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télédétection
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Télédétection aérospatiale Télédétection par satellite Télédétection satellitaire Télédétection spatiale Appareils enregistreurs >> Agriculture de précision Capteurs (technologie) Photogrammétrie aérienne Photographie aérienne >>Terme(s) spécifique(s) : Télédétection en sciences de la Terre Cartographie radar Traitement d'images -- Techniques numériques Images de télédétection Radar à antenne synthétique Radar en sciences de la Terre Reconnaissance aérienne Satellites artificiels en télédétection Satellites de télédétection des ressources terrestres SPOT (satellites de télédétection) Surveillance électronique Télédétection hyperfréquence Télémesure spatiale Thermographie Equiv. LCSH : Remote sensing Domaine(s) : 500; 600 |
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Comparing Landsat-8 and Sentinel-2 top of atmosphere and surface reflectance in high latitude regions: case study in Alaska / Jiang Chen in Geocarto international, vol 37 n° 20 ([20/09/2022])
[article]
Titre : Comparing Landsat-8 and Sentinel-2 top of atmosphere and surface reflectance in high latitude regions: case study in Alaska Type de document : Article/Communication Auteurs : Jiang Chen, Auteur ; Weining Zhu, Auteur Année de publication : 2022 Article en page(s) : pp 6052 - 6071 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Alaska (Etats-Unis)
[Termes IGN] analyse comparative
[Termes IGN] Google Earth Engine
[Termes IGN] image Landsat-8
[Termes IGN] image proche infrarouge
[Termes IGN] image Sentinel-MSI
[Termes IGN] latitude
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] observation de la Terre
[Termes IGN] réflectance de surfaceRésumé : (auteur) Combining Landsat-8 and Sentinel-2 images is an effective approach to obtain high spatiotemporal resolution data for Earth observation and remote sensing modeling. The differences between Landsat-8 and Sentinel-2 products, such as the reflectance at the top of atmosphere (TOA) and land surface, should be compared and evaluated to make sure they are spectrally consistent. Their consistency has been evaluated and the differences have been empirically corrected at mid-low latitudes, but in high latitude areas with a higher solar zenith angle (SZA), the similar work has not been explored. In this study, Landsat-8 and Sentinel-2 TOA and surface reflectance in Alaska as well as some surface parameters, such as the normalized difference vegetation index (NDVI) and normalized difference snow index (NDSI), were compared using the massive data distributed on Google earth engine (GEE) online platform, and their consistency was evaluated and the uncertainty was analyzed. Some empirical models were suggested to convert Sentinel-2 products to be consistent with Landsat-8 products at all bands. The results show that TOA reflectance is more consistent than surface reflectance in Alaska. This study suggests that the consistency between Landsat-8 and Sentinel-2 at high latitudes should be paid more attention because their consistency is lower than that at mid-low latitudes. Numéro de notice : A2022-717 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : https://doi.org/10.1080/10106049.2021.1924295 Date de publication en ligne : 17/05/2021 En ligne : https://doi.org/10.1080/10106049.2021.1924295 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101642
in Geocarto international > vol 37 n° 20 [20/09/2022] . - pp 6052 - 6071[article]Forest canopy stratification based on fused, imbalanced and collinear LiDAR and Sentinel-2 metrics / Jakob Wernicke in Remote sensing of environment, vol 279 (September-15 2022)
[article]
Titre : Forest canopy stratification based on fused, imbalanced and collinear LiDAR and Sentinel-2 metrics Type de document : Article/Communication Auteurs : Jakob Wernicke, Auteur ; Christian Torsten Seltmann, Auteur ; Ralf Wenzel, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 113134 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Allemagne
[Termes IGN] analyse comparative
[Termes IGN] canopée
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] fusion d'images
[Termes IGN] image Sentinel-MSI
[Termes IGN] indice de végétation
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] semis de points
[Termes IGN] stratificationRésumé : (auteur) Knowledge about the forest canopy stratification is of essential importance for forest management and planning. Collecting structural information (e.g. natural regeneration) still depends on cost and labour intensive forest inventories with a coarse spatio-temporal resolution. Remote sensing partly overcomes these limitations and particularly active sensors of type light detection and ranging (LiDAR) have proven their great potential of separating forest strata. The applicability of LiDAR metrics for the differentiation of the spruce dominated forest strata in Central Germany has not been tested yet. Additionally, studying the potential of Sentinel-2 metrics for the classification of forest strata is lacking too. In this study, we investigated the capabilities of six different classification approaches for the differentiation of five forest strata that are typical for the study region. Reference data were derived from forest inventory measurements surveyed on a dense 200 × 200 m grid. The six classification approaches were trained with fused and un-fused LiDAR and Sentinel-2 inferred metrics. The classification results were compared using the overall mean accuracy, sensitivity and specificity via receivers operating characteristics of multi-class problems. We were interested in the classification abilities of Sentinel-2 metrics due to the obvious advantages of Sentinel-2 based metrics (free of charge, high spatio-temporal coverage). We assumed that the canopy structure determines the reflection on stand level and thus might facilitate the classification of different canopy strata. Beforehand, it was important to examine the influence of distinctly imbalanced and collinear reference data on the classification results. We found that the Random Forest classifier most accurately separated the five forest strata with a mean overall accuracy of 83.3% (Kappa = 76.2%). These values were achieved from balanced training data and the classification capability was confirmed by classification results from an independent test data set. Fused predictors of active (LiDAR) and passive (Sentinel-2) remote sensing revealed no substantial improvement in the classification accuracy due to the dominant role of LiDAR metrics. Herein, we identified that especially the height variability, top height, portion of LiDAR-returns between 2 m and 10 m and the standard deviation of the return number between the 25th and 50th height percentile, predominately contributed to the classification accuracy. Classification results purely based on Sentinel-2 metrics revealed a rather small overall mean accuracy of 54.7%. The metrics (e.g. median, variance, entropy) were derived from Sentinel-2 indices, covering the visible and near to short infrared spectrum. Variable importance computations unraveled a detectable but minor contribution of MSI, TCG, NDVI to the classification result. Finally, our data driven observations illustrated serious drawbacks associated to data imbalance, collinearity and autocorrelation and presented practical guidance to cope with these issues. Numéro de notice : A2022-510 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2022.113134 Date de publication en ligne : 28/06/2022 En ligne : https://doi.org/10.1016/j.rse.2022.113134 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101047
in Remote sensing of environment > vol 279 (September-15 2022) . - n° 113134[article]Cartographic enclosure and urban cadastral mapping in the Ethiopian Somali capital / Romy Emmenegger in Cartographica, vol 57 n° 3 (September 2022)
[article]
Titre : Cartographic enclosure and urban cadastral mapping in the Ethiopian Somali capital Type de document : Article/Communication Auteurs : Romy Emmenegger, Auteur Année de publication : 2022 Article en page(s) : pp 226 - 238 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cadastre étranger
[Termes IGN] aménagement du territoire
[Termes IGN] cadastre étranger
[Termes IGN] cartographie cadastrale
[Termes IGN] Ethiopie
[Termes IGN] géoréférencement
[Termes IGN] propriété foncière
[Termes IGN] représentation cartographique
[Termes IGN] territoire
[Termes IGN] utilisation du solRésumé : (auteur) Cadastral maps, which are designed as comprehensive systems for recording and surveying land relations, are critical for making society legible and governable. However, critical cartography scholarship suggests that exercising power through maps is not straightforward: It is dependent on how maps are created and used during the mapping process. This paper examines cadastral mapping in Jigjiga, a multi-ethnic city in the Ethiopian Somali frontier where state authority over land and people have long been contested among ethnic Somali residents. This paper follows the ruling government’s renewed attempt to establish land control through spatial planning based on document analysis and ethnographic fieldwork. It investigates how urban planners enclose the city’s property landscape cartographically on land use maps and how land surveyors used these maps to georeference property. It demonstrates the critical role of land governance experts in navigating the simplified map and a complex property landscape on the ground. Cadastral mapping is instrumental for state territorialization and land commodification, integrating ethnic Somali property into the sedentary logic of the state. Rather than providing an account of how property is rendered legible, this paper highlights the incomplete and open-ended character of cadastral mapping in the constitution of private property regimes. Numéro de notice : A2022-849 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.3138/cart-2021-0011 Date de publication en ligne : 04/11/2022 En ligne : https://doi.org/10.3138/cart-2021-0011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102087
in Cartographica > vol 57 n° 3 (September 2022) . - pp 226 - 238[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 031-2022031 RAB Revue Centre de documentation En réserve L003 Disponible Crowdsourcing-based application to solve the problem of insufficient training data in deep learning-based classification of satellite images / Ekrem Saralioglu in Geocarto international, vol 37 n° 18 ([01/09/2022])
[article]
Titre : Crowdsourcing-based application to solve the problem of insufficient training data in deep learning-based classification of satellite images Type de document : Article/Communication Auteurs : Ekrem Saralioglu, Auteur ; Oguz Gungor, Auteur Année de publication : 2022 Article en page(s) : pp 5433 - 5452 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] acquisition d'images
[Termes IGN] apprentissage profond
[Termes IGN] approche participative
[Termes IGN] classification dirigée
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] couleur (variable spectrale)
[Termes IGN] données d'entrainement (apprentissage automatique)
[Termes IGN] étiquette
[Termes IGN] image multibande
[Termes IGN] OpenStreetMap
[Termes IGN] pixel
[Termes IGN] plateforme collaborative
[Termes IGN] texture d'image
[Termes IGN] WorldviewRésumé : (auteur) In order to solve insufficient training data problem in remote sensing, a web platform was created so that registered users can generate labeled data for various classes in a dynamic structure. Users were asked to select representative pixel groups for the forest, hazelnut, shadow, soil, tea, and building classes with the polygon tool, and then assign a class label corresponding to each created polygon thanks to the help document displaying descriptive information regarding the locations, colors, textures and distributions of the classes in the image. Crowdsourcing was again used to test the accuracy of the tagged data produced by crowdsourcing. The created data set was overlaid with the original WV-2 image, and the correctness of the labels of the polygons was once visually verified. Finally, the WV-2 image, consisting of 40 patches, was classified with CNN and an average of over 95% accuracy was achieved. Numéro de notice : A2022-702 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2021.1917006 Date de publication en ligne : 26/05/2021 En ligne : https://doi.org/10.1080/10106049.2021.1917006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101561
in Geocarto international > vol 37 n° 18 [01/09/2022] . - pp 5433 - 5452[article]Feux de forêt : un drone traque les risques de reprise / Nathalie Da Cruz in Géomètre, n° 2205 (septembre 2022)
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Titre : Feux de forêt : un drone traque les risques de reprise Type de document : Article/Communication Auteurs : Nathalie Da Cruz, Auteur Année de publication : 2022 Article en page(s) : pp 16 - 18 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] aide à la localisation
[Termes IGN] Gironde (33)
[Termes IGN] image captée par drone
[Termes IGN] image thermique
[Termes IGN] incendie de forêt
[Termes IGN] télédétection aérienne
[Termes IGN] température au solRésumé : (Auteur) Lors des incendies en Gironde, cet été, le cabinet de géomètres-experts Parallèle 45 a proposé aux autorités l’utilisation de son drone avec caméra thermique pour repérer les fumerons. Une aide précieuse appréciée des élus locaux et des sapeurs-pompiers. Numéro de notice : A2022-529 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtSansCL DOI : sans Date de publication en ligne : 01/09/2022 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101491
in Géomètre > n° 2205 (septembre 2022) . - pp 16 - 18[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 063-2022091 RAB Revue Centre de documentation En réserve L003 Disponible Historical mapping of rice fields in Japan using phenology and temporally aggregated Landsat images in Google Earth Engine / Luis Carrasco in ISPRS Journal of photogrammetry and remote sensing, vol 191 (September 2022)PermalinkLandsat, le programme fête ses cinquante ans / Laurent Polidori in Géomètre, n° 2205 (septembre 2022)PermalinkIncorporation of digital elevation model, normalized difference vegetation index, and Landsat-8 data for land use land cover mapping / Jwan Al-Doski in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 8 (August 2022)PermalinkMainstreaming remotely sensed ecosystem functioning in ecological niche models / Adrián Regos in Remote sensing in ecology and conservation, vol 8 n° 4 (August 2022)PermalinkMapping land-use intensity of grasslands in Germany with machine learning and Sentinel-2 time series / Maximilian Lange in Remote sensing of environment, vol 277 (August 2022)PermalinkRemote sensing and phytoecological methods for mapping and assessing potential ecosystem services of the Ouled Hannèche Forest in the Hodna Mountains, Algeria / Amal Louail in Forests, Vol 13 n° 8 (August 2022)PermalinkSmart city data science: Towards data-driven smart cities with open research issues / Iqbal H. Sarker in Internet of Things, vol 19 (August 2022)PermalinkMultiscale assimilation of Sentinel and Landsat data for soil moisture and Leaf Area Index predictions using an ensemble-Kalman-filter-based assimilation approach in a heterogeneous ecosystem / Nicola Montaldo in Remote sensing, vol 14 n° 14 (July-2 2022)PermalinkA framework for urban land use classification by integrating the spatial context of points of interest and graph convolutional neural network method / Yongyang Xu in Computers, Environment and Urban Systems, vol 95 (July 2022)PermalinkInvestigating the ability to identify new constructions in urban areas using images from unmanned aerial vehicles, Google Earth, and Sentinel-2 / Fahime Arabi Aliabad in Remote sensing, vol 14 n° 13 (July-1 2022)Permalink