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Journal of Entrepreneurship and Public Policy
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Traffic speed mapping with cellular network signaling data by FOSS4G
Wang Weifeng,Zhu Kemin,Liu Junli,Hu Jinghao,Raganvan Venkatesh,Xu Jiang,Song Xianfeng 대한공간정보학회 2022 Spatial Information Research Vol.30 No.2
Mapping traffic speed on road networks is crucial for urban traffic management and the development of intelligent transportation systems. Traditionally, information regarding traffic speed can be obtained from locationfixed sensors, such as loop detectors and cameras; however, these methods are limited to major road crosses. Recently, a considerable attention has been paid to utilizing vehicles with mobile phones as probes for collecting traffic information. This study proposes an open-source GIS approach to map traffic speeds in a road network. First, public service vehicles (PSVs) were identified from cellular network signaling data by measuring the similarity between cell-ID trajectories and bus routes. Then, the cell-ID trajectories of PSVs were refined into high-quality spatiotemporal trajectories, and projected onto the road network via heuristic global optimization. Finally, hourly traffic speed maps were computed by weighing the speeds of the PSVs in the road network. The approach was implemented using free and open source software for geospatial mapping stacks of toolkits (Python, TimescaleDB/PostGIS, Pandas/Pygmo2, and Matplotlib/Seaborn); this application demonstrated good results using cellular network signaling data and GPS trajectories collected in Huilongguan district, Beijing, China. Moreover, this demonstration illustrates that probe mobile monitoring is emerging as a critical technology for traffic monitoring supplements, which can help develop a comprehensive view of the roads and reduce the cost of monitoring a large area.
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Traffic speed mapping with cellular network signaling data by FOSS4G
Wang Weifeng,Zhu Kemin,Liu Junli,Hu Jinghao,Raganvan Venkatesh,Xu Jiang,Song Xianfeng 대한공간정보학회 2022 Spatial Information Research Vol.30 No.1
Mapping traffic speed on road networks is crucial for urban traffic management and the development of intelligent transportation systems. Traditionally, information regarding traffic speed can be obtained from locationfixed sensors, such as loop detectors and cameras; however, these methods are limited to major road crosses. Recently, a considerable attention has been paid to utilizing vehicles with mobile phones as probes for collecting traffic information. This study proposes an open-source GIS approach to map traffic speeds in a road network. First, public service vehicles (PSVs) were identified from cellular network signaling data by measuring the similarity between cell-ID trajectories and bus routes. Then, the cell-ID trajectories of PSVs were refined into high-quality spatiotemporal trajectories, and projected onto the road network via heuristic global optimization. Finally, hourly traffic speed maps were computed by weighing the speeds of the PSVs in the road network. The approach was implemented using free and open source software for geospatial mapping stacks of toolkits (Python, TimescaleDB/PostGIS, Pandas/Pygmo2, and Matplotlib/Seaborn); this application demonstrated good results using cellular network signaling data and GPS trajectories collected in Huilongguan district, Beijing, China. Moreover, this demonstration illustrates that probe mobile monitoring is emerging as a critical technology for traffic monitoring supplements, which can help develop a comprehensive view of the roads and reduce the cost of monitoring a large area.
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Trapping tephritid fruit flies (Diptera: Tephritidae) in citrus groves of Fujian Province of China
Yulu Xia,Gecheng Ouyang,Xingli Ma,Bohua Hou,Jinghao Huang,Hanqing HU,Guocheng Fan 한국응용곤충학회 2020 Journal of Asia-Pacific Entomology Vol.23 No.4
Certain tephritid fruit flies, such as the oriental fruit fly, Bactrocera dorsalis, the Chinese citrus fly, B. minax and the Japanese orange fly, B. tsuneonis (Diptera: Tephritidae: Dacinae), are destructive citrus pests in China. A twoyear trapping study was conducted in pomelo, Citrus maxima, groves in Fujian Province of China. The objectives of this study were to investigate the species, the abundance of tephritid fruit flies in the orchards, as well as the efficacy of the selected lure traps to these flies. Four lure traps or devices, i.e. methyl eugenol + Steiner trap (ST), cuelure + ST, ammonium acetate + putrescine + ST, and sticky spheres, were deployed from June to November 2017 and April to October 2018. Six economically significant Dacini pests were trapped during the period. These flies are B. dorsalis, the melon fruit fly, Zeugodacus cucurbitae, the pumpkin fruit fly, Z. tau, the Malaysian fruit fly, B. latifrons, and other two species - B. rubigina and Z. scutellatus. B. dorsalis was the most abundant, accounting for more than 50% of the capture, followed by Z. cucurbitae. The remaining four species accounted for less than 2% of the total capture. B. minax and B. tsuneonis, two destructive citrus-damaging tephritid fruit flies in China, were not found during the trapping period. Methyl eugenol trapped the highest number of fruit flies, followed by cuelure.
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