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scientifique

Local color and morphological image feature based vegetation identification and its application to human environment street view vegetation mapping, or how green is our county? / Istvan G. Lauko in Geo-spatial Information Science, vol 23 n° 3 (September 2020)  

Public [article]  inGeo-spatial Information Science > vol 23 n° 3 (September 2020) . - pp 222 - 236 Titre : Local color and morphological image feature based vegetation identification and its application to human environment street view vegetation mapping, or how green is our county? Type de document : Article/Communication Auteurs : Istvan G. Lauko, Auteur ; Adam Honts, Auteur ; Jacob Beihoff, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 222 - 236 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] carte de la végétation [Termes IGN] cartographie urbaine [Termes IGN] couleur (variable spectrale) [Termes IGN] densité de la végétation [Termes IGN] extraction de la végétation [Termes IGN] gestion urbaine [Termes IGN] image panoramique [Termes IGN] image Streetview [Termes IGN] indicateur environnemental [Termes IGN] indice de végétation [Termes IGN] Milwaukee [Termes IGN] paysage urbain [Termes IGN] rayonnement proche infrarouge Résumé : (auteur) Measuring the amount of vegetation in a given area on a large scale has long been accomplished using satellite and aerial imaging systems. These methods have been very reliable in measuring vegetation coverage accurately at the top of the canopy, but their capabilities are limited when it comes to identifying green vegetation located beneath the canopy cover. Measuring the amount of urban and suburban vegetation along a street network that is partially beneath the canopy has recently been introduced with the use of Google Street View (GSV) images, made accessible by the Google Street View Image API. Analyzing green vegetation through the use of GSV images can provide a comprehensive representation of the amount of green vegetation found within geographical regions of higher population density, and it facilitates an analysis performed at the street-level. In this paper we propose a fine-tuned color based image filtering and segmentation technique and we use it to define and map an urban green environment index. We deployed this image processing method and, using GSV images as a high-resolution GIS data source, we computed and mapped the green index of Milwaukee County, a 3,082 km2 urban/suburban county in Wisconsin. This approach generates a high-resolution street-level vegetation estimate that may prove valuable in urban planning and management, as well as for researchers investigating the correlation between environmental factors and human health outcomes. Numéro de notice : A2020-563 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2020.1805367 Date de publication en ligne : 24/08/2020 En ligne : https://doi.org/10.1080/10095020.2020.1805367 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95880 [article]

Incorporating crown shape information for identifying ash tree species / Haijian Liu in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 8 (août 2018)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 84 n° 8 (août 2018) . - pp 495 - 503 Titre : Incorporating crown shape information for identifying ash tree species Type de document : Article/Communication Auteurs : Haijian Liu, Auteur ; Changshan Wu, Auteur Année de publication : 2018 Article en page(s) : pp 495 - 503 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Fraxinus (genre) [Termes IGN] fusion de données [Termes IGN] hauteur des arbres [Termes IGN] houppier [Termes IGN] image aérienne [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] Milwaukee [Termes IGN] photo-interprétation assistée par ordinateur [Termes IGN] zone urbaine Résumé : (Auteur) Identifying ash trees from other common deciduous trees is challenging due to subtle spectral differences of foliage among species. Although many researchers have integrated lidar-derived tree height and crown size metrics to improve tree species classification accuracy, these simple biophysical attributes provide inadequate explanatory power in distinguishing ash trees (Fraxinus, spp.) in urban ecosystems. To address this issue, shape-related features, including crown shape index (SI) and coefficient of variation (CV) of crown height, were extracted from lidar data, and fused with treetopbased spectra for ash tree species identification in Milwaukee City, Wisconsin, United States. Analysis results indicate shape features including SI and CV play a big role in improving the accuracy for ash tree identification. Specifically, Fusion of CV and treetop-based spectra improved the overall accuracy from 81.9 percent to 89 percent, and McNemar tests indicated the differences in accuracy between CV fusion and tree height fusion was statistically significant (p = 0.016). Numéro de notice : A2018-360 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.84.8.495 Date de publication en ligne : 01/08/2018 En ligne : https://doi.org/10.14358/PERS.84.8.495 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90600 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2018081	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Incorporating remote sensing information in modelling house values: a regression tree approach / D. Yu in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 2 (February 2006)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 72 n° 2 (February 2006) . - pp 129 - 138 Titre : Incorporating remote sensing information in modelling house values: a regression tree approach Type de document : Article/Communication Auteurs : D. Yu, Auteur ; C. Wu, Auteur Année de publication : 2006 Article en page(s) : pp 129 - 138 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de la valeur [Termes IGN] analyse linéaire des mélanges spectraux [Termes IGN] bati [Termes IGN] coefficient de corrélation [Termes IGN] erreur moyenne arithmétique [Termes IGN] habitat (urbanisme) [Termes IGN] image Landsat-ETM+ [Termes IGN] Milwaukee [Termes IGN] régression linéaire [Termes IGN] zone urbaine Résumé : (Auteur) This paper explores the possibility of incorporating remote sensing information in modeling house values in the City of Milwaukee, Wisconsin, U.S.A. In particular, a Landsat ETM+ image was utilized to derive environmental characteristics, including the fractions of vegetation, impervious surface, and soil, with a linear spectral mixture analysis approach. These environmental characteristics, together with house structural attributes, were integrated to house value models. Two modeling techniques, a global OLS regression and a regression tree approach, were employed to build the relationship between house values and house structural and environmental characteristics. Analysis of results indicates that environmental characteristics generated from remote sensing technologies have strong influences on house values, and the addition of them improves house value modeling performance significantly. Moreover, the regression tree model proves as a better alternative to the OLS regression models in terms of predicting accuracy. In particular, based on the testing dataset, the mean average error (MAE) and relative error (RE) dropped from 0.202 and 0.434 for the OLS model to 0.134 and 0.280 for the regression tree model, while the correlation coefficient between the predicted and observed values increased from 0.903 to 0.960. Further, as a nonparametric and local model, the regression tree method alleviates the problems with the OLS techniques and provides a means in delineating urban housing submarkets. Numéro de notice : A2006-037 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.14358/PERS.72.2.129 En ligne : https://doi.org/10.14358/PERS.72.2.129 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27764 [article]

PPGIS in community development planning: framing the organizational context / S. Elwood in Cartographica, vol 38 n° 3 - 4 (September 2001)  

Public [article]  inCartographica > vol 38 n° 3 - 4 (September 2001) . - pp 19 - 33 Titre : PPGIS in community development planning: framing the organizational context Type de document : Article/Communication Auteurs : S. Elwood, Auteur Année de publication : 2001 Article en page(s) : pp 19 - 33 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique [Termes IGN] communauté urbaine [Termes IGN] Milwaukee [Termes IGN] outil d'aide à la décision [Termes IGN] participation du public [Termes IGN] SIG participatif [Termes IGN] ville Résumé : (Auteur) This article examines the local variability of public participation GIS (PPGIS) by urban community revitalization organizations, arguing that this variability is in part shaped by a variety of organizational factors. Existing research has shown PPGIS production to be highly context dependent, identifying an ever-growing set of key elements of this context, including a variety of locally available resources for GIS access and use as well as organizational capacities and characteristics. Contributing to current efforts to expand the conceptual basis of PPGIS research, this article argues that the conceptualization of organizational context must be expanded beyond internal capacities to include organizational networks with local actors, institutions, and resources ; organizational knowledge and stability ; and organization mission and priorities, all of which shape its activities and relationships, as well as the utility of available GIS resources. This broadened conception of organizational context enables a stronger explanation of the influencing role of organizations in PPGIS, as well as of local variability in PPGIS. These arguments are developed from comparative case study research with six Milwaukee, WI community revitalization organizations engaged in PPGIS within a city-wide participatory planning initiative. Numéro de notice : A2004-165 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.3138/R411-50G8-1777-2120 En ligne : https://doi.org/10.3138/R411-50G8-1777-2120 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26692 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
031-01021	RAB	Revue	Centre de documentation	En réserve L003	Disponible