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Exploring the synergy between Landsat and ASAR towards improving thematic mapping accuracy of optical EO data / Alexander Cass in Applied geomatics, vol 11 n° 3 (September 2019)  

Public [article]  inApplied geomatics > vol 11 n° 3 (September 2019) . - pp 277 - 288 Titre : Exploring the synergy between Landsat and ASAR towards improving thematic mapping accuracy of optical EO data Type de document : Article/Communication Auteurs : Alexander Cass, Auteur ; George P. Petropoulos, Auteur ; Konstantinos P. Ferentinos, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 277 - 288 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes descripteurs IGN] carte d'occupation du sol [Termes descripteurs IGN] cartographie thématique [Termes descripteurs IGN] classification orientée objet [Termes descripteurs IGN] image Envisat-ASAR [Termes descripteurs IGN] image Landsat-TM [Termes descripteurs IGN] image optique [Termes descripteurs IGN] image radar [Termes descripteurs IGN] Pays de Galles [Termes descripteurs IGN] surface cultivée Résumé : (Auteur) Earth Observation (EO) provides a unique means of obtaining information on land use/cover and of its changes, which is of key importance in many scientific and practical applications. EO data is already widely used, for example, in environmental practices or decision-making related to food availability and security. As such, it is imperative to examine the suitability of different EO datasets, including their synergies, in respect to their ability to create products and tools for such practices and to guide effectively such decisions. This work aims at exploring the added value of the synergistic use of optical and radar data (from the Landsat TM and Advanced Synthetic Aperture Radar (ASAR) sensors respectively). Such information can help towards improving the accuracy of land cover classifications from EO datasets. As a case study, the region of Wales in the UK has been used. Two classifications—one based on optical data alone and another one developed from the synergy of optical and RADAR datasets acquired nearly, concurrently were developed for the studied region. Evaluation of the derived land/use cover maps was performed on the basis of the confusion matrix using validation points derived from a Phase 1 habitat map of Wales. The results showed 15% increase in overall accuracy (84% from 69%) and kappa coefficient (0.81 from 0.65) using the synergistic approach over the scenario where only optical data were used in the classification. In addition, McNemar’s test was used to assess the statistical significance of the obtained results. Results of this test provided further confirmed that the use of optical data synergistically with the radar data provides more accurate land use/cover maps in comparison with the use of optical data alone. Numéro de notice : A2019-461 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s12518-019-00258-7 date de publication en ligne : 13/04/2019 En ligne : https://doi.org/10.1007/s12518-019-00258-7 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93601 [article]

Improving public data for building segmentation from Convolutional Neural Networks (CNNs) for fused airborne lidar and image data using active contours / David Griffiths in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 154 (August 2019) . - pp 70 - 83 Titre : Improving public data for building segmentation from Convolutional Neural Networks (CNNs) for fused airborne lidar and image data using active contours Type de document : Article/Communication Auteurs : David Griffiths, Auteur ; Jan Boehm, Auteur Année de publication : 2019 Article en page(s) : pp 70 - 83 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] bati [Termes descripteurs IGN] classification par réseau neuronal convolutif [Termes descripteurs IGN] détection de contours [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] données publiques [Termes descripteurs IGN] fusion de données [Termes descripteurs IGN] image RVB [Termes descripteurs IGN] Royaume-Uni [Termes descripteurs IGN] scène urbaine [Termes descripteurs IGN] segmentation sémantique [Termes descripteurs IGN] zone rurale Résumé : (Auteur) Robust and reliable automatic building detection and segmentation from aerial images/point clouds has been a prominent field of research in remote sensing, computer vision and point cloud processing for a number of decades. One of the largest issues associated with deep learning methods is the high quantity of data required for training. To help address this we present a method to improve public GIS building footprint labels by using Morphological Geodesic Active Contours (MorphGACs). We demonstrate by improving the quality of building footprint labels for detection and semantic segmentation, more robust and reliable models can be obtained. We evaluate these methods over a large UK-based dataset of 24556 images containing 169835 building instances. This is achieved by training several Mask/Faster R-CNN and RetinaNet deep convolutional neural networks. Networks are supplied with both RGB and fused RGB-lidar data. We offer quantitative analysis on the benefits of the inclusion of depth data for building segmentation. By employing both methods we achieve a detection accuracy of 0.92 (mAP@0.5) and segmentation f1 scores of 0.94 over a 4911 test images ranging from urban to rural scenes. Numéro de notice : A2019-265 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.05.013 date de publication en ligne : 06/06/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.05.013 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93079 [article]

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Geographic space as a living structure for predicting human activities using big data / Bin Jiang in International journal of geographical information science IJGIS, Vol 33 n° 3-4 (March - April 2019)  

Public [article]  inInternational journal of geographical information science IJGIS > Vol 33 n° 3-4 (March - April 2019) . - pp 764 - 779 Titre : Geographic space as a living structure for predicting human activities using big data Type de document : Article/Communication Auteurs : Bin Jiang, Auteur ; Zheng Ren, Auteur Année de publication : 2019 Article en page(s) : pp 764 - 779 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] données issues des réseaux sociaux [Termes descripteurs IGN] données massives [Termes descripteurs IGN] information topologique [Termes descripteurs IGN] métadonnées [Termes descripteurs IGN] mise à l'échelle [Termes descripteurs IGN] OpenStreetMap [Termes descripteurs IGN] polygone de Thiessen [Termes descripteurs IGN] représentation des détails topographiques [Termes descripteurs IGN] Royaume-Uni Résumé : (Auteur) Inspired by Christopher Alexander’s conception of the world – space is not lifeless or neutral, but a living structure involving far more small things than large ones – a topological representation has been previously developed to characterize the living structure or the wholeness of geographic space. This paper further develops the topological representation and living structure for predicting human activities in geographic space. Based on millions of street nodes of the United Kingdom extracted from OpenStreetMap, we established living structures at different levels of scale in a nested manner. We found that tweet locations at different levels of scale, such as country and city, can be well predicted by the underlying living structure. The high predictability demonstrates that the living structure and the topological representation are efficient and effective for better understanding geographic forms. Based on this major finding, we argue that the topological representation is a truly multiscale representation, and point out that existing geographic representations are essentially single scale, so they bear many scale problems such as modifiable areal unit problem, the conundrum of length and the ecological fallacy. We further discuss on why the living structure is an efficient and effective instrument for structuring geospatial big data, and why Alexander’s organic worldview constitutes the third view of space. Numéro de notice : A2019-215 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1427754 date de publication en ligne : 31/01/2018 En ligne : https://doi.org/10.1080/13658816.2018.1427754 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92687 [article]

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Aerial data acquisition for a digital railway / James Dunthorne in GIM international, vol 32 n° 4 (July - August 2018)  

Public [article]  inGIM international > vol 32 n° 4 (July - August 2018) . - pp 26 - 27 Titre : Aerial data acquisition for a digital railway Type de document : Article/Communication Auteurs : James Dunthorne, Auteur Année de publication : 2018 Article en page(s) : pp 26 - 27 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes descripteurs IGN] acquisition de données [Termes descripteurs IGN] chambre à format moyen [Termes descripteurs IGN] image à ultra haute résolution [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] logiciel de visualisation [Termes descripteurs IGN] réseau ferroviaire [Termes descripteurs IGN] Royaume-Uni Résumé : (auteur) One of the major challenges facing railway networks is preventing failures in railway tracks. Avoiding potential track malfunctions means inspecting thousands of miles of track, while avoiding risk to inspectors and traffic interference. One innovative inspection methodology is to build a ‘digital railway’ – an accurate and dynamic visualisation tool to identify actual and potential track damage. Relying on the highest-quality data acquisition, a digital railway helps those responsible to make better informed decisions while planning and prioritising rail development, maintenance, repairs and renewal projects. This article outlines the use of such a tool in a UK railway project. Numéro de notice : A2018-243 Thématique : IMAGERIE Nature : Article En ligne : https://www.gim-international.com/content/article/aerial-data-acquisition-for-a- [...] Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90303 [article]

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Exploring the sensitivity of coastal inundation modelling to DEM vertical error / Harry West in International journal of geographical information science IJGIS, vol 32 n° 5-6 (May - June 2018)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 32 n° 5-6 (May - June 2018) . - pp 1172 - 1193 Titre : Exploring the sensitivity of coastal inundation modelling to DEM vertical error Type de document : Article/Communication Auteurs : Harry West, Auteur ; Michael Horswell, Auteur ; Nevil Quinn, Auteur Année de publication : 2018 Article en page(s) : pp 1172 - 1193 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] analyse de sensibilité [Termes descripteurs IGN] erreur en altitude [Termes descripteurs IGN] estuaire [Termes descripteurs IGN] incertitude géométrique [Termes descripteurs IGN] inondation [Termes descripteurs IGN] littoral [Termes descripteurs IGN] méthode de Monte-Carlo [Termes descripteurs IGN] modèle numérique de surface [Termes descripteurs IGN] montée du niveau de la mer [Termes descripteurs IGN] Royaume-Uni Résumé : (Auteur) As sea level is projected to rise throughout the twenty-first century due to climate change, there is a need to ensure that sea level rise (SLR) models accurately and defensibly represent future flood inundation levels to allow for effective coastal zone management. Digital elevation models (DEMs) are integral to SLR modelling, but are subject to error, including in their vertical resolution. Error in DEMs leads to uncertainty in the output of SLR inundation models, which if not considered, may result in poor coastal management decisions. However, DEM error is not usually described in detail by DEM suppliers; commonly only the RMSE is reported. This research explores the impact of stated vertical error in delineating zones of inundation in two locations along the Devon, United Kingdom, coastline (Exe and Otter Estuaries). We explore the consequences of needing to make assumptions about the distribution of error in the absence of detailed error data using a 1 m, publically available composite DEM with a maximum RMSE of 0.15 m, typical of recent LiDAR-derived DEMs. We compare uncertainty using two methods (i) the NOAA inundation uncertainty mapping method which assumes a normal distribution of error and (ii) a hydrologically correct bathtub method where the DEM is uniformly perturbed between the upper and lower bounds of a 95% linear error in 500 Monte Carlo Simulations (HBM+MCS). The NOAA method produced a broader zone of uncertainty (an increase of 134.9% on the HBM+MCS method), which is particularly evident in the flatter topography of the upper estuaries. The HBM+MCS method generates a narrower band of uncertainty for these flatter areas, but very similar extents where shorelines are steeper. The differences in inundation extents produced by the methods relate to a number of underpinning assumptions, and particularly, how the stated RMSE is interpreted and used to represent error in a practical sense. Unlike the NOAA method, the HBM+MCS model is computationally intensive, depending on the areas under consideration and the number of iterations. We therefore used the HBM+ MCS method to derive a regression relationship between elevation and inundation probability for the Exe Estuary. We then apply this to the adjacent Otter Estuary and show that it can defensibly reproduce zones of inundation uncertainty, avoiding the computationally intensive step of the HBM+MCS. The equation-derived zone of uncertainty was 112.1% larger than the HBM+MCS method, compared to the NOAA method which produced an uncertain area 423.9% larger. Each approach has advantages and disadvantages and requires value judgements to be made. Their use underscores the need for transparency in assumptions and communications of outputs. We urge DEM publishers to move beyond provision of a generalised RMSE and provide more detailed estimates of spatial error and complete metadata, including locations of ground control points and associated land cover. Numéro de notice : A2018-203 Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1444165 date de publication en ligne : 14/03/2018 En ligne : https://doi.org/10.1080/13658816.2018.1444165 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89874 [article]

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Improving the analysis of biogeochemical patterns associated with internal waves in the strait of Gibraltar using remote sensing images / Gabriel Navarro in Estuarine, Coastal and Shelf Science, vol 204 (May 2018)  

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A review of the effects of forest management intensity on ecosystem services for northern European temperate forests with a focus on the UK / Louise Sing in Forestry, an international journal of forest research, vol 91 n° 2 (April 2018)  

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Graph-based matching of points-of-interest from collaborative geo-datasets / Tessio Novack in ISPRS International journal of geo-information, vol 7 n° 3 (March 2018)  

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Extraction of pluvial flood relevant volunteered geographic information (VGI) by deep learning from user generated texts and photos / Yu Feng in ISPRS International journal of geo-information, vol 7 n° 2 (February 2018)  

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Pensez à l'échelle du monde pour maîtriser le temps en France et en Grande-Bretagne, 1870-1914 / Isabelle Avila in Cartes & Géomatique, n° 234 (décembre 2017) 

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Depicting urban boundaries from a mobility network of spatial interactions : a case study of Great Britain with geo-located Twitter data / Junjun Yin in International journal of geographical information science IJGIS, vol 31 n° 7-8 (July - August 2017)  

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A GIS approach to exploring monetary value on enclosure era property-related maps / Christopher Macdonald Hewitt in Cartographic journal (the), Vol 54 n° 2 (May 2017)  

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A method for matching crowd-sourced and authoritative geospatial data / Heshan Du in Transactions in GIS, vol 21 n° 2 (April 2017)  

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Etude de l'impact d'un projet de développement sur les propriétés avoisinantes / Sylvain Jourdan (2017) 

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Incorporating movement in species distribution models: how do simulations of dispersal affect the accuracy and uncertainty of projections? / Paul Holloway in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)  

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