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Multi‑constellation GNSS interferometric reflectometry for the correction of long-term snow height retrieval on sloping topography / Wei Zhou in GPS solutions, vol 26 n° 4 (October 2022)  

Public [article]  inGPS solutions > vol 26 n° 4 (October 2022) . - n° 140 Titre : Multi‑constellation GNSS interferometric reflectometry for the correction of long-term snow height retrieval on sloping topography Type de document : Article/Communication Auteurs : Wei Zhou, Auteur ; Liangke Huang, Auteur ; Bing Ji, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 140 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] hauteur (coordonnée) [Termes IGN] manteau neigeux [Termes IGN] pente [Termes IGN] Ransac (algorithme) [Termes IGN] rapport signal sur bruit [Termes IGN] réflectométrie par GNSS [Termes IGN] signal GNSS [Termes IGN] système de référence altimétrique [Termes IGN] topographie locale [Termes IGN] transformation en ondelettes [Termes IGN] valeur aberrante [Vedettes matières IGN] Altimétrie Résumé : (auteur) Snow is a key parameter for global climate and hydrological systems. Global Navigation Satellite System interferometric reflectometry (GNSS-IR) has been applied to accurately monitor snow height (SH) with low cost and high temporal–spatial resolution. We proposed an improved GNSS-IR method using detrended signal-to-noise ratio (δSNR) arcs corresponding to multipath reflection tracks with different azimuths. After using wavelet decomposition and random sample consensus, noise with various frequencies for SNR arcs and outliers of reflector height (RH) estimations have been sequentially mitigated to enhance the availability of the proposed method. Thus, a height datum based on the ground RHs retrieved from multi-GNSS SNR data is established to compensate for the influence of topography variation with different azimuths in SH retrieval. The approximately 3-month δSNR datasets collected from three stations deployed on sloping topography were used to retrieve SH and compared with the existing method and in situ measurements. The results show that the root mean square errors of the retrievals derived from the proposed method for the three sites are between 4 and 8 cm, and the corresponding correlation surpasses 0.95 when compared to the reference SH datasets. Additionally, we compare the performance of a retrieval with the existing GNSS-IR Web App, and it shows an improvement in RMSE of about 7 cm. Furthermore, because topography variation has been considered, the average correction of SH retrievals is between 2 and 4 cm. The solution with the proposed method helps develop the applications of the GNSS-IR technique on complex topography. Numéro de notice : A2022-712 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1007/s10291-022-01333-0 Date de publication en ligne : 15/09/2022 En ligne : https://doi.org/10.1007/s10291-022-01333-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101590 [article]

Predicting the variability in pedestrian travel rates and times using crowdsourced GPS data / Michael J. Campbell in Computers, Environment and Urban Systems, vol 97 (October 2022)  

Public [article]  inComputers, Environment and Urban Systems > vol 97 (October 2022) . - n° 101866 Titre : Predicting the variability in pedestrian travel rates and times using crowdsourced GPS data Type de document : Article/Communication Auteurs : Michael J. Campbell, Auteur ; Philip E. Dennison, Auteur ; Matthew Thompson, Auteur Année de publication : 2022 Article en page(s) : n° 101866 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] base de données localisées [Termes IGN] Californie (Etats-Unis) [Termes IGN] chemin le moins coûteux, algorithme du [Termes IGN] données issues des réseaux sociaux [Termes IGN] durée de trajet [Termes IGN] mobilité urbaine [Termes IGN] navigation pédestre [Termes IGN] pente [Termes IGN] planification urbaine [Termes IGN] trace GPS [Termes IGN] Utah (Etas-Unis) Résumé : (auteur) Accurately predicting pedestrian travel times is critically valuable in emergency response, wildland firefighting, disaster management, law enforcement, and urban planning. However, the relationship between pedestrian movement and landscape conditions is highly variable between individuals, making it difficult to estimate how long it will take broad populations to get from one location to another on foot. Although functions exist for predicting travel rates, they typically oversimplify the inherent variability of pedestrian travel by assuming the effects of landscapes on movement are universal. In this study, we present an approach for predicting the variability in pedestrian travel rates and times using a large, crowdsourced database of GPS tracks. Acquired from the outdoor recreation website AllTrails, these tracks represent nearly 2000 hikes on a diverse range of trails in Utah and California, USA. We model travel rates as a function of the slope of the terrain by generating a series of non-linear percentile models from the 2.5 th to the 97.5 th by 2.5 percentiles. The 50 th percentile model, representing the hiking speed of the typical individual, demonstrates marked improvement over existing slope-travel rate functions when compared to an independent test dataset. Our results demonstrate novel capacity to estimate travel time variability, with modeled percentiles being able to predict actual percentiles with less than 10% error. Travel rate functions can also be applied to least cost path analysis to provide variability in travel times. Numéro de notice : A2022-599 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.compenvurbsys.2022.101866 Date de publication en ligne : 20/08/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101866 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101452 [article]

Assessing road accidents in spatial context via statistical and non-statistical approaches to detect road accident hotspot using GIS / Yegane Khosravi in Geodetski vestnik, vol 66 n° 3 (September - November 2022)  

Public [article]  inGeodetski vestnik > vol 66 n° 3 (September - November 2022) . - pp 412 - 431 Titre : Assessing road accidents in spatial context via statistical and non-statistical approaches to detect road accident hotspot using GIS Type de document : Article/Communication Auteurs : Yegane Khosravi, Auteur ; Farhad Hosseinali, Auteur ; Mostafa Adresi, Auteur Année de publication : 2022 Article en page(s) : pp 412 - 431 Note générale : bibliographie Langues : Anglais (eng) Slovène (slv) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] accident de la route [Termes IGN] analyse de groupement [Termes IGN] autocorrélation spatiale [Termes IGN] classification par nuées dynamiques [Termes IGN] corrélation automatique de points homologues [Termes IGN] distance de Manhattan [Termes IGN] estimation par noyau [Termes IGN] Iran [Termes IGN] méthode statistique [Termes IGN] pente [Termes IGN] processus de hiérarchisation analytique [Termes IGN] regroupement de données [Termes IGN] système d'information géographique Résumé : (auteur) Road accidents are among the most critical causes of fatality, personal injuries, and financial damage worldwide. Identifying accident hotspots and the causes of accidents and improving the condition of these hotspots is an economical way to improve road traffic safety. In this study, to identify the accident hotspots of “Dehbala” road located in Yazd province-Iran, statistical and non-statistical clustering methods were used. First, the weighting of the criteria was performed by an expert using the AHP method. Hence, the spatial correlation of slope and curvature was calculated by Global Moran’I. Anselin Local Moran index and Getis-Ord Gi* and Kernel Density Estimation were used to identify accident hotspots based on accident location due to the density of points. As a result, four accident hotspots were obtained by the Anselin Local Moran index, three accident hotspots by Getis-Ord Gi*and one accident-prone area were obtained by Kernel Density Estimation method. Three algorithms, k-means, k-medoids, and DBSCAN, were used to identify accident-prone areas or points using non-statistical methods. The dense cluster of each method was considered as an accident-prone cluster. Then the results of statistical and non- statistical methods were intersected with each other and the final accident-prone area was obtained. This study revealed the effect of geometric charcateristics of the road (slope and curvature) on the occurance of accidents. Numéro de notice : A2022-781 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.15292/geodetski-vestnik.2022.03.412-431 Date de publication en ligne : 04/08/2022 En ligne : https://doi.org/10.15292/geodetski-vestnik.2022.03.412-431 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101864 [article]

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Discontinuity interpretation and identification of potential rockfalls for high-steep slopes based on UAV nap-of-the-object photogrammetry / Wei Wang in Computers & geosciences, vol 166 (September 2022)  

Public [article]  inComputers & geosciences > vol 166 (September 2022) . - n° 105191 Titre : Discontinuity interpretation and identification of potential rockfalls for high-steep slopes based on UAV nap-of-the-object photogrammetry Type de document : Article/Communication Auteurs : Wei Wang ; Wenbo Zhao, Auteur ; Bo Chai, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 105191 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] Chine [Termes IGN] discontinuité [Termes IGN] éboulement [Termes IGN] extraction de données [Termes IGN] front rocheux [Termes IGN] image à haute résolution [Termes IGN] image captée par drone [Termes IGN] matrice [Termes IGN] pente [Termes IGN] photogrammétrie aérienne [Termes IGN] profondeur [Termes IGN] risque naturel [Termes IGN] semis de points [Termes IGN] texture d'image Résumé : (auteur) Discontinuity extraction and interpretation of fractured masses is of high importance when analyzing rock slope stability. Regarding high-steep slopes, which are areas that are difficult to reach, traditional methods to obtain discontinuities, such as the sample window method (SWM), are unlikely to be implemented, resulting in challenges for the identification of potential rockfalls. With the development of the unmanned ariel vehicle (UAV) technology, discontinuity extraction can overcome by noncontact photogrammetry. However, there is still a lack of comprehensive and practical solutions to fulfill rockfall identification from field investigation to in-door analysis. For this purpose, a practical case study was carried out in Wanzhou, Chongqing, China, where a 400 m vertical rock slope prone to rockfall was collected as a typical example. The centimeter-level 3D Textured Digital Outcrop Model (TDOM) and dense Point Cloud (PC) were established using high-resolution photos acquired by nap-of-the-object photogrammetry. The discontinuity of the fractured mass was interpreted by fully taking advantage of both 2D images (texture information-dominated) and 3D PCs (depth information-dominated). Furthermore, a new parameter rock cavity rate (RCR) and the corresponding semiautomatic extraction method based on point clouds are proposed. Subsequently, the possibility of various failure modes and their joint combinations were determined by kinematic analysis. Finally, the rock slope stability was determined using a matrix that considers the slope mass rating (SMR) value and the parameter RCR. The proposed process flow and relevant techniques in this study provide an operable and practical solution for further application regarding discontinuity interpretation and potential rockfall identification on high-steep slopes. Numéro de notice : A2022-655 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.cageo.2022.105191 Date de publication en ligne : 08/07/2022 En ligne : https://doi.org/10.1016/j.cageo.2022.105191 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101504 [article]

An investigation into heat storage by adopting local climate zones and nocturnal-diurnal urban heat island differences in the Tokyo Prefecture / Christopher O'Malley in Sustainable Cities and Society, vol 83 (August 2022)  

Public [article]  inSustainable Cities and Society > vol 83 (August 2022) . - n° 103959 Titre : An investigation into heat storage by adopting local climate zones and nocturnal-diurnal urban heat island differences in the Tokyo Prefecture Type de document : Article/Communication Auteurs : Christopher O'Malley, Auteur ; Hideki Kikumoto, Auteur Année de publication : 2022 Article en page(s) : n° 103959 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] cartographie thématique [Termes IGN] climat local [Termes IGN] distribution spatiale [Termes IGN] ilot thermique urbain [Termes IGN] image Landsat-8 [Termes IGN] image Terra-MODIS [Termes IGN] nuit [Termes IGN] pente [Termes IGN] stockage [Termes IGN] température au sol [Termes IGN] Tokyo (Japon) [Termes IGN] variation diurne Résumé : (auteur) This study aims to identify urban forms that are prone to heat storage in the Tokyo Prefecture in Japan. First, local climate zones (LCZ) were identified with 100 m pixel resolution using Landsat 8 data. LCZs include urban forms that are predominantly defined by building compactness and height. The spatial distribution of urban heat island intensity was obtained using LCZs and MODIS 100 m resolution land surface temperatures from 2013 to 2021. The difference between diurnal and nocturnal heat island intensity (∆UHI) was evaluated as an indicator of the relative heat storage effect between the LCZs. Lower ∆UHIs suggest increased relative heat-storage capacities. Seasonal average ∆UHIs for compact and super high-rise, high-rise, mid-rise, and low-rise LCZs were 3.1 °C, 4.1 °C, 5.8 °C, and 8.3 °C, respectively. Additionally, ∆UHIs for open and super high-rise, high-rise, and mid-rise LCZs were 5.8 °C, 6.4 °C, and 7.8 °C, respectively. Slope data also validated the LCZ height. LCZ and slope analyzes found lower ∆UHI magnitudes in all LCZs with high-rise buildings. Also, compact LCZs had lower ∆UHI magnitudes than open LCZs at corresponding heights. Therefore, higher-rise and compact LCZs are suggested to have larger relative heat storage effects than lower-rise and open LCZs. Numéro de notice : A2022-486 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.scs.2022.103959 Date de publication en ligne : 19/05/2022 En ligne : https://doi.org/10.1016/j.scs.2022.103959 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100951 [article]

Uncertainty interval estimates for computing slope and aspect from a gridded digital elevation model / Carlos López-Vázquez in International journal of geographical information science IJGIS, vol 36 n° 8 (August 2022)  

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About tree height measurement: Theoretical and practical issues for uncertainty quantification and mapping / Samuele De petris in Forests, vol 13 n° 7 (July 2022)  

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Assessing and mapping landslide susceptibility using different machine learning methods / Osman Orhan in Geocarto international, vol 37 n° 10 ([01/06/2022])  

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Using vertices of a triangular irregular network to calculate slope and aspect / Guanghui Hu in International journal of geographical information science IJGIS, vol 36 n° 2 (February 2022)  

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Forest fire susceptibility assessment using google earth engine in Gangwon-do, Republic of Korea / Yong Piao in Geomatics, Natural Hazards and Risk, vol 13 n° 1 (2022)  

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Regeneration of spruce - fir - beech mixed forests under climate and ungulate pressure / Mithila Unkule (2022)  

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Three-dimensional simulations of rockfalls in Ischia, Southern Italy, and preliminary susceptibility zonation / Massimiliano Alvioli in Geomatics, Natural Hazards and Risk, vol 13 n° 1 (2022)  

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A comparative approach of support vector machine kernel functions for GIS-based landslide susceptibility mapping / Khalil Valizadeh Kamran in Applied geomatics, vol 13 n° 4 (December 2021)  

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OBIA-based extraction of artificial terrace damages in the Loess plateau of China from UAV photogrammetry / Xuan Fang in ISPRS International journal of geo-information, vol 10 n° 12 (December 2021)  

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Quantifying coherence between TDM90, SRTM90 and ASTER90 / Umut Gunes Sefercik in Geocarto international, vol 36 n° 15 ([15/08/2021])  

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