共查询到20条相似文献，搜索用时 31 毫秒
1.
2.
3.
4.
5.
6.
Richard Wadsworth 《International journal of geographical information science》2013,27(3):299-300
Urban segregation has received increasing attention in the literature due to the negative impacts that it has on urban populations. Indices of urban segregation are useful instruments for understanding the problem as well as for setting up public policies. The usefulness of spatial segregation indices depends on their ability to account for the spatial arrangement of population and to show how segregation varies across the city. This paper proposes global spatial indices of segregation that capture interaction among population groups at different scales. We also decompose the global indices to obtain local spatial indices of segregation, which enable visualization and exploration of segregation patterns. We propose the use of statistical tests to determine the significance of the indices. The proposed indices are illustrated using an artificial dataset and a case study of socio‐economic segregation in São José dos Campos (SP, Brazil). 相似文献
7.
8.
环嵩山地区9000 aB.P.-3000 aB.P.聚落规模等级 总被引：2，自引：1，他引：1
选取遗址面积、文化层厚度、重要遗物、重要遗迹4 个变量, 利用SOFM网络对环嵩山地区9000 aB.P.-3000 aB.P.聚落按照裴李岗、仰韶、龙山、夏商4 个阶段分别进行聚类分析, 以此对区域不同时期早期聚落的规模等级进行划分, 其中裴李岗时期聚落划分为2 个级别, 仰韶、龙山时期聚落均划分为3 个级别, 夏商时期聚落划分为4 个级别。结果表明, 裴李岗时期区域聚落等级规模之间的差异不明显, 大致在距今5000 年左右的仰韶文化中晚期, 区域聚落规模等级出现分异, 这种分异在龙山时期得以延续, 并于夏商时期最终形成。此外, 规模等级划分结果还对于特定时期文化面貌的区域差异有所反映, 具体表现在裴李岗时期3 个区域所属的不同文化系统与夏、商文化不同的空间分布特征。通过环嵩山地区9000 aB.P.-3000 aB.P.聚落规模等级研究发现, SOFM网络具有的邻近单元相互竞争、相互学习特征可以降低遗址面积不准确性对于分类结果的影响, 非常适合于早期聚落规模等级的划分。 相似文献
9.
10.
David Martin 《International journal of geographical information science》2013,27(1):100-102
11.
12.
13.
Harvey Neo 《Singapore journal of tropical geography》2023,44(1):22-27
C.P. Pow was my confidant, colleague and (occasional) collaborator for more than 20 years. He had fought a valiant and dignified battle with an aggressive cancer but ultimately succumbed to it in July 2021. I will reminisce a few of the little known traits of Pow which had shaped him to become the conscientious, obliging and humble academic that he was known for. 相似文献
14.
15.
16.
17.
18.
19.
20.
PAUL MATHER 《International journal of geographical information science》2013,27(2):258-259
As they increase in popularity, social media are regarded as important sources of information on geographical phenomena. Studies have also shown that people rely on social media to communicate during disasters and emergency situation, and that the exchanged messages can be used to get an insight into the situation. Spatial data mining techniques are one way to extract relevant information from social media. In this article, our aim is to contribute to this field by investigating how graph clustering can be applied to support the detection of geo-located communities in Twitter in disaster situations. For this purpose, we have enhanced the fast-greedy optimization of modularity (FGM) clustering algorithm with semantic similarity so that it can deal with the complex social graphs extracted from Twitter. Then, we have coupled the enhanced FGM with the varied density-based spatial clustering of applications with noise spatial clustering algorithm to obtain spatial clusters at different temporal snapshots. The method was experimented with a case study on typhoon Haiyan in the Philippines, and Twitter’s different interaction modes were compared to create the graph of users and to detect communities. The experiments show that communities that are relevant to identify areas where disaster-related incidents were reported can be extracted, and that the enhanced algorithm outperforms the generic one in this task. 相似文献