Centre de documentation
scientifique

Challenges and limitations of earthquake-induced building damage mapping techniques using remote sensing images : A systematic review / Sahar S. Matin in Geocarto international, Vol 37 n° 21 ([01/10/2022])  

Public [article]  inGeocarto international > Vol 37 n° 21 [01/10/2022] . - pp 6186 - 6212 Titre : Challenges and limitations of earthquake-induced building damage mapping techniques using remote sensing images : A systematic review Type de document : Article/Communication Auteurs : Sahar S. Matin, Auteur ; Biswajeet Pradhan, Auteur Année de publication : 2022 Article en page(s) : pp 6186 - 6212 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] apprentissage profond [Termes IGN] cartographie thématique [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] déformation d'édifice [Termes IGN] détection de changement [Termes IGN] dommage matériel [Termes IGN] données lidar [Termes IGN] image optique [Termes IGN] image radar moirée [Termes IGN] secours d'urgence [Termes IGN] séisme Résumé : (auteur) Assessing the extent and level of building damages is crucial to support post-earthquake rescue and relief activities. There is a large body of literature proposing novel frameworks for automating earthquake-induced building damage mapping using high-resolution remote sensing images. Yet, its deployment in real-world scenarios is largely limited to the manual interpretation of images. Although manual interpretation is costly and labor-intensive, it is preferred over automatic and semi-automatic building damage mapping frameworks such as machine learning and deep learning because of its reliability. Therefore, this review paper explores various automatic and semi-automatic building damage mapping techniques with a quest to understand the pros and cons of different methodologies to narrow the gap between research and practice. Further, the research gaps and opportunities are identified for the future development of real-world scenarios earthquake-induced building damage mapping. This review can serve as a guideline for researchers, decision-makers, and practitioners in the emergency management service domain. Numéro de notice : A2022-719 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2021.1933213 Date de publication en ligne : 07/06/2021 En ligne : https://doi.org/10.1080/10106049.2021.1933213 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101651 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-2022211	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Integrating multilayer perceptron neural nets with hybrid ensemble classifiers for deforestation probability assessment in Eastern India / Sunil Saha in Geomatics, Natural Hazards and Risk, vol 12 n° 1 (2021)  

Public [article]  inGeomatics, Natural Hazards and Risk > vol 12 n° 1 (2021) . - pp 29 - 62 Titre : Integrating multilayer perceptron neural nets with hybrid ensemble classifiers for deforestation probability assessment in Eastern India Type de document : Article/Communication Auteurs : Sunil Saha, Auteur ; Gopal Chandra, Auteur ; Biswajeet Pradhan, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 29 - 62 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] apprentissage automatique [Termes IGN] changement d'occupation du sol [Termes IGN] classification hybride [Termes IGN] classification par Perceptron multicouche [Termes IGN] déboisement [Termes IGN] ensachage [Termes IGN] Inde [Termes IGN] modèle de simulation [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] Rotation Forest classification [Termes IGN] système d'information géographique Résumé : (auteur) The rapid expansion of human settlement, agricultural land and roads because of population growth in several regions of the world has contributed to the depletion of forest land. In this study, novel ensemble intelligent approaches using bagging, dagging and rotation forest (RTF) as meta classifiers of multilayer perceptron (MLP) were used to predict spatial deforestation probability (DP) in Gumani Basin, India. The success rate and correctness of prediction of the ensemble models were compared with MLP. A total of 1000 deforested pixels and 14 deforestation determining factors (DDFs) were used. The ensemble models were trained using 70% of the deforested pixels and validated with the remaining 30%. DDFs were chosen by applying the information gain ratio and Relief-F test methods. Distance to settlement, population growth and distance to roads were the most important factors. The results of DP modelling demonstrated that nearly 16.82%–12.64% of the basin had very high DP. All four models created DP maps with reasonable prediction accuracy and goodness of fit, but the best map was produced by MLP-bagging. The accuracy of the MLP neural net model was increased 2-3% after ensemble with the hybrid meta classifiers (RTF, bagging and dagging). The proposed method could be used for deforestation prediction in other areas having similar geo-environmental conditions. Furthermore, the findings might be used as a basis for future research and could help planners in forest management. Numéro de notice : A2021-106 Affiliation des auteurs : non IGN Thématique : FORET/INFORMATIQUE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/19475705.2020.1860139 Date de publication en ligne : 22/12/2020 En ligne : https://doi.org/10.1080/19475705.2020.1860139 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96903 [article]

Data fusion technique using wavelet transform and Taguchi methods for automatic landslide detection from airborne laser scanning data and QuickBird satellite imagery / Biswajeet Pradhan in IEEE Transactions on geoscience and remote sensing, vol 54 n° 3 (March 2016)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 54 n° 3 (March 2016) . - pp 1610 - 1622 Titre : Data fusion technique using wavelet transform and Taguchi methods for automatic landslide detection from airborne laser scanning data and QuickBird satellite imagery Type de document : Article/Communication Auteurs : Biswajeet Pradhan, Auteur ; Mustafa Neamah Jebur, Auteur ; Helmi Zulhaidi Mohd Shafri, Auteur ; Mahyat Shafapour Tehrany, Auteur Année de publication : 2016 Article en page(s) : pp 1610 - 1622 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] carte thématique [Termes IGN] classification dirigée [Termes IGN] données lidar [Termes IGN] effondrement de terrain [Termes IGN] fusion d'images [Termes IGN] image Quickbird [Termes IGN] Malaisie [Termes IGN] précision des données [Termes IGN] transformation en ondelettes Résumé : (Auteur) Landslide mapping is indispensable for efficient land use management and planning. Landslide inventory maps must be produced for various purposes, such as to record the landslide magnitude in an area and to examine the distribution, types, and forms of slope failures. The use of this information enables the study of landslide susceptibility, hazard, and risk, as well as of the evolution of landscapes affected by landslides. In tropical countries, precipitation during the monsoon season triggers hundreds of landslides in mountainous regions. The preparation of a landslide inventory in such regions is a challenging task because of rapid vegetation growth. Thus, enhancing the proficiency of landslide mapping using remote sensing skills is a vital task. Various techniques have been examined by researchers. This study uses a robust data fusion technique that integrates high-resolution airborne laser scanning data (LiDAR) with high-resolution QuickBird satellite imagery (2.6-m spatial resolution) to identify landslide locations in Bukit Antarabangsa, Ulu Klang, Malaysia. This idea is applied for the first time to identify landslide locations in an urban environment in tropical areas. A wavelet transform technique was employed to achieve data fusion between LiDAR and QuickBird imagery. An object-oriented classification method was used to differentiate the landslide locations from other land use/covers. The Taguchi technique was employed to optimize the segmentation parameters, whereas the rule-based technique was used for object-based classification. In addition, to assess the impact of fusion in classification and landslide analysis, the rule-based classification method was also applied on original QuickBird data which have not been fused. Landslide locations were detected, and the confusion matrix was used to examine the proficiency and reliability of the results. The achieved overall accuracy and kappa coefficient were 90.06% and 0.84, respectively, for fused data. Mor- over, the acquired producer and user accuracies for landslide class were 95.86% and 95.32%, respectively. Results of the accuracy assessment for QuickBird data before fusion showed 65.65% and 0.59 for overall accuracy and kappa coefficient, respectively. It revealed that fusion made a significant improvement in classification results. The direction of mass movement was recognized by overlaying the final landslide classification map with LiDAR-derived slope and aspect factors. Results from the tested site in a hilly area showed that the proposed method is easy to implement, accurate, and appropriate for landslide mapping in a tropical country, such as Malaysia. Numéro de notice : A2016-127 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2484325 En ligne : http://dx.doi.org/10.1109/TGRS.2015.2484325 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80008 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
065-2016031	SL	Revue	Centre de documentation	Revues en salle	Disponible

A novel approach for predicting the spatial patterns of urban expansion by combining the chi-squared automatic integration detection decision tree, Markov chain and cellular automata models in GIS / Abubrakr A. A. Al Sharif in Geocarto international, vol 30 n° 7 - 8 (August - September 2015)  

Public [article]  inGeocarto international > vol 30 n° 7 - 8 (August - September 2015) . - pp 858 - 881 Titre : A novel approach for predicting the spatial patterns of urban expansion by combining the chi-squared automatic integration detection decision tree, Markov chain and cellular automata models in GIS Type de document : Article/Communication Auteurs : Abubrakr A. A. Al Sharif, Auteur ; Biswajeet Pradhan, Auteur Année de publication : 2015 Article en page(s) : pp 858 - 881 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] arbre de décision [Termes IGN] automate cellulaire [Termes IGN] croissance urbaine [Termes IGN] données spatiotemporelles [Termes IGN] étalement urbain [Termes IGN] khi carré [Termes IGN] modèle de simulation [Termes IGN] modèle dynamique [Termes IGN] modèle stochastique [Termes IGN] surveillance de l'urbanisation [Termes IGN] système d'information géographique [Termes IGN] Tripoli (Libye ; ville) [Termes IGN] urbanisation Résumé : (Auteur) Urban development is a continuous and dynamic spatio-temporal phenomenon associated with economic developments and growing populations. To understand urban expansion, it is important to establish models that can simulate urbanization process and its deriving factors behaviours, monitor deriving forces interactions and predict spatio-temporally probable future urban growth patterns explicitly. In this research, therefore, we presented a hybrid model that integrates the chi-squared automatic integration detection decision tree (CHAID-DT), Markov chain (MC) and cellular automata (CA) models to analyse, simulate and predict future urban expansions in Tripoli, Libya in 2020 and 2025. First, CHAID-DT model was applied to investigate the contributions of urban factors to the expansion process, to explore their interactions and to provide future urban probability map; second, MC model was employed to estimate the future demand of urban land; third, CA model was used to allocate estimated urban land quantity on the probability map to present future projected land use map. Three satellite images of the study area were obtained from the periods of 1984, 2002 and 2010 to extract land use maps and urban expansion data. We validated the model with two methods, namely, receiver operating characteristic and the kappa statistic index of agreement. Results confirmed that the proposed hybrid model could be employed in urban expansion modelling. The applied hybrid model overcame the individual shortcomings of each model and explicitly described urban expansion dynamics, as well as the spatio-temporal patterns involved. Numéro de notice : A2015-504 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2014.997308 Date de publication en ligne : 10/02/2015 En ligne : http://www.tandfonline.com/doi/full/10.1080/10106049.2014.997308 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77421 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-2015041	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Regional gold potential mapping in Kelantan (Malaysia) using probabilistic based models and GIS / Suhaimizi Yusoff in Open geosciences, vol 7 n° 1 (January 2015)  

Public [article]  inOpen geosciences > vol 7 n° 1 (January 2015) . - pp Titre : Regional gold potential mapping in Kelantan (Malaysia) using probabilistic based models and GIS Type de document : Article/Communication Auteurs : Suhaimizi Yusoff, Auteur ; Biswajeet Pradhan, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] carte thématique [Termes IGN] données géologiques [Termes IGN] gisement [Termes IGN] Malaisie [Termes IGN] modèle stochastique [Termes IGN] or [Termes IGN] prédiction Résumé : (auteur) The aim of this study is to test and compare two probabilistic based models (frequency ratio and weightsof- evidence) with regard to regional gold potential mapping at Kelantan, Malaysia. Until now these models have not been used for the purpose of mapping gold potential areas in Malaysia. This study analyzed the spatial relationship between gold deposits and geological factors such as lithology, faults, geochemical and geophysical data in geographical information system (GIS) software. About eight (8) gold deposits and five (5) related factors are identified and quantified for their spatial relationships. Then, all factors were combined to generate a predictive gold potential map. The predictive maps were then validated by comparing them with known gold deposits using receiver operating characteristics (ROC) and “area under the curve” (AUC) graphs. The results of validation showed accuracies of 80% for the frequency ratio and 74% for the weightsof- evidence model, respectively. The results demonstrated the usefulness of frequency ratio and weights-of-evidence modeling techniques in mineral exploration work to discover unknown gold deposits in Kelantan, Malaysia. Numéro de notice : A2015-441 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1515/geo-2015-0012 En ligne : https://doi.org/10.1515/geo-2015-0012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77043 [article]

Per-pixel and object-oriented classification methods for mapping urban land cover extraction using SPOT 5 imagery / Mustafa Neamah Jebur in Geocarto international, vol 29 n° 7 - 8 (November - December 2014)  

Permalink

Fusion of airborne LiDAR with multispectral SPOT 5 image for enhancement of feature extraction using dempster–shafer theory / Vahideh Saeidi in IEEE Transactions on geoscience and remote sensing, vol 52 n° 10 tome 1 (October 2014)  

Permalink

Advanced differential interferometry synthetic aperture radar techniques for deformation monitoring: a review on sensors and recent research development / O. Idrees Mohammed in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)  

Permalink

A rule-based parameter aided with object-based classification approach for extraction of building and roads from WorldView-2 images / Zahra Ziaei in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)  

Permalink

Functional relation of land surface albedo with climatological variables: a review on remote sensing techniques and recent research developments / S. A. Salleh in Geocarto international, vol 29 n° 1 - 2 (February - April 2014)  

Permalink

Spatial 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)  

Permalink