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Analytic hierarchy process based spatial biodiversity impact assessment model of highway broadening in Sikkim Himalaya / Polash Banerjee in Geocarto international, vol 35 n° 5 ([01/04/2020])  

Public [article]  inGeocarto international > vol 35 n° 5 [01/04/2020] . - pp 470 - 493 Titre : Analytic hierarchy process based spatial biodiversity impact assessment model of highway broadening in Sikkim Himalaya Type de document : Article/Communication Auteurs : Polash Banerjee, Auteur ; Mrinal K. Ghose, Auteur ; Ratika Pradham, Auteur Année de publication : 2020 Article en page(s) : pp 470 - 493 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de sensibilité [Termes IGN] autoroute [Termes IGN] biodiversité [Termes IGN] étude d'impact [Termes IGN] Himalaya [Termes IGN] montagne [Termes IGN] parcelle forestière [Termes IGN] processus d'analyse hiérarchique [Termes IGN] projet routier Résumé : (auteur) Spatial impacts of highway projects on biodiversity of North-Eastern Himalaya remains largely unexplored. Usually a number of ecological criteria are required in biodiversity impact assessment. However, a wide set of such criteria can be overwhelming for the decision-makers to assess the viability of such projects. SBIAM uses landscape metrics and experts’ opinion to create a single composite biodiversity value map. The weighted area loss under various project alternatives estimated from Biodiversity Value Map is compared to identify the most viable alternative. SBIAM uses AHP and curve fitting method in the biodiversity estimation. The study indicates that the highway broadening project in the study area will cause a moderate biodiversity loss. Sensitivity analysis of SBIAM indicates its robustness, and shows that forest patches near the highway are most sensitive to disturbances and patch proximity. SBIAM can be applied in varied spatial scales, terrains and development projects as a decision support tool. Numéro de notice : A2020-142 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1520924 Date de publication en ligne : 22/10/2018 En ligne : https://doi.org/10.1080/10106049.2018.1520924 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94768 [article]

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Automated extraction of lane markings from mobile LiDAR point clouds based on fuzzy inference / Heidar Rastiveis in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 160 (February 2020) . - pp 149 - 166 Titre : Automated extraction of lane markings from mobile LiDAR point clouds based on fuzzy inference Type de document : Article/Communication Auteurs : Heidar Rastiveis, Auteur ; Alireza Shams, Auteur ; Wayne A. Sarasua, Auteur ; Jonathan Li, Auteur Année de publication : 2020 Article en page(s) : pp 149 - 166 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] autoroute [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] extraction automatique [Termes IGN] extraction de points [Termes IGN] extraction du réseau routier [Termes IGN] Inférence floue [Termes IGN] lidar mobile [Termes IGN] modélisation 3D [Termes IGN] semis de points [Termes IGN] transformation de Hough Résumé : (Auteur) Mobile LiDAR systems (MLS) are rapid and accurate technologies for acquiring three-dimensional (3D) point clouds that can be used to generate 3D models of road environments. Because manual extraction of desirable features such as road traffic signs, trees, and pavement markings from these point clouds is tedious and time-consuming, automatic information extraction of these objects is desirable. This paper proposes a novel automatic method to extract pavement lane markings (LMs) using point attributes associated with the MLS point cloud based on fuzzy inference. The proposed method begins with dividing the MLS point cloud into a number of small sections (e.g. tiles) along the route. After initial filtering of non-ground points, each section is vertically aligned. Next, a number of candidate LM areas are detected using a Hough Transform (HT) algorithm and considering a buffer area around each line. The points inside each area are divided into “probable-LM” and “non-LM” clusters. After extracting geometric and radiometric descriptors for the “probable-LM” clusters and analyzing them in a fuzzy inference system, true-LM clusters are eventually detected. Finally, the extracted points are enhanced and transformed back to their original position. The efficiency of the method was tested on two different point cloud datasets along 15.6 km and 9.5 km roadway corridors. Comparing the LMs extracted using the algorithm with the manually extracted LMs, 88% of the LM lines were successfully extracted in both datasets. Numéro de notice : A2020-047 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.12.009 Date de publication en ligne : 20/12/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.12.009 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94558 [article]

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Landslide susceptibility mapping using maximum entropy and support vector machine models along the highway corridor, Garhwal Himalaya / Vijendra Kumar Pandey in Geocarto international, vol 35 n° 2 ([01/02/2020])  

Public [article]  inGeocarto international > vol 35 n° 2 [01/02/2020] . - pp 168 - 187 Titre : Landslide susceptibility mapping using maximum entropy and support vector machine models along the highway corridor, Garhwal Himalaya Type de document : Article/Communication Auteurs : Vijendra Kumar Pandey, Auteur ; Hamid Reza Pourghasemi, Auteur ; Milap Chand Sharma, Auteur Année de publication : 2020 Article en page(s) : pp 168 - 187 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage automatique [Termes IGN] autoroute [Termes IGN] classification dirigée [Termes IGN] effondrement de terrain [Termes IGN] entropie maximale [Termes IGN] Himalaya [Termes IGN] image IRS-LISS [Termes IGN] image Landsat-8 [Termes IGN] Linear Imaging Self-Scanning System [Termes IGN] modèle statistique [Termes IGN] mousson [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] séparateur à vaste marge [Termes IGN] test statistique Résumé : (Auteur) The main objective of this study to produce landslide susceptibility zones using maximum entropy (MaxEnt) and support vector machine (SVM) data-driven models along the Tipari to Ghuttu highway corridors in the Garhwal Himalaya. A landslide inventory has been prepared through field surveys and LISS-IV and Landsat 8 satellite images. The datasets of 85 landslides were categorised into training and test sets. In this study 11 landslide conditioning variables were used that are; altitude, slope angle, aspect, plan curvature, topographic wetness index, normalised difference vegetation index (NDVI), land use, soil texture, distance to rivers, distance to faults, and distance to the road. The result produced using MaxEnt and SVM model were subsequently validated using receiver operating characteristics curve (ROC) with test sets of landslide dataset. Both the models have good prediction capabilities. MaxEnt has ROC value of 0.78 while SVM has the highest prediction rate of 0.85. Numéro de notice : A2020-036 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1510038 Date de publication en ligne : 20/09/2018 En ligne : https://doi.org/10.1080/10106049.2018.1510038 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94519 [article]

Accuracy assessment of speed values calculated from GNSS tracks of roads obtained from VGI / Antonio Tomás Mozas-Calvache in Survey review, vol 51 n° 367 (July 2019)  

Public [article]  inSurvey review > vol 51 n° 367 (July 2019) . - pp 354 - 363 Titre : Accuracy assessment of speed values calculated from GNSS tracks of roads obtained from VGI Type de document : Article/Communication Auteurs : Antonio Tomás Mozas-Calvache, Auteur Année de publication : 2019 Article en page(s) : pp 354 - 363 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes IGN] autoroute [Termes IGN] données localisées des bénévoles [Termes IGN] positionnement différentiel [Termes IGN] trace GPS [Termes IGN] vitesse Résumé : (Auteur) This study describes the results of an assessment of the accuracy of relative measures between two points, and more specifically of speed values, obtained from Global Positioning Satellite Systems (GNSS) tracks acquired by contributors of Volunteered Geographic Information (VGI). The VGI does not usually include information about the positional accuracy of the trackpoints neither of speed values derived from these positions. Consequently, the assessment is based on a field test that consisted of a vehicle which travelled a highway with a set of Global Positioning System (GPS) devices like those commonly used by VGI contributors. These devices captured positions of trackpoints with a time interval of 1 second. Additionally, a more accurate geodetic RTK–GNSS receptor controlled these positions. The paper describes the methodology employed, taking into account several parameters such as the acquisition time interval, the accuracy of control positions, etc. The results have demonstrated the viability of the methodology applied, the possible use of VGI in order to determine the speed values of the trackpoints and the possible improvement in the accuracy achieved with the increase of the distance between trackpoints (and as a consequence of time interval), but with the disadvantage of a reduction in the quantity of trackpoints. Thus, several values of time intervals have been suggested, considering the accuracy required. Numéro de notice : A2019-363 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2018.1460069 Date de publication en ligne : 16/04/2018 En ligne : https://doi.org/10.1080/00396265.2018.1460069 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93443 [article]

Exploitation of deep learning in the automatic detection of cracks on paved roads / Won Mo Jung in Geomatica [en ligne], vol 73 n° 2 (June 2019)  

Public [article]  inGeomatica [en ligne] > vol 73 n° 2 (June 2019) . - pp 29 - 44 Titre : Exploitation of deep learning in the automatic detection of cracks on paved roads Type de document : Article/Communication Auteurs : Won Mo Jung, Auteur ; Faizaan Naveed, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 29 - 44 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] autoroute [Termes IGN] chaussée [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] détection d'objet [Termes IGN] Ontario (Canada) Mots-clés libres : fissure Résumé : (auteur) With the advance of deep learning networks, their applications in the assessment of pavement conditions are gaining more attention. A convolutional neural network (CNN) is the most commonly used network in image classification. In terms of pavement assessment, most existing CNNs are designed to only distinguish between cracks and non-cracks. Few networks classify cracks in different levels of severity. Information on the severity of pavement cracks is critical for pavement repair services. In this study, the state-of-the-art CNN used in the detection of pavement cracks was improved to localize the cracks and identify their distress levels based on three categories (low, medium, and high). In addition, a fully convolutional network (FCN) was, for the first time, utilized in the detection of pavement cracks. These designed architectures were validated using the data acquired on four highways in Ontario, Canada, and compared with the ground truth that was provided by the Ministry of Transportation of Ontario (MTO). The results showed that with the improved CNN, the prediction precision on a series of test image patches were 72.9%, 73.9%, and 73.1% for cracks with the severity levels of low, medium, and high, respectively. The precision for the FCN was tested on whole pavement images, resulting in 62.8%, 63.3%, and 66.4%, respectively, for cracks with the severity levels of low, medium, and high. It is worth mentioning that the ground truth contained some uncertainties, which partially contributed to the relatively low precision. Numéro de notice : A2019-657 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1139/geomat-2019-0008 En ligne : https://doi.org/10.1139/geomat-2019-0008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98324 [article]

Roads, lines, and boundary objects : a critical cartographic look at the development of the Serengeti highway / Eric J. Lovell in Cartographica, vol 52 n° 4 (Winter 2017)  

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Information géographique environnementale et conception d'infrastructure : quel détail pour l'information partagée ? / Charles-Edouard Tolmer in XYZ, n° 147 (juin - août 2016)

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Surveying a mountain highway with UAS : getting accurate results in a rough area / Matteo Luccio in Geoinformatics, vol 18 n° 7 (October - November 2015)

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La télédétection au service des études urbaines : expansion de la ville de Pondichéry entre 1973 et 2009 / Emilien Kieffer in Géomatique expert, n° 95 (01/11/2013)  

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Assessing the effect of landscape change on fauna by agent-based model simulation / Laurence Jolivet (2013)  

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A practical experience on road network generalisation for production device / Jérémy Renard (2013)    

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Shanghai subway tunnels and highways monitoring through Cosmo-SkyMed Persistent Scatterers / Daniele Perissin in ISPRS Journal of photogrammetry and remote sensing, vol 73 (September 2012)

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Visibility monitoring using conventional roadside cameras : Emerging applications / Raouf Babari in Transportation Research - Part C: Emerging Technologies, vol 22 (June 2012)  

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Construction of digital 3D highway model using stereo IKONOS satellite imagery / Ahmed Shaker in Geocarto international, vol 26 n° 1 (February 2011)  

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Automatic identification of high streets and classification of urban land use in large scale topographic database / Omair Chaudhry (2010) 

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