38[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 018-2014011 RAB Revue Centre de documentation En réserve L003 Disponible Agricultural field delimitation using active learning and random forests margin / Karim Ghariani (2014)
Titre : Agricultural field delimitation using active learning and random forests margin Type de document : Article/Communication Auteurs : Karim Ghariani, Auteur ; Nesrine Chehata , Auteur ; Arnaud Le Bris , Auteur ; Philippe Lagacherie, Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2014 Conférence : IGARSS 2014, International Geoscience And Remote Sensing Symposium 13/07/2014 18/07/2014 Québec Québec - Canada Proceedings IEEE Importance : pp 1717 - 1720 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage automatique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] délimitation
[Termes IGN] image Geoeye
[Termes IGN] surface cultivéeRésumé : (auteur) Agricultural practices and spatial arrangements of fields have a strong impact on water flows in cultivated landscapes. In order to monitor landscapes at a large scale, there is a strong need for automatic or semi-automatic field delineation. Field measurements for delineating parcel network are not efficient, thus very high resolution satellite imagery should help delineating agricultural fields in a automatic way. This study focuses on agricultural field delineation based on the classification of very high resolution satellite imagery. A hybrid approach is proposed and combines a region-based approach and active learning (AL) techniques. Random forest (RF) classifier is used for classification and feature selection. The margin concept is used as uncertainty measure in active learning algorithm. Satisfying results are shown on a Geoeye image. AL RF model is compared to simple and global RF models that are built from adjacent and geographically distant fields respectively. Numéro de notice : C2014-029 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/IGARSS.2014.6946782 En ligne : http://dx.doi.org/10.1109/IGARSS.2014.6946782 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83401 Documents numériques
peut être téléchargé
Agricultural field delimitation - posterAdobe Acrobat PDF Semi-automated extraction and delineation of 3D roads of street scene from mobile laser scanning point clouds / Bishen Yang in ISPRS Journal of photogrammetry and remote sensing, vol 79 (May 2013)PermalinkOn the integration of regional classification and delineation systems into The National Map / T. Bittner in Cartographica, vol 45 n° 2 (June 2010)PermalinkDes domaines d'intervention multiples / B. Loreau in Géomètre, n° 2059 (mai 2009)PermalinkAutomatic extraction of urban vegetation structures from high resolution imagery and digital elevation models / Corina Iovan (2007)PermalinkConnecting historical and contemporary small-area geography in Britain: the creation of digital boundary data for 1971 and 1981 census / N. Walford in International journal of geographical information science IJGIS, vol 19 n° 7 (august 2005)PermalinkUse of a digital terrain model as a means of urban watershed delineation in Fredericton, New Brunswick / Wade MacNutt in Geomatica, vol 58 n° 2 (June 2004)PermalinkDelineation of forest/nonforest land use classes using nearest neighbor methods / R. Haapanen in Remote sensing of environment, vol 89 n° 3 (15/02/2004)PermalinkA GIS-based spatial pattern analysis model for eco-region mapping and characterization / Y. Zhou in International journal of geographical information science IJGIS, vol 17 n° 5 (july - August 2003)PermalinkGIS-based watershed delineation using the spatial analyst hydrologic modelling extension / F. Whelan in GIS Geo-Informations-Systeme, vol 2002 n° 6 (Juni 2002)Permalink