Inferring Land Use of Guangzhou from Big Data of Location Service
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摘要: 位置服务(LBS)产生的时空行为大数据为地理环境模拟提供了重要机遇，也为土地利用类型的模拟识别提供了创新思路。位置服务大数据下的居民活动强度的周期性变化与土地利用有显著相关性，带有较强的土地利用指示性，在土地利用类型模拟识别上具有较大的应用价值。以广州为案例，本文利用百度地图平台APP联盟用户的位置服务大数据，以150*150m格网为精度单元，应用监督分类方法中的随机森林分析法模拟识别土地利用类型，模拟总准确率达72.40%，其中，村镇建设用地、工业用地、公园绿地、居住用地和商业金融用地的预测准确率分别为50.39%、82.65%、49.53%、82.66%和49.56%。研究结果表明随机森林方法在应用高密度时空行为大数据进行土地利用类型模拟的有效性及位置服务大数据在城市土地利用类型模拟上的潜在价值，也反映了居民活动强度空间形态与土地利用之间的显著相关性。当然，这需要利用不同的技术手段在不同城市和城市的不同区域上更多的案例实证。Abstract: spatial-temporal big data produced by Location Based Service (LBS) provide an important opportunity for geo-environment simulation, and a novel way for simulation of land use types. The periodicity change of residents activity under the LBS big data has a significant correlation with land use, and show strong land use indication. LBS big data show great application value in land use type simulation. APP alliance user's Location Based Service big data on the Baidu Map platform is used to refer the land use in Guangzhou. The random analysis method in the supervisory classification method is used to simulate the land use type taking the 150*150m grid as the precision unit. The simulation result is total accuracy rate 72.40%, and among which the simulating accuracy rate of villages and towns construction land, industrial land, park green land, residential land, commercial and financial land are 50.39%, 82.65%, 49.53%, 82.66% and 49.56% respectively. The validation result confirms that random analysis method effectively infer land use types based on the high-density geographic behavior big data and demonstrates the potential values of using the LBS big data in urban land use inference, and also reveals the significant linkage between the residents activity spatial pattern and the underlying urban land use. Of course, this requires more case studies in different cities and different regions in the city using different analysis technical means.
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Keywords:
- LBS big data /
- Random analysis method /
- Land use types simulation /
- Guangzhou
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期刊类型引用(4)
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百度学术
2. 孙武，沈子桐，欧阳睿康，孙靓，乔志强，朱琳琳，陈翔. 广州市主城区建筑立体形态的圈层分异及其影响因素. 华南师范大学学报(自然科学版). 2021(02): 73-83 . 百度学术
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