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Delineation of groundwater potential zones using remote sensing and GIS-based data-driven models / Samira Ghorbani Nejad in Geocarto international, vol 32 n° 2 (February 2017)
[article]
Titre : Delineation of groundwater potential zones using remote sensing and GIS-based data-driven models Type de document : Article/Communication Auteurs : Samira Ghorbani Nejad, Auteur ; Fatemeh Falah, Auteur ; Mania Daneshfar, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 167 - 187 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] base de données topographiques
[Termes IGN] carte hydrogéologique
[Termes IGN] eau souterraine
[Termes IGN] géomorphologie locale
[Termes IGN] image satellite
[Termes IGN] Iran
[Termes IGN] modèle orienté objet
[Termes IGN] ressources en eau
[Termes IGN] système d'information géographique
[Termes IGN] théorie de Dempster-ShaferRésumé : (auteur) The rapid increase in human population has increased the groundwater resources demand for drinking, agricultural and industrial purposes. The main purpose of this study is to produce groundwater potential map (GPM) using weights-of-evidence (WOE) and evidential belief function (EBF) models based on geographic information system in the Azna Plain, Lorestan Province, Iran. A total number of 370 groundwater wells with discharge more than 10 m3s−1were considered and out of them, 256 (70%) were randomly selected for training purpose, while the remaining114 (30%) were used for validating the model. In next step, the effective factors on the groundwater potential such as altitude, slope aspect, slope angle, curvature, distance from rivers, drainage density, topographic wetness index, fault distance, fault density, lithology and land use were derived from the spatial geodatabases. Subsequently, the GPM was produced using WOE and EBF models. Finally, the validation of the GPMs was carried out using areas under the ROC curve (AUC). Results showed that the GPM prepared using WOE model has the success rate of 73.62%. Similarly, the AUC plot showed 76.21% prediction accuracy for the EBF model which means both the models performed fairly good predication accuracy. The GPMs are useful sources for planners and engineers in water resource management, land use planning and hazard mitigation purpose. Numéro de notice : A2017-133 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2015.1132481 Date de publication en ligne : 25/01/2016 En ligne : http://dx.doi.org/10.1080/10106049.2015.1132481 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85199
in Geocarto international > vol 32 n° 2 (February 2017) . - pp 167 - 187[article]Modeling of ionosphere time series using wavelet neural networks (case study: N-W of Iran) / Mir Reza Ghaffari Razin in Advances in space research, vol 58 n° 1 (July 2016)
[article]
Titre : Modeling of ionosphere time series using wavelet neural networks (case study: N-W of Iran) Type de document : Article/Communication Auteurs : Mir Reza Ghaffari Razin, Auteur ; Behzad Voosoghi, Auteur Année de publication : 2016 Article en page(s) : pp 74 - 83 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] International Reference Ionosphere
[Termes IGN] Iran
[Termes IGN] modèle numérique
[Termes IGN] ondelette
[Termes IGN] réseau neuronal artificiel
[Termes IGN] série temporelle
[Termes IGN] teneur totale en électronsRésumé : (auteur) Wavelet neural networks (WNNs) are important tools for analyzing time series especially when it is non-linear and non-stationary. It takes advantage of high resolution of wavelets and feed forward nature of neural networks (NNs). Therefore, in this paper, WNNs is used for modeling of ionosphere time series in Iran. To apply the method, observations collected at 22 GPS stations in 12 successive days of 2012 (DOY# 219–230) from Azerbaijan local GPS network are used. For training of WNN, back-propagation (BP) algorithm is used. The results of WNN compared with results of international reference ionosphere 2012 (IRI-2012) and international GNSS service (IGS) products. To assess the error of WNN, statistical indicators, relative and absolute errors are used. Minimum relative error for WNN compared with GPS TEC is 6.37% and maximum relative error is 12.94%. Also the maximum and minimum absolute error computed 6.32 and 0.13 TECU, respectively. Comparison of diurnal predicted TEC values from the WNN model and the IRI-2012 with GPS TEC revealed that the WNN provides more accurate predictions than the IRI-2012 model and IGS products in the test area. Numéro de notice : A2016-562 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.asr.2016.04.006 En ligne : http://dx.doi.org/10.1016/j.asr.2016.04.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81742
in Advances in space research > vol 58 n° 1 (July 2016) . - pp 74 - 83[article]Relationship between landform classification and vegetation (case study: southwest of Fars province, Iran) / Marzieh Mokarram in Open geosciences, vol 8 n° 1 (January - July 2016)
[article]
Titre : Relationship between landform classification and vegetation (case study: southwest of Fars province, Iran) Type de document : Article/Communication Auteurs : Marzieh Mokarram, Auteur ; Dinesh Sathyamoorthy, Auteur Année de publication : 2016 Article en page(s) : pp 302 - 309 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] classification
[Termes IGN] hauteur des arbres
[Termes IGN] Iran
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] régression multipleRésumé : (auteur) This study is aimed at investigating the relationship between landform classification and vegetation in the southwest of Fars province, Iran. First, topographic position index (TPI) is used to perform landform classification using a Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) with resolution of 30 m. The classification has ten classes; high ridges, midslope ridges, upland drainage, upper slopes, open slopes, plains, valleys, local ridges, midslope drainage and streams. Visual interpretation indicates that for the local, midslope and high ridge landforms, normalized difference vegetation index (NDVI) values and tree heights are higher as compared to the other landforms. In addition, it is found that there are positive and significant correlations betweenNDVI and tree height (r = 0.923), and landform and NDVI (r = 0.640). This shows that landform classification and NDVI can be used to predict tree height in the area. High correlation of determination (R2) 0.909 is obtained for the prediction of tree height using landform classification and NDVI. Numéro de notice : A2016--067 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1515/geo-2016-0027 En ligne : https://doi.org/10.1515/geo-2016-0027 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84413
in Open geosciences > vol 8 n° 1 (January - July 2016) . - pp 302 - 309[article]Estimation of forest biomass using multivariate relevance vector regression / Alireza Sharifi in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 1 (January 2016)
[article]
Titre : Estimation of forest biomass using multivariate relevance vector regression Type de document : Article/Communication Auteurs : Alireza Sharifi, Auteur ; Jalal Amini, Auteur ; Ryutaro Tateishi, Auteur Année de publication : 2016 Article en page(s) : pp 41 - 49 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse aérienne
[Termes IGN] biomasse forestière
[Termes IGN] estimation statistique
[Termes IGN] forêt
[Termes IGN] image ALOS-PALSAR
[Termes IGN] Iran
[Termes IGN] Perceptron multicouche
[Termes IGN] régression multiple
[Termes IGN] séparateur à vaste marge
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) The objective of this study is to develop a method based on multivariate relevance vector regression (MVRVR) as a kernelbased Bayesian model for the estimation of above-ground biomass (AGB) in the Hyrcanian forests of Iran. Field AGB data from the Hyrcanian forests and multi-temporal PALSAR backscatter values are used for training and testing the methods. The results of the MVRVR method are then compared with other methods: multivariate linear regression (MLR), multilayer perceptron neural network (MLPNN), and support vector regression (SVR). The MLR model showed lower values of R2 than the three other approaches. Although the SVR model was found to be more accurate than MLPNN, it had the lowest saturation point of 224.75 Mg/ha. The use of MVRVR model significantly improves the estimation of AGB (R2 = 0.90; RMSE = 32.05 Mg/ha), and the model showed a superior performance in estimating AGB with the highest saturation point (297.81 Mg/ha). Numéro de notice : A2016-053 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.14358/PERS.83.1.41 En ligne : https://doi.org/10.14358/PERS.83.1.41 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79654
in Photogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 1 (January 2016) . - pp 41 - 49[article]3D web services for visualization and data sharing in 3D cadastre / Ali Zare Zardiny in International journal of 3-D information modeling, vol 4 n° 4 (October - December 2015)
[article]
Titre : 3D web services for visualization and data sharing in 3D cadastre Type de document : Article/Communication Auteurs : Ali Zare Zardiny, Auteur ; Farshad Hakimpour, Auteur Année de publication : 2015 Article en page(s) : pp 1 - 15 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cadastre étranger
[Termes IGN] cadastre 3D
[Termes IGN] cartographie à la volée
[Termes IGN] CityGML
[Termes IGN] données localisées 3D
[Termes IGN] droit foncier
[Termes IGN] géovisualisation
[Termes IGN] information sémantique
[Termes IGN] interopérabilité
[Termes IGN] Iran
[Termes IGN] partage de données localisées
[Termes IGN] service web géographique
[Termes IGN] Web Feature Service
[Termes IGN] Web Map Tile Service
[Termes IGN] Web View ServiceRésumé : (Auteur) Land has an essential role in any society, either as one of the most important capitals of mankind or as a place for people's life and activities. Therefore, registration of ownership and land use rights in a formal system is a major issue. In different countries, Cadastre systems can register extent, rights, restrictions and responsibilities related to land parcels. Many organizations such as municipality, tax and banks need to this information for planning and decision making. Considering the needs for land information by different organizations, access to cadastre data gains a lot of importance. Despite this importance, access to cadastre information encounter with different challenges such as differences in platforms or data structures and access to semantic and geometric data. The main goal of this research is to overcome these challenges and to improve the interoperability in sharing and accessing 3D cadastre data and challenges. This paper investigates capabilities of current 3D Spatial Web Services: WFS, WVS, WTS and W3DS as well as advantages of using these 3D services for access to 3D cadastre data. The authors also combined the legal classes of LADM with geometrical classes of CityGML for transferring the semantic and geometric cadastre data. Finally, some prospects of using 3D Web Services will be illustrated through implementation the scenarios. The most important advantages of using 3D Spatial Web Services in cadastre are on the fly construction and on demand presentation of 3D cadastral model, facilitating of access to legal and descriptive cadastre information, no necessity to user's awareness of data structure in cadastre database and compatibility with different levels of users. Numéro de notice : A2016-428 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.4018/IJ3DIM.2015100101 En ligne : http://doi.org/10.4018/ij3dim.2015100101 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81322
in International journal of 3-D information modeling > vol 4 n° 4 (October - December 2015) . - pp 1 - 15[article]Réservation
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