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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]

Geospatial analysis of September, 2019 floods in the lower gangetic plains of Bihar using multi-temporal satellites and river gauge data / C.M. Bhatt in Geomatics, Natural Hazards and Risk, vol 12 n° 1 (2021)  

Public [article]  inGeomatics, Natural Hazards and Risk > vol 12 n° 1 (2021) . - pp 84 - 102 Titre : Geospatial analysis of September, 2019 floods in the lower gangetic plains of Bihar using multi-temporal satellites and river gauge data Type de document : Article/Communication Auteurs : C.M. Bhatt, Auteur ; Amitesh Gupta, Auteur ; Arijit Roy, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 84 - 102 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] cartographie des risques [Termes IGN] crue [Termes IGN] données spatiotemporelles [Termes IGN] Gange (fleuve) [Termes IGN] humidité du sol [Termes IGN] image Aqua-AMSR [Termes IGN] image Aqua-MODIS [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] image Terra-MODIS [Termes IGN] Inde [Termes IGN] inondation [Termes IGN] précipitation Résumé : (auteur) During late September, 2019 Bihar was struggling with severe flooding problem, which otherwise is marked as a period of flood recession due to withdrawal of south-east monsoons. The present study assess the flood situation using Sentinel-1 SAR images and complements the understanding about the flood event using long term (2000-18) multi-temporal space based flood sensitive proxy indicators like precipitation (GPM), soil moisture (AMSR-2), vegetation condition (MODIS) together with ground based river gauge (CWC) data. The study reveals that in 2019 during the 39th week of the year (late September) the central and eastern parts of Bihar witnessed heavy precipitation (176 percent higher than average), leading to enhanced soil moisture build up (19 percent higher than average) and consequently triggering severe flooding. River Ganga was observed to be flowing above danger level for almost two weeks. Due to the prolonged submergence by floodwaters a significant drop was observed in the NDVI and EVI values of about 13.7 and 11.1 percent respectively from the normal. About 8.36 lakh ha area was observed to be inundated, impacting about 9.26 million population. Patna followed by Bhagalpur were the two worst affected districts with almost 30% and 36% of districts geographical area being flooded. Numéro de notice : A2021-107 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/19475705.2020.1861113 Date de publication en ligne : 24/12/2020 En ligne : https://doi.org/10.1080/19475705.2020.1861113 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96904 [article]

Geomorphic analysis of Xiadian buried fault zone in Eastern Beijing plain based on SPOT image and unmanned aerial vehicle (UAV) data / Yanping Wang in Geomatics, Natural Hazards and Risk, vol 12 n° 1 (2021)  

Public [article]  inGeomatics, Natural Hazards and Risk > vol 12 n° 1 (2021) . - pp 261 - 278 Titre : Geomorphic analysis of Xiadian buried fault zone in Eastern Beijing plain based on SPOT image and unmanned aerial vehicle (UAV) data Type de document : Article/Communication Auteurs : Yanping Wang, Auteur ; Pinliang Dong, Auteur ; Yueqin Zhu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 261 - 278 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] auscultation topographique [Termes IGN] déformation de la croute terrestre [Termes IGN] données de terrain [Termes IGN] effondrement de terrain [Termes IGN] faille géologique [Termes IGN] géomorphologie locale [Termes IGN] image captée par drone [Termes IGN] image SPOT 5 [Termes IGN] MNS SRTM [Termes IGN] modèle numérique de surface [Termes IGN] Pékin (Chine) [Termes IGN] réseau de drainage [Termes IGN] zone à risque Résumé : (auteur) This study presents geomorphic analysis of Xiadian buried fault in eastern Beijing plain (China), based on the analysis of a Satellite Pour l’Observation de la Terre (SPOT-5) image, a high-resolution digital elevation model (DEM) derived from an unmanned aerial vehicle (UAV) system, SRTM DEM and field investigation. Interpretations of the SPOT-5 image show that the pits always distribute between fault scarp segments or shallow grooves. The geomorphic features near the fault show echelon arrangements caused by dextral strike-slip activities of the fault. Based on this, the characteristics of stress field in this area have been clearly inferred. At centimeter-level accuracy, UAV-derived DEM profiles can clearly show micro tectonic landforms such as fault scarps, shallow grooves, steep slopes, and pits. Combined with previous research and field measurements, the evolution rates in length and height of the fault scarps are analysed. Furthermore, the deflection analysis of the drainage system also shows the characteristics of the continuous strike slip activity of the Xiadian fault. The study can provide valuable insight into geomorphic analysis of buried and semi-buried active faults in plain areas with increasingly frequent human activities. Numéro de notice : A2021-108 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/19475705.2020.1870168 Date de publication en ligne : 19/01/2021 En ligne : https://doi.org/10.1080/19475705.2020.1870168 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96905 [article]

Dynamic mechanism of blown sand hazard formation at the Jieqiong section of the Lhasa–Shigatse railway / Shengbo Xie in Geomatics, Natural Hazards and Risk, vol 12 n° 1 (2021)  

Public [article]  inGeomatics, Natural Hazards and Risk > vol 12 n° 1 (2021) . - pp 154 - 166 Titre : Dynamic mechanism of blown sand hazard formation at the Jieqiong section of the Lhasa–Shigatse railway Type de document : Article/Communication Auteurs : Shengbo Xie, Auteur ; Jianjun Qu, Auteur ; Yingjun Pang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 154 - 166 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] météorologie locale [Termes IGN] modèle dynamique [Termes IGN] prévention des risques [Termes IGN] risque naturel [Termes IGN] sable [Termes IGN] Tibet [Termes IGN] variation saisonnière [Termes IGN] vent de sable [Termes IGN] vitesse [Termes IGN] voie ferrée Résumé : (auteur) Blown sand hazards at the Jieqiong section of the Lhasa–Shigatse railway are severe, and their formation mechanism is unclear. Moreover, sand prevention and control work cannot be carried out. Therefore, the dynamic mechanism of blown sand at the Jieqiong section of the Lhasa–Shigatse Railway was investigated by field observation, laboratory analysis, and calculation. Results show that the yearly sand–moving wind at the Jieqiong section commonly originates from the SW direction. The yearly resultant drift direction and the yearly resultant angle of the maximum possible sand transport quantity are NE direction. The angle between railway trend and sand transport direction is 5°–30°. During dry season, sand materials are blown up by the wind, forming wind–sand flow and movement to the NE direction, at which they are blocked by the railway roadbed. Consequently, accumulation occurs and causes serious damage. Strong wind and dryness are synchronous within a season. The directions of sand source and prevailing wind are consistent, thereby aggravating the blown sand dynamic further. The present results provide a reference for controlling sand hazards in the locale. Numéro de notice : A2021-109 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/19475705.2020.1863268 Date de publication en ligne : 28/12/2020 En ligne : https://doi.org/10.1080/19475705.2020.1863268 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96906 [article]