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Quantification of the adjacency effect on measurements in the thermal infrared region / Xiaopo Zheng in IEEE Transactions on geoscience and remote sensing, vol 57 n° 12 (December 2019)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 57 n° 12 (December 2019) . - pp 9674 - 9687 Titre : Quantification of the adjacency effect on measurements in the thermal infrared region Type de document : Article/Communication Auteurs : Xiaopo Zheng, Auteur ; Zhao-Liang Li, Auteur ; Xia Zhang, Auteur ; Guofei Shang, Auteur Année de publication : 2019 Article en page(s) : pp 9674 - 9687 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Télédétection [Termes IGN] adjacence [Termes IGN] exitance spectrale [Termes IGN] image à haute résolution [Termes IGN] image thermique [Termes IGN] modèle de transfert radiatif [Termes IGN] réflectivité [Termes IGN] température au sol Résumé : (auteur) Sensor-observed energy from adjacent pixels, known as the adjacency effect, influences land surface reflectivity retrieval accuracy in optical remote sensing. As the spatial resolution of thermal infrared (TIR) images increases, the adjacency effect may influence land surface temperature (LST) retrieval accuracy in TIR remote sensing. However, to our knowledge, few studies have focused on quantifying this adjacency effect on TIR measurements. In this study, a forward adjacency effect radiative transfer model (FAERTM) was developed to quantify the adjacency effect on high-spatial-resolution TIR measurements. The model was verified to be in good agreement with moderate resolution atmospheric transmission (MODTRAN) code, with a discrepancy 3 K in some cases. These findings indicate that the adjacency effect should be considered when retrieving LSTs from TIR measurements, at least in some specific conditions. The proposed FAERTM provides a useful model for quantifying and addressing the adjacency effect on TIR measurements Numéro de notice : A2019-600 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2928525 Date de publication en ligne : 06/08/2019 En ligne : http://doi.org/10.1109/TGRS.2019.2928525 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94599 [article]

Travel time estimation at intersections based on low-frequency spatial-temporal GPS trajectory big data / Luliang Tang in Cartography and Geographic Information Science, vol 43 n° 5 (November 2016)  

Public [article]  inCartography and Geographic Information Science > vol 43 n° 5 (November 2016) . - pp 417 - 426 Titre : Travel time estimation at intersections based on low-frequency spatial-temporal GPS trajectory big data Type de document : Article/Communication Auteurs : Luliang Tang, Auteur ; Zihan Kan, Auteur ; Xia Zhang, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 417 - 426 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] carrefour [Termes IGN] coordonnées GPS [Termes IGN] dimension temporelle [Termes IGN] données massives [Termes IGN] durée de trajet [Termes IGN] fréquence [Termes IGN] logique floue [Termes IGN] taxi [Termes IGN] trafic routier [Termes IGN] trajectoire (véhicule non spatial) [Termes IGN] Wuhan (Chine) Résumé : (Auteur) Intersections are the critical parts where different traffic flows converge and change directions, forming “bottlenecks” and “clog points” in urban traffic. Intersection travel time is an important parameter for public route planning, traffic management, and engineering optimization. Based on low-frequency spatial-temporal Global Positioning System (GPS) trace data, this article presents a novel method for estimating intersection travel time. The proposed method first analyzes the different travel patterns of vehicles through an intersection, then determines the range of an intersection dynamically and reasonably, and obtains traffic flow speed and delay at the intersection under different travel patterns using a fuzzy fitting approach. Finally, the average intersection travel time is estimated from traffic flow speed and delay and intersection range in different travel patterns. Wuhan road network data and GPS trace data from taxicabs were tested in the experiments and the results show that the proposed method can improve the accuracy of travel time estimation at city intersections. Numéro de notice : A2016-692 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/POSITIONNEMENT Nature : Article DOI : 10.1080/15230406.2015.1130649 En ligne : https://doi.org/10.1080/15230406.2015.1130649 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82029 [article]

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