Centre dedocumentation
scientifique

Comparative analysis for methods of building digital elevation models from topographic maps using geoinformation technologies / Vadim Belenok in Geodesy and cartography, vol 47 n° 4 (December 2021)  

Public [article]  inGeodesy and cartography > vol 47 n° 4 (December 2021) . - pp 191 - 199 Titre : Comparative analysis for methods of building digital elevation models from topographic maps using geoinformation technologies Type de document : Article/Communication Auteurs : Vadim Belenok, Auteur ; Yuriy Velikodsky, Auteur ; Oleksandr Nikolaienko, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 191 - 199 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] analyse comparative [Termes IGN] ArcGIS [Termes IGN] carte topographique [Termes IGN] contour [Termes IGN] données altimétriques [Termes IGN] image SRTM [Termes IGN] interpolation linéaire [Termes IGN] interpolation polynomiale [Termes IGN] modèle numérique de surface [Termes IGN] Python (langage de programmation) [Termes IGN] régression [Termes IGN] Russie [Termes IGN] vectorisation Résumé : (auteur) The article considers the question of estimating the accuracy of interpolation methods for building digital elevation models using Soviet topographic maps. The territory of the Kursk region of the Russian Federation was used as the study area, because it is located on the Central Russian Upland and characterized by the complex structure of the vertical and horizontal dissection of the relief. Contour lines automatically obtained using a Python algorithm were used as the initial elevation data to build a digital elevation model. Digital elevation models obtained by thirteen different interpolation methods in ArcGIS and Surfer software were built and analyzed. Special attention is paid to the ANUDEM method, which allows to obtain hydrologically correct digital elevation models. Recommendations for the use of one or another method of interpolation are given. The results can be useful for professionals who use topographic maps in their work and deals with the design using digital elevation models. Numéro de notice : A2021-925 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.3846/gac.2021.13208 Date de publication en ligne : 13/12/2021 En ligne : https://doi.org/10.3846/gac.2021.13208 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99287 [article]

Forest structural complexity tool: An open source, fully-automated tool for measuring forest point clouds / Sean Krisanski in Remote sensing, vol 13 n° 22 (November-2 2021)  

Public [article]  inRemote sensing > vol 13 n° 22 (November-2 2021) . - n° 4677 Titre : Forest structural complexity tool: An open source, fully-automated tool for measuring forest point clouds Type de document : Article/Communication Auteurs : Sean Krisanski, Auteur ; Mohammad Sadegh Taskhiri, Auteur ; Susana Gonzalez Aracil, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 4677 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] édition en libre accès [Termes IGN] logiciel libre [Termes IGN] modèle numérique de terrain [Termes IGN] Python (langage de programmation) [Termes IGN] segmentation [Termes IGN] semis de points [Termes IGN] squelettisation [Termes IGN] structure-from-motion [Termes IGN] télédétection par lidar Résumé : (auteur) Forest mensuration remains critical in managing our forests sustainably, however, capturing such measurements remains costly, time-consuming and provides minimal amounts of information such as diameter at breast height (DBH), location, and height. Plot scale remote sensing techniques show great promise in extracting detailed forest measurements rapidly and cheaply, however, they have been held back from large-scale implementation due to the complex and time-consuming workflows required to utilize them. This work is focused on describing and evaluating an approach to create a robust, sensor-agnostic and fully automated forest point cloud measurement tool called the Forest Structural Complexity Tool (FSCT). The performance of FSCT is evaluated using 49 forest plots of terrestrial laser scanned (TLS) point clouds and 7022 destructively sampled manual diameter measurements of the stems. FSCT was able to match 5141 of the reference diameter measurements fully automatically with mean, median and root mean squared errors (RMSE) of 0.032 m, 0.02 m, and 0.103 m respectively. A video demonstration is also provided to qualitatively demonstrate the diversity of point cloud datasets that the tool is capable of measuring. FSCT is provided as open source, with the goal of enabling plot scale remote sensing techniques to replace most structural forest mensuration in research and industry. Future work on this project will seek to make incremental improvements to this methodology to further improve the reliability and accuracy of this tool in most high-resolution forest point clouds. Numéro de notice : A2021-861 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : https://doi.org/10.3390/rs13224677 Date de publication en ligne : 19/11/2021 En ligne : https://doi.org/10.3390/rs13224677 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99075 [article]

Python software to transform GPS SNR wave phases to volumetric water content / Angel Martín in GPS solutions, vol 26 n° 1 (January 2022)  

Public [article]  inGPS solutions > vol 26 n° 1 (January 2022) . - n° 7 Titre : Python software to transform GPS SNR wave phases to volumetric water content Type de document : Article/Communication Auteurs : Angel Martín, Auteur ; Ana Belén Anquela, Auteur ; Sara Ibáñez, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 7 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] humidité du sol [Termes IGN] phase [Termes IGN] Python (langage de programmation) [Termes IGN] rapport signal sur bruit [Termes IGN] réflectométrie par GNSS [Termes IGN] signal GPS [Termes IGN] teneur en vapeur d'eau Résumé : (auteur) The global navigation satellite system interferometric reflectometry is often used to extract information about the environment surrounding the antenna. One of the most important applications is soil moisture monitoring. This manuscript presents the main ideas and implementation decisions needed to write the Python code to transform the derived phase of the interferometric GPS waves, obtained from signal-to-noise ratio data continuously observed during a period of several weeks (or months), to volumetric water content. The main goal of the manuscript is to share the software with the scientific community to help users in the GPS-IR computation. Numéro de notice : A2022-004 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-021-01190-3 Date de publication en ligne : 27/10/2021 En ligne : https://doi.org/10.1007/s10291-021-01190-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98919 [article]

JUST: MATLAB and python software for change detection and time series analysis / Ebrahim Ghaderpour in GPS solutions, vol 25 n° 3 (July 2021)  

Public [article]  inGPS solutions > vol 25 n° 3 (July 2021) . - Article 85 Titre : JUST: MATLAB and python software for change detection and time series analysis Type de document : Article/Communication Auteurs : Ebrahim Ghaderpour, Auteur Année de publication : 2021 Article en page(s) : Article 85 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Statistiques [Termes IGN] analyse de données [Termes IGN] détection de changement [Termes IGN] Matlab [Termes IGN] méthode des moindres carrés [Termes IGN] Python (langage de programmation) [Termes IGN] série temporelle Résumé : (Auteur) Change detection within unequally spaced and non-stationary time series is crucial in various applications, such as environmental monitoring and satellite navigation. The jumps upon spectrum and trend (JUST) is developed to detect potential jumps within the trend component of time series segments. JUST can simultaneously estimate the trend and seasonal components of any equally or unequally spaced time series by considering the observational uncertainties or measurement errors. JUST and its modules can also be applied to monitor vegetation time series in near-real-time. Herein, the details of the open-source software package for JUST, developed in both MATLAB and Python, are presented. Numéro de notice : A2021-330 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-021-01118-x Date de publication en ligne : 09/04/2021 En ligne : https://doi.org/10.1007/s10291-021-01118-x Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97500 [article]

Using machine learning to map Western Australian landscapes for mineral exploration / Thomas Albrecht in ISPRS International journal of geo-information, vol 10 n° 7 (July 2021)  

Public [article]  inISPRS International journal of geo-information > vol 10 n° 7 (July 2021) . - n° 459 Titre : Using machine learning to map Western Australian landscapes for mineral exploration Type de document : Article/Communication Auteurs : Thomas Albrecht, Auteur ; Ignacio Gonzalez-Alvarez, Auteur ; Jens Klump, Auteur Année de publication : 2021 Article en page(s) : n° 459 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] apprentissage automatique [Termes IGN] Australie occidentale (Australie) [Termes IGN] cartographie automatique [Termes IGN] classification dirigée [Termes IGN] classification par forêts aléatoires [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] géomorphologie [Termes IGN] modèle numérique de surface [Termes IGN] prospection minérale [Termes IGN] Python (langage de programmation) Résumé : (auteur) Landscapes evolve due to climatic conditions, tectonic activity, geological features, biological activity, and sedimentary dynamics. Geological processes at depth ultimately control and are linked to the resulting surface features. Large regions in Australia, West Africa, India, and China are blanketed by cover (intensely weathered surface material and/or later sediment deposition, both up to hundreds of metres thick). Mineral exploration through cover poses a significant technological challenge worldwide. Classifying and understanding landscape types and their variability is of key importance for mineral exploration in covered regions. Landscape variability expresses how near-surface geochemistry is linked to underlying lithologies. Therefore, landscape variability mapping should inform surface geochemical sampling strategies for mineral exploration. Advances in satellite imaging and computing power have enabled the creation of large geospatial data sets, the sheer size of which necessitates automated processing. In this study, we describe a methodology to enable the automated mapping of landscape pattern domains using machine learning (ML) algorithms. From a freely available digital elevation model, derived data, and sample landclass boundaries provided by domain experts, our algorithm produces a dense map of the model region in Western Australia. Both random forest and support vector machine classification achieve approximately 98% classification accuracy with a reasonable runtime of 48 minutes on a single Intel® Core™ i7-8550U CPU core. We discuss computational resources and study the effect of grid resolution. Larger tiles result in a more contiguous map, whereas smaller tiles result in a more detailed and, at some point, noisy map. Diversity and distribution of landscapes mapped in this study support previous results. In addition, our results are consistent with the geological trends and main basement features in the region. Mapping landscape variability at a large scale can be used globally as a fundamental tool for guiding more efficient mineral exploration programs in regions under cover. Numéro de notice : A2021-546 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10070459 Date de publication en ligne : 06/07/2021 En ligne : https://doi.org/10.3390/ijgi10070459 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98048 [article]

Data mining / Derya Birant (2021)  

Permalink

Developing graphics frameworks with Python and OpenGL / Lee Stemkoski (2021)  

Permalink

Participer à la construction de la base de données des toponymes maritimes du Shom / Solenn Tual (2021) 

Permalink

Qualification des données LiDAR GEDI pour le suivi de l’impact climatique sur la forêt de Südharz / Iris Jeuffrard (2021) 

Permalink

Système de gestion des servitudes d’utilité publique du Bas-Rhin : développement "backend" / Patrick-Franck Namekong-Teulong (2021) 

Permalink

Python software tools for GNSS interferometric reflectometry (GNSS-IR) / Angel Martín in GPS solutions, Vol 24 n° 4 (October 2020)  

Permalink

Estimating spatio-temporal air temperature in London (UK) using machine learning and earth observation satellite data / Rochelle Schneider dos Santos in International journal of applied Earth observation and geoinformation, vol 88 (June 2020)  

Permalink

Improved supervised learning-based approach for leaf and wood classification from LiDAR point clouds of forests / Sruthi M. Krishna Moorthy in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)  

Permalink

Création d’un outil d’interrogation du référentiel régional pédologique de Bretagne pour estimation du stock de carbone organique du sol / Louise Grall (2020) 

Permalink

Développement d’une application web de cartographie interactive d’un réseau de transports en commun / Nelly Paradelle (2020)  

Permalink