Extracting the Maritime Traffic Route in Korea Based on Probabilistic Approach Using Automatic Identification System Big Data
Abstract
:1. Introduction
2. Materials and Methods
2.1. Analysis Area
2.2. Overview of Extracting the Korean Maritime Traffic Route
2.3. Preprocessing and Statistical Analysis of AIS Data Used for Analysis
2.4. Density Analysis for Extracting Main Maritime Traffic Routes
2.5. Related Study and Application to Extract Vessel Passage
3. Results of the Korean Maritime Traffic Route Analysis
3.1. Results of Main Maritime Traffic Routes Based on Density Analysis
3.2. The Korean Maritime Traffic Route Classification and Definition
3.2.1. Definition of the Main Route
3.2.2. Definition of the Outer Branch Route
3.2.3. Definition of the Inner Branch Route
3.3. The Result of Korean Maritime Traffic Main Route as Polygon
4. Discussion
5. Conclusions and Future Work
- First, it is to protect the area of the new and renewable energy zone that is being actively developed recently and the area of the ship passage within the MSP. So far, the domestic shipping area has only been protected in a very small area, which is restricted to the vicinity of ports. To keep ship routes to a minimum, a 50% density analysis was used for cargo ships, tanker ships, passenger ships, and towing ships larger than 60 m, but not all ships. This result does not use all the data, and it is essential to keep the area to which these ships navigate. Based on the density analysis result, it is divided into three routes: the main routes, the outer branch route, and the inner branch route. Once again, it is divided into routes that cannot be moved or changed and routes that allow movement and change through appropriate regulations.
- Second, domestic maritime traffic routes are designed to respond to the emergence of MASS in the future. The massive amount of AIS data used in this analysis is a historical record of ships operating safely and efficiently. If a ship’s navigation route is chosen with such conviction based on data, it is determined that it can be applied to the route of future ships. If a country’s maritime route is selected and major waypoints are presented, it is expected that MASS will be able to use a route that connects the world beyond one country.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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No. | Latitude | Longitude | No. | Latitude | Longitude |
---|---|---|---|---|---|
Area 1 | 36.50° N–37.60° N | 124.50° E–127.00° E | Area 9 | 33.10° N–34.00° N | 127.20° E–129.00° E |
Area 2 | 35.80° N–36.70° N | 124.50° E–126.80° E | Area 10 | 33.80° N–34.60° N | 128.70° E–130.00° E |
Area 3 | 35.00° N–36.00° N | 124.50° E–126.80° E | Area 11 | 35.50° N–36.50° N | 129.30° E–130.50° E |
Area 4 | 33.70° N–35.10° N | 124.50° E–126.50° E | Area 12 | 36.40° N–37.50° N | 129.30° E–130.50° E |
Area 5 | 33.70° N–35.00° N | 126.40° E–127.70° E | Area 13 | 37.20° N–38.70° N | 128.30° E–130.00° E |
Area 6 | 33.70° N–35.05° N | 127.60° E–128.75° E | Area 14 | 37.00° N–38.00° N | 130.40° E–132.40° E |
Area 7 | 34.50° N–35.60° N | 128.40° E–130.50° E | Area 15 | 34.30° N–35.20° N | 129.60° E–130.50° E |
Area 8 | 32.90° N–33.90° N | 125.80° E–127.30° E | Area 16 | 35.10° N–35.65° N | 129.85° E–130.50° E |
Categorization | AIS |
---|---|
Data Period | 1 January 2018–31 December 2018 1 September 2019–31 August 2020 |
Data Volume | Approx. 1.1 TB |
Analysis Area | Republic of Korea |
Ship Type | Cargo Ship, Tanker Ship, Passenger Ship, Towing ship |
Ship Length | 60 m or Over of Ship’s Type (≥60 m) |
Area | Data Counting | COG (°) | SOG (kts) | GT (ton) | Length (m) |
---|---|---|---|---|---|
Mean | Mean | Mean | Mean | ||
Area 1 | 7,125,269 | 171.1 | 5.9 | 13,403.4 | 131.3 |
Area 2 | 2,424,427 | 140.4 | 9.2 | 17,477.7 | 144.8 |
Area 3 | 2,360,251 | 158.0 | 8.8 | 14,927.5 | 129.5 |
Area 4 | 7,249,111 | 188.8 | 9.6 | 26,748.6 | 159.0 |
Area 5 | 3,712,294 | 154.1 | 8.4 | 10,769.9 | 116.8 |
Area 6 | 8,023,942 | 170.4 | 6.1 | 12,811.6 | 111.2 |
Area 7 | 14,654,929 | 169.2 | 3.8 | 14,419.0 | 122.2 |
Area 8 | 2,954,921 | 134.5 | 8.5 | 17,348.6 | 128.6 |
Area 9 | 2,744,786 | 119.2 | 11.5 | 41,535.5 | 172.3 |
Area 10 | 1,464,791 | 116.7 | 11.0 | 33,849.4 | 160.8 |
Area 11 | 4,664,982 | 152.0 | 3.5 | 73,756.7 | 120.8 |
Area 12 | 1,322,681 | 159.5 | 7.9 | 16,218.0 | 118.3 |
Area 13 | 959,212 | 142.2 | 6.2 | 6844.9 | 96.7 |
Area 14 | 931,028 | 80.9 | 6.5 | 14,566.8 | 99.3 |
Area 15 | 857,881 | 96.4 | 6.4 | 19,763.3 | 109.8 |
Area 16 | 661,153 | 78.5 | 6.0 | 21,415.2 | 110.9 |
No. | Threshold of 90% | Threshold of 75% | Threshold of 50% | Standard Deviation | Mean |
---|---|---|---|---|---|
Area 1 | 166 | 332 | 664 | 863 | 224 |
Area 2 | 52 | 104 | 234 | 275 | 124 |
Area 3 | 72 | 145 | 217 | 228 | 132 |
Area 4 | 86 | 173 | 281 | 373 | 239 |
Area 5 | 132 | 308 | 551 | 549 | 236 |
Area 6 | 207 | 345 | 552 | 810 | 443 |
Area 7 | 177 | 444 | 799 | 796 | 403 |
Area 8 | 90 | 180 | 316 | 279 | 233 |
Area 9 | 131 | 196 | 268 | 208 | 258 |
Area 10 | 57 | 173 | 385 | 353 | 293 |
Area 11 | 73 | 184 | 332 | 305 | 233 |
Area 12 | 47 | 78 | 118 | 108 | 93 |
Area 13 | 48 | 96 | 144 | 105 | 36 |
Area 14 | 26 | 52 | 79 | 50 | 40 |
Area 15 | 55 | 105 | 161 | 177 | 163 |
Area 16 | 104 | 160 | 225 | 116 | 188 |
Vertex No. | Width of Main Route (km) | Difference (km) | Vertex No. | Width of Main Route (km) | Difference (km) |
---|---|---|---|---|---|
1 | 11.04 | +4.64 | 18 | 18.86 | +12.46 |
2 | 7.23 | +0.83 | 19 | 27.64 | +21.24 |
3 | 8.49 | +2.09 | 20 | 25.66 | +19.26 |
4 | 13.77 | +7.39 | 21 | 27.71 | +21.31 |
5 | 15.00 | +8.60 | 22 | 26.83 | +20.43 |
6 | 7.89 | +1.49 | 23 | 24.21 | +17.81 |
7 | 7.45 | +1.05 | 24 | 21.46 | +15.06 |
8 | 9.23 | +2.83 | 25 | 12.69 | +6.29 |
9 | 10.06 | +3.66 | 26 | 10.43 | +4.03 |
10 | 11.48 | +5.08 | 27 | 8.47 | +2.07 |
11 | 6.11 | −0.29 | 28 | 5.93 | −0.47 |
12 | 6.14 | −0.26 | 29 | 7.29 | +0.89 |
13 | 10.24 | +3.84 | 30 | 6.04 | −0.36 |
14 | 7.65 | +1.25 | 31 | 5.50 | −0.90 |
15 | 7.29 | +0.89 | 32 | 5.05 | −1.35 |
16 | 10.09 | +3.69 | 33 | 6.46 | +0.06 |
17 | 16.19 | +9.79 |
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Lee, J.-S.; Cho, I.-S. Extracting the Maritime Traffic Route in Korea Based on Probabilistic Approach Using Automatic Identification System Big Data. Appl. Sci. 2022, 12, 635. https://doi.org/10.3390/app12020635
Lee J-S, Cho I-S. Extracting the Maritime Traffic Route in Korea Based on Probabilistic Approach Using Automatic Identification System Big Data. Applied Sciences. 2022; 12(2):635. https://doi.org/10.3390/app12020635
Chicago/Turabian StyleLee, Jeong-Seok, and Ik-Soon Cho. 2022. "Extracting the Maritime Traffic Route in Korea Based on Probabilistic Approach Using Automatic Identification System Big Data" Applied Sciences 12, no. 2: 635. https://doi.org/10.3390/app12020635
APA StyleLee, J.-S., & Cho, I.-S. (2022). Extracting the Maritime Traffic Route in Korea Based on Probabilistic Approach Using Automatic Identification System Big Data. Applied Sciences, 12(2), 635. https://doi.org/10.3390/app12020635