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A generalized space-time OBIA classification scheme to map sugarcane areas at regional scale, using Landsat images time-series and the random forest algorithm / Ana Claudia Dos Santos Luciano in International journal of applied Earth observation and geoinformation, vol 80 (August 2019)
[article]
Titre : A generalized space-time OBIA classification scheme to map sugarcane areas at regional scale, using Landsat images time-series and the random forest algorithm Type de document : Article/Communication Auteurs : Ana Claudia Dos Santos Luciano, Auteur ; Michelle Cristina Araújo Picoli, Auteur ; Jansle Vieira Rocha, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 127-136 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse spatio-temporelle
[Termes IGN] apprentissage automatique
[Termes IGN] Brésil
[Termes IGN] carte agricole
[Termes IGN] classification dirigée
[Termes IGN] classification orientée objet
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] extraction de données
[Termes IGN] image à haute résolution
[Termes IGN] image Landsat
[Termes IGN] production agricole
[Termes IGN] Saccharum officinarum
[Termes IGN] série temporelle
[Termes IGN] surface cultivée
[Termes IGN] zone d'intérêtRésumé : (auteur) The monitoring of sugarcane areas is important for sustainable planning and management of the sugarcane industry in Brazil. We developed an operational Object-Based Image Analysis (OBIA) classification scheme, with generalized space-time classifier, for mapping sugarcane areas at the regional scale in São Paulo State (SP). Binary random forest (RF) classification models were calibrated using multi-temporal data from Landsat images, at 10 sites located across SP. Space and time generalization were tested and compared for three approaches: a local calibration and application; a cross-site spatial generalization test with the RF model calibrated on a site and applied on other sites; and a unique space–time classifier calibrated with all sites together on years 2009–2014 and applied to the entire SP region on 2015. The local RF models Dice Coefficient (DC) accuracies at sites 1 to 8 were between 0.83 and 0.92 with an average of 0.89. The cross-site classification accuracy showed an average DC of 0.85, and the unique RF model had a DC of 0.89 when compared with a reference map of 2015. The results demonstrated a good relationship between sugarcane prediction and the reference map for each municipality in SP, with R² = 0.99 and only 5.8% error for the total sugarcane area in SP, and compared with the area inventory from the Brazilian Institute of Geography and Statistics, with R² = 0.95 and –1% error for the total sugarcane area in SP. The final unique RF model allowed monitoring sugarcane plantations at the regional scale on independent year, with efficiency, low-cost, limited resources and a precision approximating that of a photointerpretation. Numéro de notice : A2019-470 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2019.04.013 Date de publication en ligne : 25/04/2019 En ligne : https://doi.org/10.1016/j.jag.2019.04.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93612
in International journal of applied Earth observation and geoinformation > vol 80 (August 2019) . - pp 127-136[article]A novel method for separating woody and herbaceous time series / Qiang Zhou in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 7 (July 2019)
[article]
Titre : A novel method for separating woody and herbaceous time series Type de document : Article/Communication Auteurs : Qiang Zhou, Auteur ; Shuguang Liu, Auteur ; Michael J Hill, Auteur Année de publication : 2019 Article en page(s) : pp 509 - 520 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Afrique australe
[Termes IGN] bois
[Termes IGN] extraction de la végétation
[Termes IGN] image à haute résolution
[Termes IGN] image Ikonos
[Termes IGN] image Landsat-SWIR
[Termes IGN] image Terra-MODIS
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] plante herbacée
[Termes IGN] savane
[Termes IGN] série temporelle
[Termes IGN] variation saisonnièreRésumé : (auteur) Mapping the spatial distribution of woody and herbaceous vegetation in high temporal resolution in savannas would be beneficial for modeling interrelationships between trees and grasses, and monitoring fuel loads and biomass for livestock. In this study, we developed a frequency decomposition method to separate woody and herbaceous vegetation components using Normalized Difference Vegetation Index (NDVI) time series. The results were validated using fractional cover data derived from high-resolution images. The validation revealed a close relationship between our decomposed NDVI and corresponding fractional cover (R2 = 0.55 and 0.64 for woody and herbaceous components, respectively). We examined the spatial and temporal patterns of the decomposed NDVI, where woody and herbaceous NDVI showed different responses to precipitation. The methods proposed in this study can be used to separate the woody and herbaceous NDVI time series as an alternative approach for monitoring woody and herbaceous vegetation interrelationships related to climatic drivers. Numéro de notice : A2019-259 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.7.509 Date de publication en ligne : 01/07/2019 En ligne : https://doi.org/10.14358/PERS.85.7.509 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93062
in Photogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 7 (July 2019) . - pp 509 - 520[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2019071 SL Revue Centre de documentation Revues en salle Disponible PPP-RTK based on undifferenced and uncombined observations: theoretical and practical aspects / Baocheng Zhang in Journal of geodesy, vol 93 n°7 (July 2019)
[article]
Titre : PPP-RTK based on undifferenced and uncombined observations: theoretical and practical aspects Type de document : Article/Communication Auteurs : Baocheng Zhang, Auteur ; Yongchang Chen, Auteur ; Yunbin Yuan, Auteur Année de publication : 2019 Article en page(s) : pp 1011 - 1024 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] ambiguïté entière
[Termes IGN] données GNSS
[Termes IGN] mesurage de phase
[Termes IGN] positionnement cinématique en temps réel
[Termes IGN] positionnement par GNSS
[Termes IGN] positionnement ponctuel précis
[Termes IGN] série temporelleRésumé : (auteur) A synthesis of two prevailing global navigation satellite system positioning technologies, namely the precise point positioning and the network-based real-time kinematic, results in the emergence of the PPP-RTK, enabling single-receiver users to achieve high positioning accuracy with reasonable timeliness through integer ambiguity resolution. The realization of PPP-RTK needs to accomplish two sequential tasks. The first task is to determine a class of corrections including, among others, the satellite phase biases (SPBs) at the network level. With these corrections, the second task, then, is to solve for the ambiguity-fixed, absolute position at the user level. In this contribution, we revisit three variants (geometry-free, geometry-fixed and geometry-plus-satellite-clock-fixed) of the undifferenced and uncombined PPP-RTK network model and then point out their implications for practical use. We also carry out a case study using multi-day, dual-frequency global positioning system data from the crustal movement observation network of China stations, aiming to figure out what are the most appropriate linear combinations of the SPBs to be transmitted to the users from the viewpoint of decorrelation, and to assess the static and kinematic positioning performance. Numéro de notice : A2019-357 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-018-1220-5 Date de publication en ligne : 06/12/2018 En ligne : https://doi.org/10.1007/s00190-018-1220-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93425
in Journal of geodesy > vol 93 n°7 (July 2019) . - pp 1011 - 1024[article]Sea level prediction in the Yellow Sea from satellite altimetry with a combined least squares-neural network approach / Jian Zhao in Marine geodesy, vol 42 n° 4 (July 2019)
[article]
Titre : Sea level prediction in the Yellow Sea from satellite altimetry with a combined least squares-neural network approach Type de document : Article/Communication Auteurs : Jian Zhao, Auteur ; Yanguo Fan, Auteur ; Yuxiang Mu, Auteur Année de publication : 2019 Article en page(s) : pp 344 - 366 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] détection d'anomalie
[Termes IGN] données altimétriques
[Termes IGN] données Jason
[Termes IGN] données Topex-Poseidon
[Termes IGN] image ERS-SAR
[Termes IGN] méthode des moindres carrés
[Termes IGN] montée du niveau de la mer
[Termes IGN] Pacifique nord
[Termes IGN] prévision
[Termes IGN] réseau neuronal artificiel
[Termes IGN] série temporelleRésumé : (auteur) Accessible high-quality observation datasets and proper modeling process are critically required to accurately predict sea level rise in coastal areas. This study focuses on developing and validating a combined least squares-neural network approach applicable to the short-term prediction of sea level variations in the Yellow Sea, where the periodic terms and linear trend of sea level change are fitted and extrapolated using the least squares model, while the prediction of the residual terms is performed by several different types of artificial neural networks. The input and output data used are the sea level anomalies (SLA) time series in the Yellow Sea from 1993 to 2016 derived from ERS-1/2, Topex/Poseidon, Jason-1/2, and Envisat satellite altimetry missions. Tests of different neural network architectures and learning algorithms are performed to assess their applicability for predicting the residuals of SLA time series. Different neural networks satisfactorily provide reliable results and the root mean square errors of the predictions from the proposed combined approach are less than 2 cm and correlation coefficients between the observed and predicted SLA are up to 0.87. Results prove the reliability of the combined least squares-neural network approach on the short-term prediction of sea level variability close to the coast. Numéro de notice : A2019-281 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01490419.2019.1626306 Date de publication en ligne : 12/06/2019 En ligne : https://doi.org/10.1080/01490419.2019.1626306 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93115
in Marine geodesy > vol 42 n° 4 (July 2019) . - pp 344 - 366[article]Mise en oeuvre d'outils open source pour le suivi opérationnel de l'occupation des sols et de la déforestation à partir des données Sentinel radar optique : études de cas en Guyane et au Togo / Cédric Lardeux in Revue Française de Photogrammétrie et de Télédétection, n° 219-220 (juin - octobre 2019)
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Titre : Mise en oeuvre d'outils open source pour le suivi opérationnel de l'occupation des sols et de la déforestation à partir des données Sentinel radar optique : études de cas en Guyane et au Togo Type de document : Article/Communication Auteurs : Cédric Lardeux, Auteur ; Anoumou Kemavo, Auteur ; Maxence Rageade, Auteur ; Mathieu Rahm, Auteur ; Pierre-Louis Frison , Auteur ; Jean-Paul Rudant , Auteur Année de publication : 2019 Article en page(s) : pp 59 - 70 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] déboisement
[Termes IGN] Guyane (département français)
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] Orfeo Tool Box
[Termes IGN] Python (langage de programmation)
[Termes IGN] QGIS
[Termes IGN] série temporelle
[Termes IGN] surveillance de la végétation
[Termes IGN] télédétection en hyperfréquence
[Termes IGN] TogoRésumé : (auteur) Remote sensing is a particularly suitable tool for monitoring land use but also particularly suited for deforestation monito-ring. By launching the Setinel-1 and Sentinel-2 satellites in the Copernicus program, the community now has free data with important time-revisits allowing the greatest number of people to effectively monitor land cover of a study area. This paper presents a land use monitoring method based on the combination of two approaches computed using Open Source tools ((MIS, Orfeo ToolBox, python). First, we focus on land use monitoring at an annual time scale using Sentinel-1 and Sentinel-2 data, and then, by the use f entienl-1 data, we detect changes in the forest cover due to deforestation at bi-monthly time scale. The results obtained show a very good synergy of these approaches allowing the complementary of optical and radar data. In order to make accessible the proposed method, all the used open source tools are available on this link http ://remotesensing4all.net/index.php/2018/09/11/ kit-use-des-donnees-radar- sentinel-1-in-de-latelier-radar-du-FOSS4G-en-2018-2/. Numéro de notice : A2019-348 Affiliation des auteurs : UPEM-LASTIG+Ext (2016-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.52638/rfpt.2019.467 En ligne : https://doi.org/10.52638/rfpt.2019.467 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93385
in Revue Française de Photogrammétrie et de Télédétection > n° 219-220 (juin - octobre 2019) . - pp 59 - 70[article]Seasonal pattern in time series of variances of GPS residual errors Anova estimates / Darko Anđić in Geodetski vestnik, vol 63 n° 2 (June - August 2019)PermalinkJournées de la recherche 2019 / Anonyme in Géomatique expert, n° 127 (avril - mai 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)PermalinkA comparative study between least square and total least square methods for time-series analysis and quality control of sea level observations / Mahmoud Pirooznia in Marine geodesy, vol 42 n° 2 (March 2019)PermalinkDuPLO: A DUal view Point deep Learning architecture for time series classificatiOn / Roberto Interdonato in ISPRS Journal of photogrammetry and remote sensing, vol 149 (March 2019)PermalinkTemporal and spatial high-resolution climate data from 1961 to 2100 for the German National Forest Inventory (NFI) / Helge Dietrich in Annals of Forest Science, vol 76 n° 1 (March 2019)PermalinkCombined orbits and clocks from IGS second reprocessing / Jake Griffiths in Journal of geodesy, vol 93 n° 2 (February 2019)PermalinkAnalyse de la déformation récente dans le Grand Tunis par interférométrie radar SAR / Anis Chaabani (2019)PermalinkAssessment of different vegetation parameters for parameterizing the coupled water cloud model and advanced integral equation model for soil moisture retrieval using time series Sentinel-1A data / Long Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 1 (January 2019)PermalinkChallenges in grassland mowing event detection with multimodal Sentinel images / Anatol Garioud (2019)Permalink