| 基于微博大数据的2010～2018年中国桃花观赏日期时空格局研究 |
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| 引用本文： | 刘俊,王胜宏,金朦朦,李宁馨.基于微博大数据的2010～2018年中国桃花观赏日期时空格局研究[J].地理科学,2019,39(9):1446-1454. |
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| 作者姓名： | 刘俊 王胜宏 金朦朦 李宁馨 |
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| 作者单位： | 四川大学旅游学院,四川成都,610065;四川大学旅游学院,四川成都,610065;四川大学旅游学院,四川成都,610065;四川大学旅游学院,四川成都,610065 |
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| 基金项目： | 国家自然科学基金项目(41771163);四川省重点研发项目(2018SZ0373);四川大学创新火花项目库(2018hhs-44) |
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| 摘 要： | 从新浪微博中检索到2 952 828条有关桃花观赏活动的微博,按照数据筛选、时空匹配、检验校准的流程,筛选出843 034条表述“桃花开了”的可采信微博,从中提取并构建了2010~2018年全国293个城市的桃花观赏日期数据集。之后使用物候站点观测数据、气温数据和物候模型模拟数据验证了桃花观赏日期数据集,得出基于微博大数据提取的中国桃花观赏日期数据集符合物候站点观测的桃花花期变化规律,符合桃花开花前气温升高则花期提前的基本规律,并与物候模型模拟的桃花花期基本一致,可以作为物候站点观测数据的重要补充。基于提取出的桃花观赏日期数据集,进一步分析了中国桃花观赏日期的时空格局,结果表明,纬度每升高1°,桃花观赏日期推迟1.78 d,其中北亚热带桃花观赏日期对纬度变化最为敏感,纬度每升高1°,桃花观赏日期推迟2.56 d。过去9 a全国大部分城市的桃花观赏日期提前。
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| 关 键 词： | 物候 大数据 桃花 赏花旅游 |
Reconstruction of Peach Blossom-viewing Date of China Using Weibo Big Data |
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| Liu Jun,Wang Shenghong,Jin Mengmeng,Li Ningxin.Reconstruction of Peach Blossom-viewing Date of China Using Weibo Big Data[J].Scientia Geographica Sinica,2019,39(9):1446-1454. |
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| Authors: | Liu Jun Wang Shenghong Jin Mengmeng Li Ningxin |
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| Institution: | Tourism School, Sichuan University, Chengdu 610065, Sichuan, China |
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| Abstract: | The big data of Web site are important complementary sources for phenological site observation data. Using Sina Weibo big data, 2.95×10 6 peach blossom timing data were retrieved for 293 Chinese cities. Through data screening, space-time matching, and verification, 843 034 trusted microblogs were related to the peach blossom-viewing season; from those data, a peach blossom-viewing dataset was extracted and constructed for those cities in 2010-2018. The dataset was validated with respect to the following: whether it matched phenological site observation data; whether the peach blossom-viewing period was preceded by an increase in temperature; and whether the results matched the simulation produced using a phenological model. The results with the dataset were as follows: it was found to be in accordance with the change in the peach blossom period observed at phenological sites; the beginning of the peach blossom-viewing period was indeed preceded by an increase in temperature; and the findings were basically consistent with the peach blossom-viewing period simulated using the phenological model. Thus, the peach blossom-viewing dataset could be employed as an important supplement to observation data observed at phenological sites. Further analysis showed that for every 1° increase in latitude, the peach blossom-viewing date in China was delayed by 1.78 days. Among all the climate zones, the peach blossom-viewing date in the northern subtropics was most sensitive to latitude: for each increase in latitude, the peach blossom-viewing date was delayed by 2.56 days in that zone. Over the past 9 years, the peach blossom-viewing date with most Chinese cities has become earlier. |
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| Keywords: | phenology big data peach blossom flower viewing tourism |
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