地理空间作为使用大数据预测人类活动的生命结构
Geographic Space as a Living Structure for Predicting Human Activities Using Big Data
摘要：
受克里斯托弗·亚历山大的世界观的启发--空间不是无生命的或中性的，而是一个包含远多于大事物的生命结构，拓扑表示法先前已经被开发出来以表征生命结构或地理空间的整体性。本文进一步发展了用于预测地理空间中人类活动的拓扑表示和生命结构。基于从OpenStreetMap中提取的英国数百万个街道节点，我们以嵌套的方式建立了不同尺度的生活结构。我们发现，在不同的规模水平，如国家和城市，可以很好地预测推文位置的基本生活结构。高的可预测性表明，生活结构和拓扑表示是有效的，更好地理解地理形态。基于这一重要发现，我们认为拓扑表示是一种真正的多尺度表示，并指出现有的地理表示本质上是单尺度的，因此它们存在许多尺度问题，如可修改的面积单位问题、长度难题和生态谬误。我们进一步讨论了为什么活结构是构建地理空间大数据的有效工具，以及为什么亚历山大的有机世界观构成了第三种空间观。关键词：有机世界观，拓扑表示，鸣叫位置，自然城市，地理空间的缩放
英文摘要：
Inspired by Christopher Alexanders conception of the world - space is not lifeless or neutral but a living structure involving far more small things than large ones a topological representation has been previously developed to characterize the living structure or the wholeness of geographic space. This paper further develops the topological representation and living structure for predicting human activities in geographic space. Based on millions of street nodes of the United Kingdom extracted from OpenStreetMap, we established living structures at different levels of scale in a nested manner. We found that tweet locations at different levels of scale, such as country and city, can be well predicted by the underlying living structure. The high predictability demonstrates that the living structure and the topological representation are efficient and effective for better understanding geographic forms. Based on this major finding, we argue that the topological representation is a truly multi-scale representation, and point out that existing geographic representations are essentially single scale, so they bear many scale problems such as modifiable areal unit problem, the conundrum of length, and the ecological fallacy. We further discuss on why the living structure is an efficient and effective instrument for structuring geospatial big data, and why Alexanders organic worldview constitutes the third view of space. Keywords: Organic worldview, topological representation, tweet locations, natural cities, scaling of geographic space
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
