Efficient Method for POI/ROI Discovery Using Flickr Geotagged Photos
Efficient Method for POI/ROI Discovery Using Flickr Geotagged Photos
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DOI：
10.3390/ijgi7030121
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发表时间：
2018-03
期刊：
影响因子：
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通讯作者：
C. Kuo;T. Chan;I. Fan;A. Zipf
中科院分区：
文献类型：
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作者：
C. Kuo;T. Chan;I. Fan;A. Zipf
在大数据时代，无处不在的Flickr地理标记照片为发现有价值的地理信息提供了相当大的机会。感兴趣点（POI）和感兴趣区域（ROI）是地理空间应用中广泛使用的重要参考数据。本研究的目的是开发一种有效的方法，从Flickr的兴趣点/感兴趣区域发现。首先利用照片中具有局部最大值的有吸引力的足迹，这有利于区分聚类。将模式发现与空间重叠（SO）算法相结合，并采用命名合并的方法进行吸引足迹聚类。由聚类的峰值和范围得出的POI和ROI表示最受欢迎的景点欣赏位置和范围。所发现的ROI具有特定的空间重叠，这意味着可以共享ROI的满意区域以欣赏景点。所开发的方法在台湾的两个研究领域：台南和台北，这是最古老的和denestrian城市，分别证明。结果表明，发现的POI/ROI在台南市的官方数据几乎匹配，而更多的商业POI/ROI在台北市发现的算法比官方数据。同时，我们的方法可以解决密集区域的聚类问题。
In the era of big data, ubiquitous Flickr geotagged photos have opened a considerable opportunity for discovering valuable geographic information. Point of interest (POI) and region of interest (ROI) are significant reference data that are widely used in geospatial applications. This study aims to develop an efficient method for POI/ROI discovery from Flickr. Attractive footprints in photos with a local maximum that is beneficial for distinguishing clusters are first exploited. Pattern discovery is combined with a novel algorithm, the spatial overlap (SO) algorithm, and the naming and merging method is conducted for attractive footprint clustering. POI and ROI, which are derived from the peak value and range of clusters, indicate the most popular location and range for appreciating attractions. The discovered ROIs have a particular spatial overlap available which means the satisfied region of ROIs can be shared for appreciating attractions. The developed method is demonstrated in two study areas in Taiwan: Tainan and Taipei, which are the oldest and densest cities, respectively. Results show that the discovered POI/ROIs nearly match the official data in Tainan, whereas more commercial POI/ROIs are discovered in Taipei by the algorithm than official data. Meanwhile, our method can address the clustering issue in a dense area.