Journal of Geographical Sciences ›› 2020, Vol. 30 ›› Issue (9): 1534-1552.doi: 10.1007/s11442-020-1798-4
• Research Articles • Previous Articles
XU Chenchen1,2(), LIAO Xiaohan1,3,4,*(
), YE Huping1, YUE Huanyin1,3,4
Received:
2020-03-04
Accepted:
2020-06-02
Online:
2020-09-25
Published:
2020-11-25
Contact:
LIAO Xiaohan
E-mail:xucc.14s@igsnrr.ac.cn;liaoxh@igsnrr.ac.cn
About author:
Xu Chenchen, PhD Candidate, E-mail: Supported by:
XU Chenchen, LIAO Xiaohan, YE Huping, YUE Huanyin. Iterative construction of low-altitude UAV air route network in urban areas: Case planning and assessment[J].Journal of Geographical Sciences, 2020, 30(9): 1534-1552.
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Table 1
The minimum general element set for the iterative construction process of regional air route network"
Step | Key technology | Required elements | Optional elements | Required data processing |
---|---|---|---|---|
I | Hierarchi- cal planning | Road network: urban expressway, urban main road, community or campus internal trunk road Mobile base station. | Roads around buildings within a community or campus. | Road network: extract the road area and its center line and measure the road width. The road is stored in the form of shapefile. A road is a record composed of the coordinate values of feature points. Mobile base station: analyze the communication coverage limit and determine the regional route height limit accordingly. |
II | Utilizing positive constraints | None. The positive constraint element is only auxiliary but not required. | Urban green belt, isolation belt, grassland, street trees, parks, and other green areas; rivers, large areas of waters, ditches, and other water sources. | Green space: the relative position with the road determines the translation direction and translation distance, and thus the direction and translation distance matrices. Water area: the relative position with the road determines the translation direction and translation distance, and thus the direction and translation distance matrices. |
III | Avoiding negative constraints | General obstacles: buildings, mobile base station tower poles, street lamps, power lines (poles), etc. | Other obstacles, such as terrain in constructing the route in mountainous areas. | Mobile base station: the clearance boundary modeling of the tower pole is used to build an “obstacle” environment, and the communication coverage is modeled to analyze the spatial signal distribution. Other ground objects: to construct a mathematical model of clearance boundary. |
Table 2
Air route classification and relative attributes in JJXC district (Xu et al., 2020)"
Types | Function | Constraints | Height (m) | Minimum height (m) | Platform |
---|---|---|---|---|---|
1 | Connecting urban areas with the outside area | Higher than most of ground objects in urban area | 70-300 | 70 | Fixed wing/multi- rotor UAV |
2 | Main traffic routes inside the urban areas | Higher than lamps, trees, and buildings along roads | 50-70 | 50 | Multi-rotor UAV |
3 | Internal air route of community units in urban area | None | 15-50 | 30 | Multi-rotor UAV |
Table 3
Sheltering factor for each type of land use"
Code | Type | Sheltering factor |
---|---|---|
12 | Farmland | 0 |
23 | Open woodland (canopy density 10%-30%) | 2.5 |
41 | Waters | 0 |
51 | High-rise buildings | 7.5 |
52 | Low-rise buildings | 5 |
53 | Other construction land: factories and mines, large industrial zones, oil fields, salt fields, quarries and other patches of land; traffic roads, airports, and special areas | 10 |
61 | Others, including of unexploited land (e.g., deserts, salt flats, marshes) | 0 |
Table 4
Comparison of the population exposure risk for iterative UAV low-altitude air route network"
Type | Population exposure risk index (PERI) | |||||
---|---|---|---|---|---|---|
Average | Variance | Average | Variance | Average | Variance | |
Type 1 | Type 2 | Type 3 | ||||
Class I | 62.42 | 62.92 | 158 | 0 | 117.47 | 62.14 |
Class II | 21.75 | 9.05 | 25.98 | 15.35 | 23.92 | 17.88 |
Class III | 21.74 | 8.89 | 25.06 | 14.05 | 25.37 | 22.17 |
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