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A mangrove forest map of China in 2015: Analysis of time series Landsat 7/8 and Sentinel-1A imagery in Google Earth Engine cloud computing platform / Bangqian Chen in ISPRS Journal of photogrammetry and remote sensing, vol 131 (September 2017)
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Titre : A mangrove forest map of China in 2015: Analysis of time series Landsat 7/8 and Sentinel-1A imagery in Google Earth Engine cloud computing platform Type de document : Article/Communication Auteurs : Bangqian Chen, Auteur ; Xiangming Xiao, Auteur ; Lianghao Pan, Auteur ; Russell Doughty, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 104 - 120 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] carte forestière
[Termes IGN] Chine
[Termes IGN] Google Earth Engine
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-OLI
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] mangrove
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] série temporelleRésumé : (auteur) Due to rapid losses of mangrove forests caused by anthropogenic disturbances and climate change, accurate and contemporary maps of mangrove forests are needed to understand how mangrove ecosystems are changing and establish plans for sustainable management. In this study, a new classification algorithm was developed using the biophysical characteristics of mangrove forests in China. More specifically, these forests were mapped by identifying: (1) greenness, canopy coverage, and tidal inundation from time series Landsat data, and (2) elevation, slope, and intersection-with-sea criterion. The annual mean Normalized Difference Vegetation Index (NDVI) was found to be a key variable in determining the classification thresholds of greenness, canopy coverage, and tidal inundation of mangrove forests, which are greatly affected by tide dynamics. In addition, the integration of Sentinel-1A VH band and modified Normalized Difference Water Index (mNDWI) shows great potential in identifying yearlong tidal and fresh water bodies, which is related to mangrove forests. This algorithm was developed using 6 typical Regions of Interest (ROIs) as algorithm training and was run on the Google Earth Engine (GEE) cloud computing platform to process 1941 Landsat images (25 Path/Row) and 586 Sentinel-1A images circa 2015. The resultant mangrove forest map of China at 30 m spatial resolution has an overall/users/producer’s accuracy greater than 95% when validated with ground reference data. In 2015, China’s mangrove forests had a total area of 20,303 ha, about 92% of which was in the Guangxi Zhuang Autonomous Region, Guangdong, and Hainan Provinces. This study has demonstrated the potential of using the GEE platform, time series Landsat and Sentine-1A SAR images to identify and map mangrove forests along the coastal zones. The resultant mangrove forest maps are likely to be useful for the sustainable management and ecological assessments of mangrove forests in China. Numéro de notice : A2017-419 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.07.011 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.07.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86313
in ISPRS Journal of photogrammetry and remote sensing > vol 131 (September 2017) . - pp 104 - 120[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2017091 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017093 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2017092 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Vol 44 n° 5 - September 2017 - Special content sections: pointed innovations; bicycle mapping (Bulletin de Cartography and Geographic Information Science)
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[n° ou bulletin]
est un bulletin de Cartography and Geographic Information Science / Cartography and geographic information society (1999 -)
Titre : Vol 44 n° 5 - September 2017 - Special content sections: pointed innovations; bicycle mapping Type de document : Périodique Année de publication : 2017 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique
[Termes IGN] carte thématique
[Termes IGN] cartographie collaborative
[Termes IGN] données localisées des bénévolesNuméro de notice : 032-201705 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Numéro de périodique En ligne : http://www.tandfonline.com/toc/tcag20/44/5?nav=tocList Format de la ressource électronique : URL Sommaire Permalink : https://documentation.ensg.eu/index.php?lvl=bulletin_display&id=28805 [n° ou bulletin] Contient
- Point grid map : a new type of thematic map for statistical data associated with geographic points / Mengjie Zhou in Cartography and Geographic Information Science, Vol 44 n° 5 (September 2017)
- BinSq : visualizing geographic dot density patterns with gridded maps / Alvin Chua in Cartography and Geographic Information Science, Vol 44 n° 5 (September 2017)
- Crowdsourcing a cyclist perspective on suggested recreational paths in real-world networks / Kevin Baker in Cartography and Geographic Information Science, Vol 44 n° 5 (September 2017)
- An empirical evaluation of three elevation change symbolization methods along routes in bicycle maps / Annina Brügger in Cartography and Geographic Information Science, Vol 44 n° 5 (September 2017)
- Assessing professional benefits of GIS certification / Adam J. Mathews in Cartography and Geographic Information Science, Vol 44 n° 5 (September 2017)
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Code-barres Cote Support Localisation Section Disponibilité 032-2017051 RAB Revue Centre de documentation En réserve L003 Disponible Exploiting illusory grid lines for object-location memory performance in urban topographic maps / Frank Dickmann in Cartographic journal (the), Vol 54 n° 3 (August 2017)
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Titre : Exploiting illusory grid lines for object-location memory performance in urban topographic maps Type de document : Article/Communication Auteurs : Frank Dickmann, Auteur ; Dennis Edler, Auteur ; Anne-Kathrin Bestgen, Auteur ; Lars Kuchinke, Auteur Année de publication : 2017 Article en page(s) : pp 242-253 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie
[Termes IGN] carte interactive
[Termes IGN] carte topographique
[Termes IGN] géopositionnement
[Termes IGN] quadrillage
[Termes IGN] symbole graphique
[Termes IGN] système d'information géographique
[Termes IGN] topologieRésumé : (Auteur) In order to be successful in spatial orientation tasks, people need to recall locations and configurations of spatial objects from their memory. This understanding of geographic space often arises from experience with cartographic media representing topographic and topological information by graphic symbols. Learning spatial information from graphic media is influenced by different perception-based grouping effects distorting the accuracy of spatial object-positions and their relations. Such geometric inaccuracies can be softened by adding a grid layer, which regionalizes the map and can be used as an additional orientation pattern. This grid layer usually consists of solid lines and overlays semantic information. The present paper reports the results of two empirical studies on object-location memory (OLM) performance. In these studies, the amount of visual detail of the grid layer was reduced. By positioning the grid layer below specific urban topographic objects (study 1), the grid pattern was graphically interrupted. These interrupted grid lines were completed by cognitive completion mechanisms (illusory grid lines) described in the Gestalt principles of closure and continuation. The second experiment examined the maximum grid line gap that is closed by cognitive line completion and keeps an advantage for OLM (study 2). Numéro de notice : A2017-693 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00087041.2016.1236509 En ligne : https://doi.org/10.1080/00087041.2016.1236509 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88003
in Cartographic journal (the) > Vol 54 n° 3 (August 2017) . - pp 242-253[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 030-2017031 RAB Revue Centre de documentation En réserve L003 Disponible Reducing classification error of grassland overgrowth by combing low-density lidar acquisitions and optical remote sensing data / Timo P Pitkänen in ISPRS Journal of photogrammetry and remote sensing, vol 130 (August 2017)
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Titre : Reducing classification error of grassland overgrowth by combing low-density lidar acquisitions and optical remote sensing data Type de document : Article/Communication Auteurs : Timo P Pitkänen, Auteur ; Niina Käyhkö, Auteur Année de publication : 2017 Article en page(s) : pp 150 - 161 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse diachronique
[Termes IGN] arbre (flore)
[Termes IGN] boisement naturel
[Termes IGN] carte de la végétation
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] densité des points
[Termes IGN] détection de changement
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] erreur de classification
[Termes IGN] image Landsat
[Termes IGN] orthoimage
[Termes IGN] prairie
[Termes IGN] structure de données localiséesRésumé : (Auteur) Mapping structural changes in vegetation dynamics has, for a long time, been carried out using satellite images, orthophotos and, more recently, airborne lidar acquisitions. Lidar has established its position as providing accurate material for structure-based analyses but its limited availability, relatively short history, and lack of spectral information, however, are generally impeding the use of lidar data for change detection purposes. A potential solution in respect of detecting both contemporary vegetation structures and their previous trajectories is to combine lidar acquisitions with optical remote sensing data, which can substantially extend the coverage, span and spectral range needed for vegetation mapping. In this study, we tested the simultaneous use of a single low-density lidar data set, a series of Landsat satellite frames and two high-resolution orthophotos to detect vegetation succession related to grassland overgrowth, i.e. encroachment of woody plants into semi-natural grasslands. We built several alternative Random Forest models with different sets of variables and tested the applicability of respective data sources for change detection purposes, aiming at distinguishing unchanged grassland and woodland areas from overgrown grasslands. Our results show that while lidar alone provides a solid basis for indicating structural differences between grassland and woodland vegetation, and orthophoto-generated variables alone are better in detecting successional changes, their combination works considerably better than its respective parts. More specifically, a model combining all the used data sets reduces the total error from 17.0% to 11.0% and omission error of detecting overgrown grasslands from 56.9% to 31.2%, when compared to model constructed solely based on lidar data. This pinpoints the efficiency of the approach where lidar-generated structural metrics are combined with optical and multitemporal observations, providing a workable framework to identify structurally oriented and dynamically organized landscape phenomena, such as grassland overgrowth. Numéro de notice : A2017-513 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.05.016 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.05.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86459
in ISPRS Journal of photogrammetry and remote sensing > vol 130 (August 2017) . - pp 150 - 161[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2017081 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017083 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2017082 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt A relative evaluation of random forests for land cover mapping in an urban area / Di Shi in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 8 (August 2017)
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Titre : A relative evaluation of random forests for land cover mapping in an urban area Type de document : Article/Communication Auteurs : Di Shi, Auteur ; Xiaojun Yang, Auteur Année de publication : 2017 Article en page(s) : pp 541 - 552 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse comparative
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] objet géographique complexe
[Termes IGN] occupation du sol
[Termes IGN] Perceptron multicouche
[Termes IGN] zone urbaineRésumé : (auteur) Random forests as a novel ensemble learning algorithm have significant potential for land cover mapping in complex areas but have not been sufficiently tested by the remote sensing community relative to some more popular pattern classifiers. In this research, we implemented random forests as a pattern classifier for land cover mapping from a satellite image covering a complex urban area, and evaluated the performance relative to several popular classifiers including Gaussian maximum likelihood (GML), multi-layer-perceptron networks (MLP), and support vector machines (SVM). Each classifier was carefully configured with the parameter settings recommended by recent literature, and identical training data were used in each classification. The accuracy of each classified map was further evaluated using identical reference data. Random forests were slightly more accurate than SVM and MLP but significantly better than GML in the overall map accuracy. Random forests and support vector machines generated almost identical overall map accuracy, but the former produced a smaller standard deviation of categorical accuracies, suggesting its better overall capability in classifying both homogeneous and heterogeneous land cover classes. Random forests have shown its robustness due to the most accurate classification on the whole, relatively balanced performance across all land cover categories, and relatively easier to implement. These findings should help promote the use of random forests for land cover classification in complex areas. Numéro de notice : A2017-435 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.14358/PERS.83.8.541 En ligne : https://doi.org/10.14358/PERS.83.8.541 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86339
in Photogrammetric Engineering & Remote Sensing, PERS > vol 83 n° 8 (August 2017) . - pp 541 - 552[article]Developing detailed age-specific thematic maps for coffee (Coffea arabica L.) in heterogeneous agricultural landscapes using random forests applied on Landsat 8 multispectral sensor / Abel Chemura in Geocarto international, vol 32 n° 7 (July 2017)
PermalinkDomains of uncertainty visualization research: a visual summary approach / Jennifer Smith Mason in Cartography and Geographic Information Science, Vol 44 n° 4 (July 2017)
PermalinkEvaluating the performance of using PPK-GPS technique in producing topographic contour map / Ahmed El Shouny in Marine geodesy, vol 40 n° 4 (July 2017)
PermalinkFusion of RADARSAT-2 and multispectral optical remote sensing data for LULC extraction in a tropical agricultural area / Mohamed Barakat A. Gibril in Geocarto international, vol 32 n° 7 (July 2017)
PermalinkInteractive shearing for terrain visualization : an expert study / Jonas Buddeberg in Geoinformatica, vol 21 n° 3 (July - September 2017)
PermalinkMap the gap: alternative visualisations of geographic knowledge production / Margath Walker in Geo: Geography and Environment, vol 4 n°2 (July 2017)
PermalinkSafe separation distance score : a new metric for evaluating wildland firefighter safety zones using lidar / Michael J. Campbell in International journal of geographical information science IJGIS, vol 31 n° 7-8 (July - August 2017)
PermalinkSuperresolution for UAV images via adaptive multiple sparse representation and its application to 3-D reconstruction / Muhammad Haris in IEEE Transactions on geoscience and remote sensing, vol 55 n° 7 (July 2017)
PermalinkApplication of terrestrial laser scanning to the development and updating of the base map / Przemysław Klapa in Geodesy and cartography, vol 66 n° 1 (June 2017)
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