Descripteur
Documents disponibles dans cette catégorie (1446)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Long-term soil moisture content estimation using satellite and climate data in agricultural area of Mongolia / Enkhjargal Natsagdorj in Geocarto international, vol 34 n° 7 ([01/06/2019])
[article]
Titre : Long-term soil moisture content estimation using satellite and climate data in agricultural area of Mongolia Type de document : Article/Communication Auteurs : Enkhjargal Natsagdorj, Auteur ; Tsolmon Renchin, Auteur ; Philippe De Maeyer, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 722 - 734 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] données météorologiques
[Termes IGN] image Aqua-MODIS
[Termes IGN] image SPOT-Végétation
[Termes IGN] image Terra-MODIS
[Termes IGN] Mongolie
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] surface cultivée
[Termes IGN] teneur en eau de la végétation
[Termes IGN] variation temporelleRésumé : (auteur) The purpose of this study is to estimate long-term SMC and find its relation with soil moisture (SM) of climate station in different depths and NDVI for the growing season. The study area is located in agricultural regions in the North of Mongolia. The Pearson’s correlation methodology was used in this study. We used MODIS and SPOT satellite data and 14 years data for precipitation, temperature and SMC of 38 climate stations. The estimated SMC from this methodology were compared with SM from climate data and NDVI. The estimated SMC was compared with SM of climate stations at a 10-cm depth (r2 = 0.58) and at a 50-cm depth (r2 = 0.38), respectively. From the analysis, it can be seen that the previous month’s SMC affects vegetation growth of the following month, especially from May to August. The methodology can be an advantageous indicator for taking further environmental analysis in the region. Numéro de notice : A2019-513 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1434686 Date de publication en ligne : 08/03/2018 En ligne : https://doi.org/10.1080/10106049.2018.1434686 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93822
in Geocarto international > vol 34 n° 7 [01/06/2019] . - pp 722 - 734[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 059-2019071 RAB Livre Centre de documentation En réserve L003 Disponible A new stochastic simulation algorithm for image-based classification : Feature-space indicator simulation / Qing Wang in ISPRS Journal of photogrammetry and remote sensing, vol 152 (June 2019)
[article]
Titre : A new stochastic simulation algorithm for image-based classification : Feature-space indicator simulation Type de document : Article/Communication Auteurs : Qing Wang, Auteur ; Hua Sun, Auteur ; Ruopu Li, Auteur ; Guangxing Wang, Auteur Année de publication : 2019 Article en page(s) : pp 145 - 165 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] forêt
[Termes IGN] géostatistique
[Termes IGN] image Landsat-OLI
[Termes IGN] image SPOT 5
[Termes IGN] Mongolie intérieure (Chine)
[Termes IGN] occupation du sol
[Termes IGN] précision de la classification
[Termes IGN] utilisation du sol
[Termes IGN] variogrammeRésumé : (Auteur) Traditional parametric methods for classification of land use and land cover (LULC) types using remote sensing imagery assume a global distribution model and fail to consider local variation of categorical variables. Differently, non-parametric methods do not make any statistical assumptions but are typically sensitive to the sample sizes of training sample data that usually require a high cost to collect in the field. Geostatistical classifiers, such as indicator kriging and simulation, are local variability-based methods that exhibit great potential for image-based classification of LULC types. However, variogram models required are highly sensitive to the spatial configuration of training samples as well as sample size given a study area. Moreover, when a large number of spectral variables are considered into kriging systems, modeling the variograms and cross-variograms would be problematic. To circumvent these issues, this study extended the geostatistical methods from a 2-dimensional geographic space to a m-dimensional image feature space to derive feature-space indicator variograms (FSIVs). Moreover, a novel stochastic simulation classification algorithm, Feature-Space Indicator Simulation (FSIS), was proposed and examined for classification of LULC types in Duolun County located in Inner Mongolia and in Huang-Feng-Qiao (HFQ) forest farm, Hunan of China. In Duolun, six LULC types were involved and in HFQ a complicated forest landscape consisting of nine forest types plus water, built-up area, and agricultural/bare soil, was classified. The classification results of FSIS were compared with another feature-space geostatistical classifier – feature-space indicator kriging (FSIK), a traditional parametric method – maximum likelihood (ML), a widely used nonparametric method – support vector machine (SVM), and a recently popular method – random forest (RF). The results showed that compared with ML, SVM and RF, in both study areas FSIS statistically significantly increased the accuracy of the classifications by 10.0–29.9% for percentage correct and 19.0–47.6% for Kappa statistic. Compared with FSIK, FSIS also improved the classification accuracy but the accuracy increases were relatively smaller with the percentages correct of 3.5% and 7.6% and the Kappa values of 4.6% and 8.6% for Duolun and HFQ, respectively. Moreover, FSIS led to the spatial uncertainties of the classification estimates as the quality measure of the estimates. In addition, the results also demonstrated that FSIVs were sensitive to the within-class heterogeneity but not very much to the size of training samples. Overall, FSIS exhibited the greater potential to improve the classification accuracy of LULC and forest types using remote sensing image. Numéro de notice : A2019-457 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.04.011 Date de publication en ligne : 25/04/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.04.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92871
in ISPRS Journal of photogrammetry and remote sensing > vol 152 (June 2019) . - pp 145 - 165[article]Réservation
Réserver ce documentExemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2019061 RAB Revue Centre de documentation En réserve L003 Disponible 081-2019063 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2019062 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Ability of GPS PPP in 2D deformation analysis with respect to GPS network solution / C. Aydin in Survey review, vol 51 n° 366 (May 2019)
[article]
Titre : Ability of GPS PPP in 2D deformation analysis with respect to GPS network solution Type de document : Article/Communication Auteurs : C. Aydin, Auteur ; S. O. Uygur, Auteur ; S. Çetin, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 199 - 212 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] analyse comparative
[Termes IGN] Bernese
[Termes IGN] déformation de la croute terrestre
[Termes IGN] données GPS
[Termes IGN] positionnement ponctuel précis
[Termes IGN] station de référence
[Termes IGN] surveillance géologique
[Termes IGN] TurquieRésumé : (Auteur) GNSS networks play an important role in monitoring the displacements, movements and deformations of the Earth’s crust and engineering buildings. In this study, we examine how GPS Precise Point Positioning (PPP) is able to determine the horizontal deformations with respect to the GPS network solution. For this purpose, 7 days data of 12 Continuously Operating Reference Stations (CORS) in Turkey (CORS-TR), located in the western part of Turkey, are considered. The Bernese (v5.2)-derived coordinates over 7 days and the ones from four free online PPP services (CSRS, GAPS, APPS, Magic-PPP) are compared using the Bursa-Wolf coordinate transformation model. The errors from these transformations are used to define the RMS values of the PPP solutions in the local coordinate system. These values are relative to the GPS network solution. This fact leads to analysing how the PPP solutions are able to determine the horizontal deformations with respect to the network solution. From many experiments, in which the displacements belonging to the PPP solutions are simulated relative to the network solution, it has been shown that several ppm extensions or contractions may be determined using the free online PPP services. Therefore, we conclude that the online PPP services studied here may be used in 2D deformation studies as an alternative to the GPS network solutions. Numéro de notice : A2019-192 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2017.1415664 Date de publication en ligne : 29/12/2017 En ligne : https://doi.org/10.1080/00396265.2017.1415664 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92638
in Survey review > vol 51 n° 366 (May 2019) . - pp 199 - 212[article]Estimation of the forest stand mean height and aboveground biomass in Northeast China using SAR Sentinel-1B, multispectral Sentinel-2A, and DEM imagery / Yanan Liu in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)
[article]
Titre : Estimation of the forest stand mean height and aboveground biomass in Northeast China using SAR Sentinel-1B, multispectral Sentinel-2A, and DEM imagery Type de document : Article/Communication Auteurs : Yanan Liu, Auteur ; Weishu Gong, Auteur ; Yanqiu Xing, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 277 - 289 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] biomasse aérienne
[Termes IGN] biomasse forestière
[Termes IGN] Chine
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] hauteur des arbres
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] modèle numérique de surface
[Termes IGN] polarisationRésumé : (Auteur) Accurate mapping the forest stand mean height (FSMH) and aboveground biomass (AGB) with a high spatial resolution are important for monitoring carbon stocks on Earth and the variability and trends of terrestrial carbon fluxes. The recently launched Sentinel-1 (SAR) and Sentinel-2 (multispectral) missions offers a new opportunity to map FSMH and AGB. Here we present a methodological framework to map the FSMH and AGB at a resolution of 10 m in Yichun, Northeast China, by integrating field plots, Sentinel imagery, topographic data, and national geographical conditions monitoring data. First, a spatial continuous FSMH product was retrieved using an empirical model, which adopts the backscattering of SAR Sentinel-1B and the fraction of vegetation cover (FVC) variable from multispectral Sentinel-2A imagery. Subsequently, three AGB estimation models were developed for different forest types to link the field measurements to the FSMH, biophysical variables, spectral vegetation index, and topographic variables using the random forest algorithm. The mapping results show that the FSMH estimated using SAR backscatter values from VH polarization is more robust and accurate than that based on VV polarization. Furthermore, the three AGB estimation models based on three different forest types perform better than the model built by grouping all forest types together. The determination coefficient (R2) and root-mean-squared error (RMSE) range from 0.69 to 0.74 and 23.38 Mg/ha to 24.21 Mg/ha, respectively. Overall, our study demonstrates that the proposed methodological framework can be used to map the FSMH and AGB products at a high spatial resolution utilizing freely accessible Sentinel-1 SAR and Sentinel-2 multispectral imagery. Numéro de notice : A2019-211 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.03.016 Date de publication en ligne : 30/03/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.03.016 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92677
in ISPRS Journal of photogrammetry and remote sensing > vol 151 (May 2019) . - pp 277 - 289[article]Réservation
Réserver ce documentExemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2019051 RAB Revue Centre de documentation En réserve L003 Disponible 081-2019053 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2019052 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt A model for phased evacuations for disasters with spatio-temporal randomness / Menghui Li in International journal of geographical information science IJGIS, Vol 33 n° 5-6 (May - June 2019)
[article]
Titre : A model for phased evacuations for disasters with spatio-temporal randomness Type de document : Article/Communication Auteurs : Menghui Li, Auteur ; jinliang Xu, Auteur ; Jin Li, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 922 - 944 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] Chine
[Termes IGN] protection civile
[Termes IGN] réseau routier
[Termes IGN] secours d'urgence
[Termes IGN] zone à risque
[Termes IGN] zone sinistréeRésumé : (Auteur) This research presents an operable zoning approach for phased evacuations adapted to disasters with spatio-temporal randomness. As a criterion for prioritizing evacuation order, evacuation risk is formulated by taking into consideration the estimated residual evacuation horizon associated with the characteristics of the disaster, the estimated time-dependent capacities of outbound lanes related to network supply, and the time-dependent evacuation demand of an evacuation unit. The modeling of the subzone determined for phased evacuation is based on rescue demand, the characteristics of the disaster, and network supply, and is labeled as a high-risk evacuation zone (HEZ). The range of HEZ features a time-evolving pattern in accordance with phased evacuation. The zone partition paradigm can be seamlessly applied to different types of disasters, especially those with high spatio-temporal randomness. It also provides a generalizable approach for subzone partitioning in phased evacuation by minimizing evacuation risk. The proposed approach is examined on numerical experiments through the road network of Xi’an, China, the results of which highlight its strength in increased adaptability to the dynamics of disaster impact and improved performance in evacuation operation. Numéro de notice : A2019-441 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 13658816.2018.1564315 Date de publication en ligne : 28/01/2019 En ligne : https://doi.org/10.1080/13658816.2018.1564315 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92775
in International journal of geographical information science IJGIS > Vol 33 n° 5-6 (May - June 2019) . - pp 922 - 944[article]Réservation
Réserver ce documentExemplaires(2)
Code-barres Cote Support Localisation Section Disponibilité 079-2019051 RAB Revue Centre de documentation En réserve L003 Disponible 079-2019052 RAB Revue Centre de documentation En réserve L003 Disponible Towards new applications of underwater photogrammetry for investigating coral reef morphology and habitat complexity in the Myeik Archipelago, Myanmar / Martina Anelli in Geocarto international, vol 34 n° 5 ([01/05/2019])PermalinkCartographie de l’aléa érosif dans le bassin sud du Litani-Liban / Hussein El Hage Hassan in Revue internationale de géomatique, vol 29 n° 2 (avril - juin 2019)PermalinkGeographic Knowledge Graph (GeoKG): A formalized geographic knowledge representation / Shu Wang in ISPRS International journal of geo-information, vol 8 n° 4 (April 2019)PermalinkMultilane roads extracted from the OpenStreetMap urban road network using random forests / Yongyang Xu in Transactions in GIS, vol 23 n° 2 (April 2019)PermalinkDiscrimination and classification of mangrove forests using EO-1 Hyperion data : a case study of Indian Sundarbans / Tanumi Kumar in Geocarto international, vol 34 n° 4 ([15/03/2019])PermalinkAnalysis of ocean tide loading displacements by GPS kinematic precise point positioning: a case study at the China coastal site SHAO / H. Zhao in Survey review, vol 51 n° 365 (March 2019)PermalinkLarge-scale patterns in forest growth rates are mainly driven by climatic variables and stand characteristics / Hao Zhang in Forest ecology and management, vol 435 (1 March 2019)PermalinkA methodology with a distributed algorithm for large-scale trajectory distribution prediction / QiuLei Guo in International journal of geographical information science IJGIS, Vol 33 n° 3-4 (March - April 2019)PermalinkSEH-SDB : a semantically enriched historical spatial database for documentation and preservation of monumental heritage based on CityGML / Reda Yaagoubi in Applied geomatics, vol 11 n° 1 (March 2019)PermalinkAn automated and optimized approach for online spatial biodiversity model: a case study of OGC web processing service / Hariom Singh in Geocarto international, vol 34 n° 2 ([01/02/2019])PermalinkMonitoring suspended particle matter using GOCI satellite data after the Tohoku (Japan) tsunami in 2011 / Audrey Minghelli in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol 12 n° 2 (February 2019)PermalinkNear real-time deforestation detection in Malaysia and Indonesia using change vector analysis with three sensors / Pauline Perbet in International Journal of Remote Sensing IJRS, vol 40 n°19 (February 2019)PermalinkPermalinkPermalinkClimate variability and climate change impacts on land surface, hydrological processes and water management / Yongqiang Zhang (2019)PermalinkPermalinkFlash flood risk assessment in urban arid environment: case study of Taibah and Islamic universities’ campuses, Medina, Kingdom of Saudi Arabia / Mohamed Abdulrazzak in Geomatics, Natural Hazards and Risk, vol 10 n° 1 (2019)PermalinkPermalinkPermalinkReal-time capturing of seismic waveforms using high-rate BDS, GPS and GLONASS observations: the 2017 Mw 6.5 Jiuzhaigou earthquake in China / Xingxing Li in GPS solutions, vol 23 n° 1 (January 2019)Permalink