Quantifying the spatial heterogeneity of points
文献类型：期刊论文
| 作者 | Shu, Hua1,2; Pei, Tao1,2,3; Song, Ci1,2; Ma, Ting1; Du, Yunyan1; Fan, Zide1; Guo, Sihui1,2 |
| 刊名 | INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
 |
| 出版日期 | 2019-07-03 |
| 卷号 | 33期号:7页码:1355-1376 |
| 关键词 | Point pattern spatial heterogeneity spatial statistics nearest-neighbor statistics |
| ISSN号 | 1365-8816 |
| DOI | 10.1080/13658816.2019.1577432 |
| 通讯作者 | Pei, Tao(peit@lreis.ac.cn) |
| 英文摘要 | Variation in the spatial heterogeneity of points reflects the evolutionary process or mechanism of geographical events. The key to depicting this variation is quantifying spatial heterogeneity. In this paper, the spatial heterogeneity of a point pattern is defined as the degree of aggregation-type deviation from complete spatial randomness. In such a case, a goodness-of-fit-type statistic based on the distribution of nearest-neighbor distances called the level of heterogeneity (LH*) is regarded as a standard measurement, and a normalized version called the normalized level of heterogeneity (NLH*) is proposed for datasets with different point numbers and study region areas. Considering the complex integration calculation of LH* and NLH*, simulation experiments are implemented to test the capability of some classic nearest-neighbor statistics in quantifying spatial heterogeneity. The results showed that except for the standard LH* statistic, only Clark and Evans' statistic (A-w) and Byth and Ripley's statistic (H-xw) are robust. Statistics NLH*, (A-w) and (H-xw) are validated by quantifying the spatial heterogeneity of two-dimensional crime events, three-dimensional earthquake events and four-dimensional origin-destination (OD) events. The results indicate that these statistics all have a reasonable explanation in quantifying spatial heterogeneity for real-world geographical events of different types and with different dimensions. Compared with NLH*, Clark and Evans' (A-w) statistic and Byth and Ripley's (H-xw) statistic are recommended from the perspective of accessibility. |
| WOS关键词 | STATISTICAL-ANALYSIS ; CRIME CONCENTRATION ; NEAREST-NEIGHBOR ; PATTERN-ANALYSIS ; INHOMOGENEITY ; SEGREGATION ; EARTHQUAKES ; DENSITY |
| 资助项目 | National Natural Science Foundation of China[41525004] ; National Natural Science Foundation of China[41421001] ; National Key R&D Program of China[2017YFB0503604] |
| WOS研究方向 | Computer Science ; Geography ; Physical Geography ; Information Science & Library Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000468585300005 |
| 出版者 | TAYLOR & FRANCIS LTD |
| 资助机构 | National Natural Science Foundation of China ; National Key R&D Program of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/59266]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Pei, Tao |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing, Jiangsu, Peoples R China |
| 推荐引用方式 GB/T 7714 | Shu, Hua,Pei, Tao,Song, Ci,et al. Quantifying the spatial heterogeneity of points[J]. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,2019,33(7):1355-1376. |
| APA | Shu, Hua.,Pei, Tao.,Song, Ci.,Ma, Ting.,Du, Yunyan.,...&Guo, Sihui.(2019).Quantifying the spatial heterogeneity of points.INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,33(7),1355-1376. |
| MLA | Shu, Hua,et al."Quantifying the spatial heterogeneity of points".INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE 33.7(2019):1355-1376. |
入库方式： OAI收割
来源：地理科学与资源研究所
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