Journal of Geo-information Science, Volume. 22, Issue 6, 1202(2020)
Fig. 1. Crawling and storing flow chart of merchant's menu data from Ele.me in January 2019
Fig. 2. Data processing flow chart of merchant's menu from Ele.me in January 2019
Fig. 4. Distribution map of Sweet Habits in different province of China
Fig. 5. Moran scatter graph and LISA agglomeration graph of polygon data in China
Fig. 6. Cold point and hot Point bubble diagrams of sweetness in different cities of China
Fig. 7. Distribution Map of Modern Sweet Habits in China based on grouping analysis
Fig. 8. Relationship between Sweetness and Sunshine Hours in coastal and inland cities
Table 1. Comparison of accuracy of different interpolation methods
View tableView in ArticleTable 1. Comparison of accuracy of different interpolation methods
插值方法 均方根误差（RMS） 平均偏差 标准均方根误差（标准化RMS） 反距离加权 0.130 -0.016 — 普通克里格 0.138 0.008 1.366
Table 2. LISA of Urban Eating Sweetness
View tableView in ArticleTable 2. LISA of Urban Eating Sweetness
城市 食甜度 Moran' s I 标准化Z值 p 值关联类型 上海 0.7697 0.000 035 5.1219*** 0.0000 H-H 杭州 0.5724 0.000 032 4.4924*** 0.0000 H-H 福州 0.6000 0.000 011 2.8835*** 0.0039 H-H 成都 0.0794 0.000 013 3.0953*** 0.0019 L-L 银川 0.1000 0.000 010 2.3447** 0.0190 L-L
Table 3. Grouping analysis results of sweetness for different provinces in China
View tableView in ArticleTable 3. Grouping analysis results of sweetness for different provinces in China
空间约束类型 评价参数 组数 R 2孤元个数 CONTIGUITY面邻接类型 3 0.78 0 4 0.88 0 5 0.87 1 DELAUNAY三角测量 3 0.87 2 4 0.90 3 5 0.92 4 K_NEAREST邻接类型 3 0.80 1 4 0.88 3 5 0.93 4
Table 4. Stepwise regression analysis parameters
View tableView in ArticleTable 4. Stepwise regression analysis parameters
变量 模型1 模型2 模型3 模型4 模型5 模型6 βi βi βi βi βi βi C -1.67*** -6.17*** -7.10*** -7.49*** -6.78*** -6.68*** k ×lnp 0.12*** 0.13*** 0.11*** 0.72** 3.54** 3.77*** ln s 0.87*** 0.88*** 0.99*** 0.99*** 0.99*** 0.43** 0.35** 0.05 k ×lnh -1.01* -3.58** -3.81*** k ×lnt -3.19* -3.45*** F 值21.89*** 22.18** 20.70*** 17.95*** 16.86*** 22.18*** R 20.50 0.68 0.76 0.79 0.82 0.82
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Kezhen YAO, Shuping YUE.
Received: Aug. 8, 2019
Accepted: --
Published Online: Nov. 12, 2020
The Author Email: Shuping YUE (yueshuping@nuist.edu.cn)
