Research Article
Spatiotemporal Simulation of Tourist Town Growth Based on the Cellular Automata Model: The Case of Sanpo Town in Hebei Province
Table 1
Driving factors and weights of spatio-temporal growth of tourist town.
| Influencing factor | Variable type | Weight coefficient | Variable grading |
| | Distance to town center | 4 | Grade 1: 0~500 m Grade 2: 501~1000 m Grade 3: 1001~3000 m Grade 4: >3000 m | Basic geographic factors | Distance to arterial roads | 4 | Grade 1: 0~100 m Grade 2: 101~500 m Grade 3: 501~1000 m Grade 4: >1000 m | | Distance to railway | 2 | Grade 1: 0~100 m Grade 2: 101~500 m Grade 3: 501~1000 m Grade 4: >1000 m |
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Geographic factors for tourism | Distance to footpath | 3 | Grade 1: 0~100 m Grade 2: 101~300 m Grade 3: 301~600 m Grade 4: >600 m | Distance to scenic spots | 3 | Grade 1: 0~500 m Grade 2: 501~1000 m Grade 3: 1001~2000 m Grade 4: >2000 m |
| | Slope | 4 | Grade 1: <5 degrees Grade 2: 6 degrees~15 degrees Grade 3: 16 degrees~25 degrees Grade 4: >25 degrees | Topographical factors | Aspect | 1 | Grade 1: −45 degrees~45 degrees Grade 2: 45 degrees~135 degrees Grade 3: 135 degrees~225 degrees Grade 4: 225 degrees~315 degrees | | Ground fluctuation degree | 2 | Grade 1: <10 Grade 2: 10~20 Grade 3: 20~40 Grade 4: >40 |
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