Urban hotspots detection of taxi stops with local maximum density

2021 ◽  
Vol 89 ◽  
pp. 101661
Author(s):  
Xiao-Jian Chen ◽  
Ying Wang ◽  
Jiayi Xie ◽  
Xinyan Zhu ◽  
Jie Shan
Author(s):  
H. Wang ◽  
X.-J. Chen ◽  
Y. Wang ◽  
J. Shan

<p><strong>Abstract.</strong> Taxi trajectory data contains the detailed spatial and temporal traveling information of urban residents. By using a clustering algorithm, the hotspots’ distributions of pick-up and drop-off points can be extracted to explore the patterns of taxi traveling behaviors and its relationship with urban environment. Comparing with traditional methods that determine hotspots at a relatively large scale, we propose an approach to detect small-scale hotspots, so called docking points, to represent the local clusters in both sparse and dense stops areas. In this method, we divide the research area into grids and extract the docking points by finding local maximums of a certain range. The extracted docking points are classified into five levels for the subsequent analysis. Finally, to uncover detail characteristics of taxi mobility patterns, we analyze the distributions of docking points from three aspects &amp;ndash; the overall, by day of the week, and by time of the day.</p>


Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 248
Author(s):  
Sencer Yücesan ◽  
Daniel Wildt ◽  
Philipp Gmeiner ◽  
Johannes Schobesberger ◽  
Christoph Hauer ◽  
...  

A systematic variation of the exposure level of a spherical particle in an array of multiple spheres in a high Reynolds number turbulent open-channel flow regime was investigated while using the Large Eddy Simulation method. Our numerical study analysed hydrodynamic conditions of a sediment particle based on three different channel configurations, from full exposure to zero exposure level. Premultiplied spectrum analysis revealed that the effect of very-large-scale motion of coherent structures on the lift force on a fully exposed particle resulted in a bi-modal distribution with a weak low wave number and a local maximum of a high wave number. Lower exposure levels were found to exhibit a uni-modal distribution.


2021 ◽  
Vol 13 (8) ◽  
pp. 1442
Author(s):  
Kaisen Ma ◽  
Yujiu Xiong ◽  
Fugen Jiang ◽  
Song Chen ◽  
Hua Sun

Detecting and segmenting individual trees in forest ecosystems with high-density and overlapping crowns often results in bias due to the limitations of the commonly used canopy height model (CHM). To address such limitations, this paper proposes a new method to segment individual trees and extract tree structural parameters. The method involves the following key steps: (1) unmanned aerial vehicle (UAV)-scanned, high-density laser point clouds were classified, and a vegetation point cloud density model (VPCDM) was established by analyzing the spatial density distribution of the classified vegetation point cloud in the plane projection; and (2) a local maximum algorithm with an optimal window size was used to detect tree seed points and to extract tree heights, and an improved watershed algorithm was used to extract the tree crowns. The proposed method was tested at three sites with different canopy coverage rates in a pine-dominated forest in northern China. The results showed that (1) the kappa coefficient between the proposed VPCDM and the commonly used CHM was 0.79, indicating that performance of the VPCDM is comparable to that of the CHM; (2) the local maximum algorithm with the optimal window size could be used to segment individual trees and obtain optimal single-tree segmentation accuracy and detection rate results; and (3) compared with the original watershed algorithm, the improved watershed algorithm significantly increased the accuracy of canopy area extraction. In conclusion, the proposed VPCDM may provide an innovative data segmentation model for light detection and ranging (LiDAR)-based high-density point clouds and enhance the accuracy of parameter extraction.


1979 ◽  
Vol 57 (10) ◽  
pp. 1985-1997 ◽  
Author(s):  
Kerwin J. Finley

Numbers of ringed seals hauled out on the ice began to increase in early June. Numbers on the ice were highest from 0900 to 1500 hours Central Standard Time and lowest (average 40–50% of peak) in early morning. Seals commonly remained on the ice for several hours, and occasionally (during calm weather) for > 48 h. Numbers on the ice were reduced on windy days and possibly also on unusually warm, bright and calm days. Seals tended to face away from the wind (particularly with high wind speed) and oriented broadside to the sun. Seals usually occurred singly (60–70% of all groups) at their holes.Numbers of seals hauled out at Freemans Cove remained relatively constant during June (maximum density 4.86/km2), whereas at Aston Bay numbers increased dramatically to a maximum density of 10.44/km2 in late June. The increase was thought to be due to an influx of seals abandoning unstable ice. The density of seal holes at Freemans Cove (5.92/km2) was much higher than at Aston Bay (2.73/km2). The ratio of holes to the maximum numbers of seals (1.12:1) at Freemans Cove represents a first estimate of this relationship in an apparently stable population.


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