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It is possible to obtain vast amounts of spatiotemporal data related to human activities to support the study of human behavior and social evolution.In this context,geography,with the human-nature relationship as its core,is undergoing a transition from strictly earth observations to the observation of human activities.Geocomputation for social science is one manifestation thereof.Geocomputation for social science is an interdisciplinary approach combining remote sensing techniques,social science,and big data computation.Driven by the availability of spatially and temporally expansive big data,geocomputation for social science uses spatiotemporal statistical analyses to detect and analyze the interactions between human behavior,the natural environment,and social activities;Remote sensing(RS)observations are used as primary data.Geocomputation for social science can be used to investigate major social issues and to assess the impact of major natural and societal events,and will surely be an area of focused development in geography in the near future.We briefly review the background of geocomputation in the social sciences,discuss its definition and disciplinary characteristics,and highlight the main research foci.Several key technologies and applications are also illustrated with relevant case studies of the Syrian Civil War,typhoon transits,and traffic patterns. 相似文献
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准实时监测城市发展、掌握城市土地利用类型是日趋科学化、合理化进行城市规划的基本要求。随着信息通信技术、移动互联网技术、位置服务等的发展,海量的手机数据、浮动车数据、公交卡数据、社交网络数据等在内的人类时空活动信息为从“人”的角度动态实时感知城市土地利用、空间结构提供了可能。本文以深圳市为例,基于百万名QQ用户2013年的电子足迹数据,提出了不同类型的人类时空活动指数,以建立人类活动与城市地物间的对应关系;借鉴遥感影像不同波段记录各类地物在特定波谱区间辐射值的思想,生成各类人类时空活动指数波段图;并利用最大似然法对该“类高光谱影像”进行城市土地监督分类,获取城市的土地利用图。通过与深圳市规划图的对比验证,全体分类精度为72%。相较于传统基于“物”的遥感探测手段,基于“人”的城市感知更能反映城市内部相同地类的发展差异性。 相似文献
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基于海量的中国大型社交网络新浪微博人际社交关系数据,利用用户的地理位置信息对人-人(人际)社交关系进行虚拟网络空间到物理空间的映射,形成地-地关系。以城市为尺度,对个体间的社交关系链进行聚合,构建城市-城市(城际)社交关系网。根据网络的全局异构和局部异构等拓扑特征以及城市空间的相互作用,提出了一种融合重力模型和信息熵技术的地理骨干网提取方法。该研究有助于揭示虚拟网络环境下的城市体系结构、城市辐射力、城市吸引力和开放程度等问题。 相似文献
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