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Assessment of groundwater potential using multi-criteria decision analysis and geoelectrical surveying / Marzieh Shabani in Geo-spatial Information Science, vol 25 n° 4 (December 2022)
[article]
Titre : Assessment of groundwater potential using multi-criteria decision analysis and geoelectrical surveying Type de document : Article/Communication Auteurs : Marzieh Shabani, Auteur ; Zohreh Masoumi, Auteur ; Abolfazl Rezaei, Auteur Année de publication : 2022 Article en page(s) : pp 600 - 618 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] analyse de sensibilité
[Termes IGN] analyse multicritère
[Termes IGN] analyse spatiale
[Termes IGN] bassin hydrographique
[Termes IGN] carte thématique
[Termes IGN] développement durable
[Termes IGN] eau souterraine
[Termes IGN] gestion de l'eau
[Termes IGN] Iran
[Termes IGN] processus de hiérarchisation analytiqueRésumé : (auteur) A precise map of the dispersion of the groundwater potential across each watershed can help decision-makers to exert optimal water management in each region. In this research, the potential of groundwater resources in both the Zanjanrood Catchment and the Tarom Region, located in the northwest of Iran, has been studied. Seven effective criteria including slope, land-use, drainage density, spring density, lithology, lineament density, and rainfall are considered. Criteria were first weighted using the Analytical Hierarchical Process (AHP) method and then overlaid by the Technique for Order Preferences by Similarity to Ideal (TOPSIS) model. Finally, the spatial zoning map of groundwater potential was obtained in four categories. A sensitivity analysis was performed to determine the influence of each criterion on the obtained map. The model was verified using both the spatial distribution of the high-discharged production wells and the geophysical-based geoelectric field surveys. The results indicate that the high-discharged wells (>40 l/s) in both regions are dispersed predominantly in the very good zone and, in several cases, in the good zone. Besides, the results from the two-dimensional models of resistivity and induced polarization of geoelectrical field survey are inappropriate agreement with those from the TOPSIS method. Notably, there is no suitable potential zone of groundwater in the surrounding highlands to be used in the future for drinking purposes since the highlands water supply is a strategic supply for drinking. The strategies employed in this study, the results of GIS modeling, and the geoelectrical analysis can be considered for sustainable development of similar arid and semi-arid areas since groundwater is considered as the main supplier of water in such regions. Numéro de notice : A2022-891 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/10095020.2022.2069052 Date de publication en ligne : 10/05/2022 En ligne : https://doi.org/10.1080/10095020.2022.2069052 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102238
in Geo-spatial Information Science > vol 25 n° 4 (December 2022) . - pp 600 - 618[article]GIS-based land-use suitability analysis for urban agriculture development based on pollution distributions / Fatemeh Kazemi in Land use policy, vol 123 (December 2022)
[article]
Titre : GIS-based land-use suitability analysis for urban agriculture development based on pollution distributions Type de document : Article/Communication Auteurs : Fatemeh Kazemi, Auteur ; Nazanin Hosseinpour, Auteur Année de publication : 2022 Article en page(s) : n° 106426 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] agriculture
[Termes IGN] distribution spatiale
[Termes IGN] espace vert
[Termes IGN] Iran
[Termes IGN] milieu urbain
[Termes IGN] paysage urbain
[Termes IGN] pollution atmosphérique
[Termes IGN] pollution des sols
[Termes IGN] processus de hiérarchisation analytique
[Termes IGN] utilisation du solRésumé : (auteur) With recent increases in urban population and development, agricultural lands have been changed to residential areas and industrial settlements. Such urban population growth increases necessitate emerging relatively new strategies and forms in urban parks and landscape designs to meet today's economic, social, and ecological needs toward sustainable development. Urban agriculture is one of the strategies for achieving sustainable development and creating multi-purpose landscapes. Such an approach appears to partially solve the problem of agricultural land reduction and degradation. However, urban pollutants seem to hinder the development of such a sustainable concept in the cities. This research aimed to identify suitable locations for urban agriculture in urban green spaces according to various contamination criteria and the uniform distribution of the green spaces in Mashhad, Iran. In this research, using an Analytical Hierarchy Process (AHP) and a Geographic Information System (GIS) facilitated the decision-making process. It also determined the importance of the land use criteria for urban agricultural development. The results showed that the most suitable areas for urban agricultural development with the least impact of pollutants in Mashhad were the suburbs, especially in the northeast and southeast parts. These research results have practical implications for planning urban agricultural development at the city level across the world. Numéro de notice : A2022-895 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.landusepol.2022.106426 Date de publication en ligne : 03/11/2022 En ligne : https://doi.org/10.1016/j.landusepol.2022.106426 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102244
in Land use policy > vol 123 (December 2022) . - n° 106426[article]Hybrid XGboost model with various Bayesian hyperparameter optimization algorithms for flood hazard susceptibility modeling / Saeid Janizadeh in Geocarto international, vol 37 n° 25 ([01/12/2022])
[article]
Titre : Hybrid XGboost model with various Bayesian hyperparameter optimization algorithms for flood hazard susceptibility modeling Type de document : Article/Communication Auteurs : Saeid Janizadeh, Auteur Année de publication : 2022 Article en page(s) : pp 8273 - 8292 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] apprentissage automatique
[Termes IGN] ArcGIS
[Termes IGN] bassin hydrographique
[Termes IGN] cartographie des risques
[Termes IGN] classification par arbre de décision
[Termes IGN] colinéarité
[Termes IGN] estimation bayesienne
[Termes IGN] Extreme Gradient Machine
[Termes IGN] inondation
[Termes IGN] modèle numérique de surface
[Termes IGN] modélisation spatiale
[Termes IGN] optimisation (mathématiques)
[Termes IGN] TéhéranRésumé : (auteur) The purpose of this investigation is to develop an optimal model to flood susceptibility mapping in the Kan watershed, Tehran, Iran. Therefore, in this study, three Bayesian optimization hyper-parameter algorithms including Upper confidence bound (UCB), Probability of improvement (PI) and Expected improvement (EI) in order to Extreme Gradient Boosting (XGB) machine learning model optimization and Extreme randomize tree (ERT) model for modeling flood hazard were used. In order to perform flood susceptibility mapping, 118 historic flood locations were identified and analyzed using 17 geo-environmental explanatory variables to predict flooding susceptibility. Flood locations data were divided into 70% for training and 30% for testing of models developed. The receiver operating characteristic (ROC) curve parameters were used to evaluate the performance of the models. The evaluation results based on the criterion area under curve (AUC) in the testing stage showed that the ERT and XGB models have efficiencies of 91.37% and 91.95%, respectively. The evaluation of the efficiency of Bayesian hyperparameters optimization methods on the XGB model also showed that these methods increase the efficiency of the XGB model, so that the model efficiency using these methods EI-XGB, POI-XGB and UCB-XGB based on the AUC in the testing stage were 95.89%, 96.87% and 96.38%, respectively. The results of the relative importance of the five models shows that the variables of elevation and distance from the river are the significant compared to other variables in predicting flood hazard in the Kan watershed. Numéro de notice : A2022-931 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/10106049.2021.1996641 Date de publication en ligne : 29/10/2021 En ligne : https://doi.org/10.1080/10106049.2021.1996641 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102666
in Geocarto international > vol 37 n° 25 [01/12/2022] . - pp 8273 - 8292[article]A semi-automatic method for extraction of urban features by integrating aerial images and LIDAR data and comparing its performance in areas with different feature structures (case study: comparison of the method performance in Isfahan and Toronto) / Masoud Azad in Applied geomatics, vol 14 n° 4 (December 2022)
[article]
Titre : A semi-automatic method for extraction of urban features by integrating aerial images and LIDAR data and comparing its performance in areas with different feature structures (case study: comparison of the method performance in Isfahan and Toronto) Type de document : Article/Communication Auteurs : Masoud Azad, Auteur ; Farshid Farnood Ahmadi, Auteur Année de publication : 2022 Article en page(s) : pp 589 - 607 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] détection d'objet
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction de la végétation
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] extraction semi-automatique
[Termes IGN] image aérienne
[Termes IGN] Iran
[Termes IGN] modèle numérique de terrain
[Termes IGN] segmentation d'image
[Termes IGN] seuillage
[Termes IGN] Toronto
[Termes IGN] zone urbaineRésumé : (auteur) In this article, a new feature detection approach based on integration of LiDAR data and visible images in the form of a semi-automatic method has been proposed. In this approach, a two-step method for feature detection was developed using object-based analysis in order to increase the level of automation and level of accuracy in the detection process. The first step is providing a method for integration of two data sources for detection process by maintaining independency between image data and LiDAR altimetric data. In this step, the feature detection process is started based on image data and for detecting areas that detection properly is not done, LiDAR altimetric data is used. In the second step, a new method for detection of vegetation is implemented. Of the characteristics of this method is that there is no need to use the infrared band in the image data and also there is no need for LiDAR intensity data. The implemented method in the recent step is based on the new indices developed for detection of vegetation using three visible bands (red, green, and blue). The results of applying the method on two sample data sets show that the proposed approach and developed indices have the lowest dependency on the type and region of imaging and about each input image data includes visible bands (red, green, and blue) along with LiDAR data (that both data have a high spatial resolution), feature detection process is done with acceptable accuracy. Only thresholds depend on image data and change about different images. The changes are very small. Therefore, using the mean of these thresholds, despite may not be optimal for all image data, but generally is useful and for different images is efficient. In the case of many accessible images from Iran, the thresholds determined optimally by the trial-and-error method, the changes were very small. About the image data of Toronto and Iran which great changes were expected in the thresholds, the optimal thresholds showed very small changes. The results of this research demonstrated that the proposed method can successfully detect urban features (include vegetation, road, and building) with different shapes. Evaluation process showed that the overall accuracy, kappa coefficient, producer’s accuracy, and user’s accuracy of the proposed method about vegetation are 97%, 92%, 96%, and 94%, respectively. Also, the producer’s accuracy, user’s accuracy, and kappa coefficient about the building class are 94%, 95%, and 91%, respectively. About the road class these parameters are 95%, 89%, and 91%. Numéro de notice : A2022-892 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s12518-022-00455-x Date de publication en ligne : 10/08/2022 En ligne : https://doi.org/10.1007/s12518-022-00455-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102239
in Applied geomatics > vol 14 n° 4 (December 2022) . - pp 589 - 607[article]GCPs-free photogrammetry for estimating tree height and crown diameter in Arizona cypress plantation using UAV-mounted GNSS RTK / Morteza Pourreza in Forests, vol 13 n° 11 (November 2022)
[article]
Titre : GCPs-free photogrammetry for estimating tree height and crown diameter in Arizona cypress plantation using UAV-mounted GNSS RTK Type de document : Article/Communication Auteurs : Morteza Pourreza, Auteur ; Fardin Moradi, Auteur ; Mohammad Khosravi, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 1905 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] cupressus (genre)
[Termes IGN] diamètre des arbres
[Termes IGN] hauteur de vol
[Termes IGN] hauteur des arbres
[Termes IGN] image captée par drone
[Termes IGN] Iran
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] point d'appui
[Termes IGN] positionnement cinématique en temps réel
[Termes IGN] structure-from-motionRésumé : (auteur) One of the main challenges of using unmanned aerial vehicles (UAVs) in forest data acquisition is the implementation of Ground Control Points (GCPs) as a mandatory step, which is sometimes impossible for inaccessible areas or within canopy closures. This study aimed to test the accuracy of a UAV-mounted GNSS RTK (real-time kinematic) system for calculating tree height and crown height without any GCPs. The study was conducted on a Cupressus arizonica (Greene., Arizona cypress) plantation on the Razi University Campus in Kermanshah, Iran. Arizona cypress is commonly planted as an ornamental tree. As it can tolerate harsh conditions, this species is highly appropriate for afforestation and reforestation projects. A total of 107 trees were subjected to field-measured dendrometric measurements (height and crown diameter). UAV data acquisition was performed at three altitudes of 25, 50, and 100 m using a local network RTK system (NRTK). The crown height model (CHM), derived from a digital surface model (DSM), was used to estimate tree height, and an inverse watershed segmentation (IWS) algorithm was used to estimate crown diameter. The results indicated that the means of tree height obtained from field measurements and UAV estimation were not significantly different, except for the mean values calculated at 100 m flight altitude. Additionally, the means of crown diameter reported from field measurements and UAV estimation at all flight altitudes were not statistically different. Root mean square error (RMSE Numéro de notice : A2022-838 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/f13111905 Date de publication en ligne : 12/11/2022 En ligne : https://doi.org/10.3390/f13111905 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102039
in Forests > vol 13 n° 11 (November 2022) . - n° 1905[article]Tidal level prediction using combined methods of harmonic analysis and deep neural networks in Southern coastline of Iran / Kourosh Shahryari Nia in Marine geodesy, vol 45 n° 6 (November 2022)PermalinkDeveloping a GIS-based rough fuzzy set granulation model to handle spatial uncertainty for hydrocarbon structure classification, case study: Fars domain, Iran / Sahand Seraj in Geo-spatial Information Science, vol 25 n° 3 (October 2022)PermalinkDevelopment of a novel hybrid multi-boosting neural network model for spatial prediction of urban flood / Amid Darabi in Geocarto international, vol 37 n° 19 ([15/09/2022])PermalinkAssessing road accidents in spatial context via statistical and non-statistical approaches to detect road accident hotspot using GIS / Yegane Khosravi in Geodetski vestnik, vol 66 n° 3 (September - November 2022)PermalinkA boundary-based ground-point filtering method for photogrammetric point-cloud data / Seyed Mohammad Ayazi in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 9 (September 2022)PermalinkDetection of potential gold mineralization areas using MF-fuzzy approach on multispectral data / Tohid Nouri in Geocarto international, Vol 37 n° 17 ([20/08/2022])PermalinkThe influence of data density and integration on forest canopy cover mapping using Sentinel-1 and Sentinel-2 time series in Mediterranean oak forests / Vahid Nasiri in ISPRS International journal of geo-information, vol 11 n° 8 (August 2022)PermalinkA model development on GIS-driven data to predict temporal daily collision through integrating Discrete Wavelet Transform (DWT) and Artificial Neural Network (ANN) algorithms; case study: Tehran-Qazvin freeway / Reza Sanayeia in Geocarto international, vol 37 n° 14 ([20/07/2022])PermalinkSpatial modeling of migration using GIS-based multi-criteria decision analysis: A case study of Iran / Naeim Mijani in Transactions in GIS, vol 26 n° 2 (April 2022)PermalinkFlood monitoring by integration of remote sensing technique and multi-criteria decision making method / Hadi Farhadi in Computers & geosciences, vol 160 (March 2022)PermalinkMulti-parameter risk mapping of Qazvin aquifer by classic and fuzzy clustering techniques / Saman Javadi in Geocarto international, vol 37 n° 4 ([15/02/2022])PermalinkAbove-ground biomass estimation in a Mediterranean sparse coppice oak forest using Sentinel-2 data / Fardin Moradi in Annals of forest research, vol 65 n° 1 (January - June 2022)PermalinkEstimating aboveground biomass in dense Hyrcanian forests by the use of Sentinel-2 data / Fardin Moradi in Forests, vol 13 n° 1 (January 2022)PermalinkFlood susceptibility mapping using meta-heuristic algorithms / Alireza Arabameri in Geomatics, Natural Hazards and Risk, vol 13 (2022)PermalinkA GIS-based landslide susceptibility mapping and variable importance analysis using artificial intelligent training-based methods / Pengxiang Zhao in Remote sensing, vol 14 n° 1 (January-1 2022)PermalinkModeling of precipitable water vapor from GPS observations using machine learning and tomography methods / Mir Reza Ghaffari Razin in Advances in space research, vol 69 n° 7 (April 2022)PermalinkA comparative approach of support vector machine kernel functions for GIS-based landslide susceptibility mapping / Khalil Valizadeh Kamran in Applied geomatics, vol 13 n° 4 (December 2021)PermalinkIncorporating multi-criteria decision-making and fuzzy-value functions for flood susceptibility assessment / Ali Azareh in Geocarto international, vol 36 n° 20 ([01/12/2021])PermalinkParticle swarm optimization based water index (PSOWI) for mapping the water extents from satellite images / Mohammad Hossein Gamshadzaei in Geocarto international, vol 36 n° 20 ([01/12/2021])PermalinkMulti-sensor aboveground biomass estimation in the broadleaved hyrcanian forest of Iran / Ghasem Ronoud in Canadian journal of remote sensing, vol 47 n° 6 ([01/11/2021])PermalinkEstimating regional soil moisture with synergistic use of AMSR2 and MODIS images / Majid Rahimzadegan in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 9 (September 2021)PermalinkThree-dimensional building change detection using object-based image analysis (case study: Tehran) / Fatemeh Tabib Mahmoudi in Applied geomatics, vol 13 n° 3 (September 2021)PermalinkIdentifying urban neighborhoods with higher potential for social investment using GIS-FIS approach / Hossein Aghajani in Applied geomatics, vol 13 n° 1 (May 2021)PermalinkIntegrating a forward feature selection algorithm, random forest, and cellular automata to extrapolate urban growth in the Tehran-Karaj region of Iran / Hossein Shafizadeh-Moghadam in Computers, Environment and Urban Systems, vol 87 (May 2021)PermalinkDEM resolution influences on peak flow prediction: a comparison of two different based DEMs through various rescaling techniques / Ali H. Ahmed Suliman in Geocarto international, vol 36 n° 7 ([15/04/2021])PermalinkAnalysis of plot-level volume increment models developed from machine learning methods applied to an uneven-aged mixed forest / Seyedeh Kosar Hamidi in Annals of Forest Science, vol 78 n° 1 (March 2021)PermalinkUrban flood hazard mapping using machine learning models: GARP, RF, MaxEnt and NB / Mahya Norallahi in Natural Hazards, vol 106 n° 1 (March 2021)PermalinkIntegrating runoff map of a spatially distributed model and thematic layers for identifying potential rainwater harvesting suitability sites using GIS techniques / Hamid Karimi in Geocarto international, vol 36 n° 3 ([15/02/2021])PermalinkAn improved approach based on terrain-dependent mathematical models for georeferencing pushbroom satellite images / Behrooz Moradi in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 1 (January 2021)PermalinkImproving traffic sign recognition results in urban areas by overcoming the impact of scale and rotation / Roholah Yazdan in ISPRS Journal of photogrammetry and remote sensing, vol 171 (January 2021)PermalinkThe effect of different sampling schemes on estimation precision of snow water equivalent (SWE) using geostatistics techniques in a semi-arid region of Iran / Hojatolah Ganjkhanlo in Geocarto international, vol 35 n° 16 ([01/12/2020])PermalinkImproving drainage conditions of forest roads using the GIS and forest road simulator / Mehran Nasiri in Journal of forest science, vol 66 n° 9 (September 2020)PermalinkEstimation of tropospheric wet refractivity using tomography method and artificial neural networks in Iranian case study / Mir Reza Ghaffari Razin in GPS solutions, Vol 24 n° 3 (July 2020)PermalinkCrowdsource mapping of target buildings in hazard: the utilization of smartphone technologies and geographic services / Mohammad H. Vahidnia in Applied geomatics, vol 12 n° 1 (April 2020)PermalinkGeneration of digital terrain model for forest areas using a new particle swarm optimization on LiDAR data / Behnaz Bigdeli in Survey review, vol 52 n° 371 (March 2020)PermalinkAutomatic canola mapping using time series of Sentinel 2 images / Davoud Ashourloo in ISPRS Journal of photogrammetry and remote sensing, vol 156 (October 2019)PermalinkCalculating potential evapotranspiration and single crop coefficient based on energy balance equation using Landsat 8 and Sentinel-2 / Ali Mokhtari in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)PermalinkThe Iranian height datum offset from the GBVP solution and spirit-leveling/gravimetry data / Amir Ebadi in Journal of geodesy, vol 93 n° 8 (August 2019)PermalinkDesigning an integrated urban growth prediction model: a scenario-based approach for preserving scenic landscapes / Sepideh Saeidi in Geocarto international, vol 33 n° 12 (December 2018)PermalinkApplication of Landsat-8 and ASTER satellite remote sensing data for porphyry copper exploration: a case study from Shahr-e-Babak, Kerman, south of Iran / Morteza Safari in Geocarto international, vol 33 n° 11 (November 2018)PermalinkA novel approach to site selection: collaborative multi-criteria decision making through geo-social network (case study: public parking) / Zeinab Neisani Samani in ISPRS International journal of geo-information, vol 7 n° 3 (March 2018)PermalinkApplicability of generalized additive model in groundwater potential modelling and comparison its performance by bivariate statistical methods / Fatemeh Falah in Geocarto international, vol 32 n° 10 (October 2017)PermalinkMeasuring the effect of an ongoing urbanization process on biodiversity conservation suitability index : integrating scenario-based urban growth modelling with Conservation Assessment and Prioritization System (CAPS) / Mehdi Sheikh Goodarzi in Geocarto international, vol 32 n° 8 (August 2017)PermalinkPerformance evaluation of land change simulation models using landscape metrics / Sadeq Dezhkam in Geocarto international, vol 32 n° 6 (June 2017)PermalinkA comparison of two downscaling procedures to increase the spatial resolution of mapping actual evapotranspiration / Milad Mahour in ISPRS Journal of photogrammetry and remote sensing, vol 126 (April 2017)PermalinkDelineation 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)PermalinkModeling 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)PermalinkRelationship between landform classification and vegetation (case study: southwest of Fars province, Iran) / Marzieh Mokarram in Open geosciences, vol 8 n° 1 (January - July 2016)PermalinkEstimation of forest biomass using multivariate relevance vector regression / Alireza Sharifi in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 1 (January 2016)Permalink3D 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)PermalinkA multicriteria spatial decision support system for solving emergency service station location problems / Majid Esmaelian in International journal of geographical information science IJGIS, vol 29 n° 7 (July 2015)PermalinkThe decision task complexity and information acquisition strategies in GIS-MCDA / Mohammadreza Jelokhani-Niaraki in International journal of geographical information science IJGIS, vol 29 n° 2 (February 2015)PermalinkA morphological approach to predicting urban expansion / Jamal Jokar Arsanjani in Transactions in GIS, vol 18 n° 2 (April 2014)PermalinkSpatial modelling of site suitability assessment for hospitals using geographical information system-based multicriteria approach at Qazvin city, Iran / Saleh Abdulhahi in Geocarto international, vol 29 n° 1 - 2 (February - April 2014)PermalinkInSAR-derived coseismic deformation of the 2010 Southeastern Iran earthquake (M6.5) and its relationship with the tectonic background in the South of Lut Block / Tomokazu Kobayashi in Bulletin of the GeoSpatial Information authority of Japan, vol 60 (March 2013)Permalink