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Geomorphic Change Detection Using Cost-Effective Structure-from-Motion Photogrammetry: Evaluation of Direct Georeferencing from Consumer-Grade UAS at Orewa Beach (New Zealand) / Stéphane Bertin in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 5 (May 2020)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 5 (May 2020) . - pp 189 - 198 Titre : Geomorphic Change Detection Using Cost-Effective Structure-from-Motion Photogrammetry: Evaluation of Direct Georeferencing from Consumer-Grade UAS at Orewa Beach (New Zealand) Type de document : Article/Communication Auteurs : Stéphane Bertin, Auteur ; Benjamin Levy, Auteur ; Trevor Gee, Auteur ; Patrice Delmas, Auteur Année de publication : 2020 Article en page(s) : pp 189 - 198 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] détection de changement [Termes descripteurs IGN] géomorphologie locale [Termes descripteurs IGN] géoréférencement direct [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] Nouvelle-Zélande [Termes descripteurs IGN] plage [Termes descripteurs IGN] structure-from-motion Résumé : (Auteur) Unmanned aerial systems (UAS) and structure-from-motion photogrammetry are transforming the way we produce topo- graphic data, with applications covering many disciplines in the geosciences, including coastal studies. To overcome limitations of ground control points (GCPs), we evaluate direct georeferencing (DG) of consumer UAS imagery for the cost-effective measurement of beach topography. Using DG, camera positions determined with on-board instruments provide air control points for photogrammetry, obviating the need for presurveyed GCPs. We validate the approach at Orewa Beach, New Zealand, achieving vertical accuracies similar to light detection and ranging ( Numéro de notice : A2020-187 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.5.289 date de publication en ligne : 01/05/2020 En ligne : https://doi.org/10.14358/PERS.86.5.289 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95037 [article]

Comparative usability of an augmented reality sandtable and 3D GIS for education / Antoni B. Moore in International journal of geographical information science IJGIS, vol 34 n° 2 (February 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 2 (February 2020) . - pp 229 - 250 Titre : Comparative usability of an augmented reality sandtable and 3D GIS for education Type de document : Article/Communication Auteurs : Antoni B. Moore, Auteur ; Benjamin Daniel, Auteur ; greg Leonard, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 229 - 250 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique [Termes descripteurs IGN] enseignement supérieur [Termes descripteurs IGN] hydrologie [Termes descripteurs IGN] modèle numérique de terrain [Termes descripteurs IGN] modélisation 3D [Termes descripteurs IGN] Nouvelle-Zélande [Termes descripteurs IGN] réalité augmentée [Termes descripteurs IGN] réalité de terrain [Termes descripteurs IGN] réalité virtuelle [Termes descripteurs IGN] sable [Termes descripteurs IGN] test de performance Résumé : (auteur) Augmented Reality (AR) sandtables facilitate the shaping of sand to form a surface that is transformed into a digital terrain map which is projected back onto the sand. Although a mature technology, there are still few instances of sandtables being used in surface analysis. Fundamentally there has not been any reported formal assessment of how well sandtables perform in an educational context compared to other conventional learning environments. We compared learning outcomes from using an AR sandtable versus a conventional 3D GIS to convey key concepts in terrain and hydrological analyses via usability and knowledge testing. Overall results from students at a research-intensive New Zealand university reveal a faster task performance and more learning satisfaction when using the sandtable to undertake experimental tasks. Effectiveness and knowledge quiz results revealed no significant difference between the technologies though there was a trend for more accurate answers with 3D GIS tasks. Student learning wise, the sandtable integrated core concepts (especially morphometry) more effectively though both technologies were otherwise similar. We conclude that sandtables have high potential in geospatial teaching, fostering accessible and engaging means of introducing terrain and hydrological concepts, prior to undertaking a more accurate and precise surface analysis with 3D GIS. Numéro de notice : A2020-028 Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1656810 date de publication en ligne : 27/08/2019 En ligne : https://doi.org/10.1080/13658816.2019.1656810 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94481 [article]

Optimal segmentation of high spatial resolution images for the classification of buildings using random forests / James Bialas in International journal of applied Earth observation and geoinformation, vol 82 (October 2019)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 82 (October 2019) . - pp Titre : Optimal segmentation of high spatial resolution images for the classification of buildings using random forests Type de document : Article/Communication Auteurs : James Bialas, Auteur ; Thomas Oommen, Auteur ; Timothy C. Havens, Auteur Année de publication : 2019 Article en page(s) : pp Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] analyse d'image orientée objet [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] bâtiment [Termes descripteurs IGN] Christchurch [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] dommage matériel [Termes descripteurs IGN] image à haute résolution [Termes descripteurs IGN] image aérienne [Termes descripteurs IGN] précision de la classification [Termes descripteurs IGN] qualité du processus [Termes descripteurs IGN] segmentation d'image [Termes descripteurs IGN] séisme [Termes descripteurs IGN] zone urbaine Résumé : (auteur) In the application of machine learning to geographic object based image analysis, several parameters influence overall classifier performance. One of the first parameters is segmentation size—for example, how many pixels should be grouped together to form an image object. Often, trial and error methods are used to obtain segmentation parameters that best delineate the borders of real world objects. Several attempts at automated methods have produced promising results, but manual intervention is still necessary. Meanwhile, numerous measures of segmentation quality have been defined, but their relationship to classifier performance is not then directly shown. For example, as measures of segmentation quality improve, do classification results improve as well? Our work considers the problem of building classification in high resolution aerial imagery of urban areas. Based on user defined training polygons generated with or without a reference segmentation, we have found several measures of segmentation quality and feature performance that can help users narrow the range of appropriate segmentations. Furthermore, our work finds that given this range, performance of machine learning algorithms remains relatively constant for any given segmentation as long as features used for classification are chosen correctly. We find that the range of scale parameters capable of producing an accurate classification is much broader than typically assumed and trial and error methods for finding this parameter may be an acceptable approach. Numéro de notice : A2019-472 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2019.06.005 date de publication en ligne : 08/06/2019 En ligne : https://doi.org/https://doi.org/10.1016/j.jag.2019.06.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93632 [article]

Simulation of urban expansion via integrating artificial neural network with Markov chain – cellular automata / Tingting Xu in International journal of geographical information science IJGIS, vol 33 n° 10 (October 2019)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 33 n° 10 (October 2019) . - pp 1960 - 1983 Titre : Simulation of urban expansion via integrating artificial neural network with Markov chain – cellular automata Type de document : Article/Communication Auteurs : Tingting Xu, Auteur ; Jay Gao, Auteur ; Giovanni Coco, Auteur Année de publication : 2019 Article en page(s) : pp 1960 - 1983 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] analyse diachronique [Termes descripteurs IGN] Auckland [Termes descripteurs IGN] automate cellulaire [Termes descripteurs IGN] base de données d'occupation du sol [Termes descripteurs IGN] chaîne de Markov [Termes descripteurs IGN] classification par réseau neuronal [Termes descripteurs IGN] croissance urbaine [Termes descripteurs IGN] étalement urbain [Termes descripteurs IGN] Kappa de Cohen [Termes descripteurs IGN] modèle de simulation [Termes descripteurs IGN] morphologie urbaine [Termes descripteurs IGN] optimisation (mathématiques) Résumé : (auteur) Accurate simulations and predictions of urban expansion are critical to manage urbanization and explicitly address the spatiotemporal trends and distributions of urban expansion. Cellular Automata integrated Markov Chain (CA-MC) is one of the most frequently used models for this purpose. However, the urban suitability index (USI) map produced from the conventional CA-MC is either affected by human bias or cannot accurately reflect the possible nonlinear relations between driving factors and urban expansion. To overcome these limitations, a machine learning model (Artificial Neural Network, ANN) was integrated with CA-MC instead of the commonly used Analytical Hierarchy Process (AHP) and Logistic Regression (LR) CA-MC models. The ANN was optimized to create the USI map and then integrated with CA-MC to spatially allocate urban expansion cells. The validated results of kappa and fuzzy kappa simulation indicate that ANN-CA-MC outperformed other variously coupled CA-MC modelling approaches. Based on the ANN-CA-MC model, the urban area in South Auckland is predicted to expand to 1340.55 ha in 2026 at the expense of non-urban areas, mostly grassland and open-bare land. Most of the future expansion will take place within the planned new urban growth zone. Numéro de notice : A2019-428 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1600701 date de publication en ligne : 05/04/2019 En ligne : https://doi.org/10.1080/13658816.2019.1600701 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93561 [article]

Unmanned aerial vehicles (UAVs) for monitoring macroalgal biodiversity: comparison of RGB and multispectral imaging sensors for biodiversity assessments / Leigh Tait in Remote sensing, vol 11 n° 19 (October 2019)  

Public [article]  inRemote sensing > vol 11 n° 19 (October 2019) . - 18 p. Titre : Unmanned aerial vehicles (UAVs) for monitoring macroalgal biodiversity: comparison of RGB and multispectral imaging sensors for biodiversity assessments Type de document : Article/Communication Auteurs : Leigh Tait, Auteur ; Jochen Bind, Auteur ; Hannah Charan-Dixon, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : 18 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] algue [Termes descripteurs IGN] biodiversité [Termes descripteurs IGN] changement climatique [Termes descripteurs IGN] estran [Termes descripteurs IGN] habitat (nature) [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] image multibande [Termes descripteurs IGN] image RVB [Termes descripteurs IGN] Kappa de Cohen [Termes descripteurs IGN] Nouvelle-Zélande [Termes descripteurs IGN] orthophotoplan numérique [Termes descripteurs IGN] réflectance spectrale [Termes descripteurs IGN] surveillance du littoral Résumé : (auteur) Developments in the capabilities and affordability of unmanned aerial vehicles (UAVs) have led to an explosion in their use for a range of ecological and agricultural remote sensing applications. However, the ubiquity of visible light cameras aboard readily available UAVs may be limiting the application of these devices for fine-scale, high taxonomic resolution monitoring. Here we compare the use of RGB and multispectral cameras deployed aboard UAVs for assessing intertidal and shallow subtidal marine macroalgae to a high taxonomic resolution. Our results show that the diverse spectral profiles of marine macroalgae naturally lend themselves to remote sensing and habitat classification. Furthermore, we show that biodiversity assessments, particularly in shallow subtidal habitats, are enhanced using six-band discrete wavelength multispectral sensors (81% accuracy, Cohen’s Kappa) compared to three-band broad channel RGB sensors (79% accuracy, Cohen’s Kappa) for 10 habitat classes. Combining broad band RGB signals and narrow band multispectral sensing further improved the accuracy of classification with a combined accuracy of 90% (Cohen’s Kappa). Despite notable improvements in accuracy with multispectral imaging, RGB sensors were highly capable of broad habitat classification and rivaled multispectral sensors for classifying intertidal habitats. High spatial scale monitoring of turbid exposed rocky reefs presents a unique set of challenges, but the limitations of more traditional methods can be overcome by targeting ideal conditions with UAVs. Numéro de notice : A2019-553 Thématique : BIODIVERSITE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs11192332 date de publication en ligne : 08/10/2019 En ligne : https://doi.org/10.3390/rs11192332 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94206 [article]

Thinking outside the square: Evidence that plot shape and layout in forest inventories can bias estimates of stand metrics / Thomas S. H. Paul in Methods in ecology and evolution, vol 10 n° 3 (March 2019)  

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Comparison of high-density LiDAR and satellite photogrammetry for forest inventory / Grant D. Pearse in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)  

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The New Zealand gravimetric quasigeoid model 2017 that incorporates nationwide airborne gravimetry / Jack C. McCubbine in Journal of geodesy, vol 92 n° 8 (August 2018)  

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Augmented reality and maps : new possibilities for engaging with geographic data / Gabriel Henrique de Almeida Pereira in Cartographic journal (the), Vol 54 n° 4 (November 2017)  

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An investigation into the performance of real-time GPS + GLONASS Precise Point Positioning (PPP) in New Zealand / Ken Harima in Journal of applied geodesy, vol 11 n° 3 (September 2017)  

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Geospatial big data and archaeology: Prospects and problems too great to ignore / Mark D. McCoy in Journal of archaeological science, vol 8x (2017)  

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A spatial data infrastructure approach for the characterization of New Zealand's groundwater systems / Alexander Kmoch in Transactions in GIS, vol 20 n° 4 (August 2016)  

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Empirical determination of geometric parameters for selective omission in a road network / Qi Zhou in International journal of geographical information science IJGIS, vol 30 n° 1-2 (January - February 2016)  

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Using integrated visualization techniques to investigate associations between cardiovascular health outcomes and residential migration in Auckland, New Zealand / Jinfeng Zhao in Cartography and Geographic Information Science, Vol 42 n° 5 (November 2015)  

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Flying high with a UAS adventurer / Anonyme in Position, n° 79 (October - November 2015)

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