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Can ensemble techniques improve coral reef habitat classification accuracy using multispectral data? / Mohammad Shawkat Hossain in Geocarto international, vol 35 n° 11 ([01/08/2020])
[article]
Titre : Can ensemble techniques improve coral reef habitat classification accuracy using multispectral data? Type de document : Article/Communication Auteurs : Mohammad Shawkat Hossain, Auteur ; Aidy M. Muslim, Auteur ; Muhammad Izuan Nadzri, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 214 - 1232 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] biodiversité
[Termes IGN] carte bathymétrique
[Termes IGN] Chine, mer de
[Termes IGN] classification barycentrique
[Termes IGN] classification hypercube
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] distribution de Fisher
[Termes IGN] fond marin
[Termes IGN] image multibande
[Termes IGN] Malaisie
[Termes IGN] précision de la classification
[Termes IGN] récif corallien
[Termes IGN] réflectance spectraleRésumé : (auteur) Remote sensing has potential in studies of the benthic habitat and extracting the reflectance from the data of multispectral sensors, but traditional image classification techniques cannot provide coral habitat maps with adequate accuracy. This study tested five traditional and three ensemble classification techniques on QuickBird for mapping the benthic composition of coral reefs on the Lang Tengah Island (Malaysia). The common techniques, minimum distance, maximum likelihood, K-nearest neighbour, Fisher and parallelepiped techniques were compared with ensemble classifiers, such as majority voting (MV), simple averaging, and mode combination. The per-class accuracy of the habitat detection improved in the ensemble classifiers; in particular, the MV classifier achieved 95%, 65%, 75% and 95% accuracies for coral, sparse coral, coral rubble and sand, respectively. Ensembles increased the accuracy of the habitat mapping classification by 28%, relative to conventional techniques. Thus, the ensemble techniques can be preferred over the traditional for benthic habitat mapping. Numéro de notice : A2020-459 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1557263 Date de publication en ligne : 12/02/2019 En ligne : https://doi.org/10.1080/10106049.2018.1557263 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95566
in Geocarto international > vol 35 n° 11 [01/08/2020] . - pp 214 - 1232[article]Comparative study of different models for soil erosion and sediment yield in Pairi watershed, Chhattisgarh, India / Tarun Kumar in Geocarto international, vol 35 n° 11 ([01/08/2020])
[article]
Titre : Comparative study of different models for soil erosion and sediment yield in Pairi watershed, Chhattisgarh, India Type de document : Article/Communication Auteurs : Tarun Kumar, Auteur ; D. C. Jhariya, Auteur ; H.K. Pandey, Auteur Année de publication : 2020 Article en page(s) : pp 1245 - 1266 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse comparative
[Termes IGN] bassin hydrographique
[Termes IGN] érosion côtière
[Termes IGN] Inde
[Termes IGN] modèle RUSLE
[Termes IGN] occupation du sol
[Termes IGN] précipitation
[Termes IGN] sédiment
[Termes IGN] système d'information géographique
[Termes IGN] texture du sol
[Termes IGN] topographie
[Termes IGN] utilisation du solRésumé : (auteur) A Comparative Study of different models for assessment of soil erosion (Universal Soil Loss Equation and Revised Universal Soil Loss Equation) and sediment yield (Modify Universal Soil Loss Equation and Sediment delivery ratio) carried out in Pairi Watershed, Chhattisgarh, India. The main objective is to estimate the spatial pattern of annual soil erosion rate and sediment yield using Remote Sensing and GIS technique which are promising and cost-effective tools for mapping critical areas. To calculate the soil erosion and sediment yield different spatial data sets were utilized such as rainfall, soil texture, topography, land use land cover etc. Obtained result of soil erosion and sediment yield was validated using field check using Baronda CWC Observatory data. It is found that, RUSLE model for soil erosion and MUSLE model for sediment yield has been found to be most reliable for the study area. Numéro de notice : A2020-470 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1576779 Date de publication en ligne : 26/03/2019 En ligne : https://doi.org/10.1080/10106049.2019.1576779 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95567
in Geocarto international > vol 35 n° 11 [01/08/2020] . - pp 1245 - 1266[article]Conjugate ruptures and seismotectonic implications of the 2019 Mindanao earthquake sequence inferred from Sentinel-1 InSAR data / Bingquan Li in International journal of applied Earth observation and geoinformation, vol 90 (August 2020)
[article]
Titre : Conjugate ruptures and seismotectonic implications of the 2019 Mindanao earthquake sequence inferred from Sentinel-1 InSAR data Type de document : Article/Communication Auteurs : Bingquan Li, Auteur ; Yongsheng Li, Auteur ; Wenliang Jiang, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : n° 102127 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] déformation de la croute terrestre
[Termes IGN] faille géologique
[Termes IGN] filtre de Goldstein
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] loi de Coulomb
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] modèle numérique de surface
[Termes IGN] Philippines
[Termes IGN] séisme
[Termes IGN] séquence d'imagesRésumé : (auteur) In 2019, four strong earthquakes of Mw>6.4 occurred successively in Mindanao, Philippines. Based on the reports from the USGS and PHIVOLCS, these earthquakes were dominated by strike-slip ruptures. Whether these earthquakes are temporally and spatially related remained unknown. We characterized the coseismic displacement fields during the earthquake sequence using an InSAR technique with Sentinel-1 SAR data. The InSAR deformation measurements convincingly reveal that the four earthquakes produced distinct coseismic displacement patterns. We estimated the source parameters of the earthquakes with a two-step inversion strategy. The optimal model suggests that the earthquake sequence resulted from the reactivation of a conjugate fault structure that involves two nearly vertical left-lateral strike-slip faults and two high-angle right-lateral strike-slip faults. We calculated Coulomb stress changes from the earthquake sequence, suggesting that the previous strong earthquakes had significant stress-encouraging effects on the following events. The regional velocities based on the GPS analysis suggest that the formation of this conjugate structure is mainly due to the westward movement of the subducting Philippine Sea Plate. This earthquake sequence provides a seismotectonic background for subsequent strong earthquakes and helps to better understand the formation mechanisms and seismotectonic implications of conjugate structure rupturing. Numéro de notice : A2020-718 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article DOI : 10.1016/j.jag.2020.102127 Date de publication en ligne : 18/04/2020 En ligne : https://doi.org/10.1016/j.jag.2020.102127 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96293
in International journal of applied Earth observation and geoinformation > vol 90 (August 2020) . - n° 102127[article]Detecting abandoned farmland using harmonic analysis and machine learning / Heeyeun Yoon in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)
[article]
Titre : Detecting abandoned farmland using harmonic analysis and machine learning Type de document : Article/Communication Auteurs : Heeyeun Yoon, Auteur ; Soyoun Kim, Auteur Année de publication : 2020 Article en page(s) : pp 201 - 212 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse harmonique
[Termes IGN] apprentissage automatique
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] Corée du sud
[Termes IGN] gestion des ressources
[Termes IGN] inventaire
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] Normalized Difference Water Index
[Termes IGN] phénologie
[Termes IGN] production agricole
[Termes IGN] Soil Adjusted Vegetation Index
[Termes IGN] surface cultivéeRésumé : (auteur) It is critical to inventory abandoned farmland soon after it is generated, to better manage agricultural resources and to prevent negative consequences that would otherwise follow. This study aims to distinguish abandoned farmlands from active croplands—rice paddy and agricultural fields—by discerning the phenological trajectories over a short-term period of three years (Jan. 2016 to Dec. 2018) in Gwanyang City in South Korea. For Support Vector Machine (SVM) classification, we fully utilized parameters derived from harmonic analyses of the three vegetation indices (VIs: NDVI, NDWI, and SAVI) extracted from Sentinel-2A imagery. The harmonic analyses proved that higher-order sinusoid components produced better fitting to explain the trajectory of the VIs—the maximum adjusted was 95.23%—and the multiple VIs diversified the attributes for the classifications. Consequently, the higher-order harmonic components and the additional VIs increased the accuracy when used in SVM classification. The best performing classification was achieved with a composite of harmonic terms derived from the three VIs, yielding overall accuracy of 90.72%, Kappa index of 0.858, and user’s accuracy for abandoned farmland of 93.40%. The proposed method here would greatly improve the process of detecting abandoned farmland, despite a relatively short observation period, and enable a rapid response to the occurrence of abandonment. Numéro de notice : A2020-356 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.05.021 Date de publication en ligne : 16/06/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.05.021 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95243
in ISPRS Journal of photogrammetry and remote sensing > vol 166 (August 2020) . - pp 201 - 212[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2020081 RAB Revue Centre de documentation En réserve L003 Disponible 081-2020083 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2020082 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Development and application of a new mangrove vegetation index (MVI) for rapid and accurate mangrove mapping / Alvin B. Baloloy in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)
[article]
Titre : Development and application of a new mangrove vegetation index (MVI) for rapid and accurate mangrove mapping Type de document : Article/Communication Auteurs : Alvin B. Baloloy, Auteur ; Ariel C. Blanco, Auteur ; Raymund Rhommel StaAna, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 95 - 117 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse spectrale
[Termes IGN] Asie du sud-est
[Termes IGN] carte de la végétation
[Termes IGN] espèce exotique envahissante
[Termes IGN] image captée par drone
[Termes IGN] image Landsat-8
[Termes IGN] image proche infrarouge
[Termes IGN] image Sentinel-MSI
[Termes IGN] indice de végétation
[Termes IGN] mangrove
[Termes IGN] orthophotographie
[Termes IGN] Philippines
[Termes IGN] surveillance du littoralRésumé : (auteur) Advancement in Remote Sensing allows rapid mangrove mapping without the need for data-intensive methodologies, complex classifiers, and skill-dependent classification techniques. This study proposes a new index, the Mangrove Vegetation Index (MVI), to rapidly and accurately map mangroves extent from remotely-sensed imageries. The MVI utilizes three Sentinel-2 bands green, Near Infrared (NIR) and Shortwave Infrared (SWIR) in the form |NIR-Green|/|SWIR-Green| to discriminate the distinct greenness and moisture of mangroves from terrestrial vegetation and other land cover. Spectral band analysis shows that the |NIR-Green| part of MVI captures the differences of greenness between mangrove forests and terrestrial vegetation. The |SWIR-Green| part of the index expresses the distinct moisture of mangroves without the need for additional intertidal data and water indices. The MVI value increases with the increasing probability of a pixel being classified as mangroves. Eleven mangrove forests in the Philippines and one mangrove park in Japan were then mapped using MVI. Accuracy assessment was done using field inventory data and high-resolution drone orthophotos. MVI have successfully separated the mangroves from other cover especially terrestrial vegetation, with an overall index accuracy of 92%. The MVI was applied to Landsat 8 images using the equivalent bands to test the universality of the index. Comparable MVI mangrove maps were produced between Sentinel-2 and Landsat images, with an optimal minimum threshold of 4.5 and 4.6, respectively. MVI can effectively highlight the greenness and moisture information in mangroves as reflected by its moderate to high correlation value (r = 0.63 and 0.84, α = 0.05) with the Sentinel-derived chlorophyll-a (Ca) and canopy water (Cw) biophysical products. This study developed and implemented two automated platforms: an offline IDL-based ‘MVI Mapper’ and an online Google Earth Engine-based MVI mapping interface. The MVI implemented in Google Earth Engine was used in generating the latest mangrove extent map of the Philippines. Additionally, the application of MVI were tested to four additional mangrove forests in Southeast Asia: Thailand, Vietnam, Indonesia and Cambodia; and to selected mangroves forests in South America, Africa and Australia. Numéro de notice : A2020-354 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.06.001 Date de publication en ligne : 11/06/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.06.001 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95240
in ISPRS Journal of photogrammetry and remote sensing > vol 166 (August 2020) . - pp 95 - 117[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2020081 RAB Revue Centre de documentation En réserve L003 Disponible 081-2020083 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2020082 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Evaluation of single-frequency receivers for studying crustal deformation at the longitudinal Valley fault, eastern Taiwan / Horng-Yue Chen in Survey review, vol 52 n° 374 (August 2020)PermalinkSmall‐area patch‐merging method accounting for both local constraints and the overall area balance / Chengming Li in Transactions in GIS, Vol 24 n° 4 (August 2020)PermalinkTourism land use simulation for regional tourism planning using POIs and cellular automata / Hong Shi in Transactions in GIS, Vol 24 n° 4 (August 2020)PermalinkComplete and accurate data correction for seamless mosaicking of airborne hyperspectral images: A case study at a mining site in Inner Mongolia, China / Kun Tan in ISPRS Journal of photogrammetry and remote sensing, vol 165 (July 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)PermalinkLong time-series remote sensing analysis of the periodic cycle evolution of the inlets and ebb-tidal delta of Xincun Lagoon, Hainan Island, China / Huaguo Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 165 (July 2020)PermalinkRoles of horizontal and vertical tree canopy structure in mitigating daytime and nighttime urban heat island effects / Jike Chen in International journal of applied Earth observation and geoinformation, vol 89 (July 2020)PermalinkSimulating urban land use change by integrating a convolutional neural network with vector-based cellular automata / Yaqian Zhai in International journal of geographical information science IJGIS, vol 34 n° 7 (July 2020)PermalinkSpatiotemporally Varying Coefficients (STVC) model: a Bayesian local regression to detect spatial and temporal nonstationarity in variables relationships / Chao Song in Annals of GIS, vol 26 n° 3 (July 2020)PermalinkTemporal and spatial variations of monsoonal upwelling along the South West and East coasts of India / Shailee Patel in Marine geodesy, Vol 43 n° 4 (July 2020)Permalink