New Development of Religions in China

1. 空间宗教与社会研究- 数据、方法、技术与研究方向Spatial Explorer of Religions and Society- Data, Methodology, Technology and Research Agenda密西根大学中国信息研究中心 鲍曙明University of Michigan China Data CenterShuming Bao

2. New Fashion New Trends New Development of Religions in China New Clusters

3. The Primary Factors for Spatial Differences in Local Religions影响地方神信仰差异的主要因素朱海滨：《祭祀政策与民间信仰变迁-近世浙江民間信仰研究》上海：复旦大学出版社，2008 • 自然灾害 • 产业形态 • 交通与地理 • 乡土意识 • 迁入移民 • 巫、道文化 • 宗教与环境 • 宗教与经济 • 宗教与与地理 • 宗教与文化 • 宗教与移民 • 宗教与宗教 • 。。。。 • 宗教与历史 • 宗教与政治 • 宗教与管理

4. Spatial Analysis of Religions • Identify the spatial patterns of religious, demographic and socioeconomic distribution. • Identify the spatial interactions (linkages) between religious and other aspects of the society. • Evaluate the impacts of religions on future development of the society.

5. Demand for Spatial Analysis • How can we use the data from different sources, time, and formats? • What is the spatial patterns of data distribution? • How the spatial patterns changes over the time? • How the observations are interacted over the time and space? • How different factors are interacted each other over the time and space ?

6. Topics Data Methodology Technology Applications Research Agenda Future Directions

7. I. Data Government Statistics Remote Sensing Data Census (population, economy,…) Enterprises database Geography Information infrastructure for China Studies Financial Database Environment Custom Database Household Surveys Market Database

8. Statistical Data • Statistical Database: • Monthly Statistics • National Statistics • Provincial Statistics • City Statistics • County Statistics • Monthly Industrial Data • Yearly Industrial Data • Statistics on Map • Statistical Yearbooks • Census Database: • Population Census 1982 • Population Census 1990 • Population Survey 1995, 2005 • Province Census 2000 • County Census 2000 • Economic Census 2004

9. The Census Data of China Population Census: • 1953, 1964, 1982, 1990, 2000 Economic Census: • Industrial Census (1995) • Basic Unit Census (2001) • Economic Census (2004)

10. Spatial Data of China • 2000 China Township Population Census Data with GIS Maps • 2000 China County Population Census Data with GIS Maps (Version III) • 2000 China Province Population Census Data with GIS Maps • 2000 China Grid Population Census Data with Township Boundaries • China Historical Province Population Census Data with GIS Maps (1953, 1964, 1982, 1990, 2000) • China Historical County Population Census Data with GIS Maps (1953, 1964, 1982, 1990, 2000) • China 1995 Industrial Census Data with GIS Maps • China 2001 Basic Unit Census Data with GIS Maps • China 2004 Economic Census Data with GIS Maps • China City Statistical Indicators with Maps (1996-) • Geographic Layers (rivers, lakes, roads, highways, railways)

11. Local Gazetteers and Journal Databases

12. New Releases

13. II. Methodology

14. Spatial Statistics • Tests on spatial patterns: • Tests on spatial non-stationarity • Tests on spatial autocorrelation • Data-driven approaches (Exploratory Spatial Data Analysis) • Global Statistics • Local statistics • Model-driven approaches • Spatial linear and non-linear models • Space-temporal models

15. Difference between Conventional Statistics and Spatial Statistics Con. statistics Spatial statistics Data: Time-series data Spatial data (cross-sectional) Relationship: Time (yt-1, yt, yt+1) Topology (yi-1, yi, yi+1) Process: {Z(t), tT} {Z(s;t), sD(t), tT} Model: Y = WY +  t = 1, 2, 3, … wi,j= 1 if i is adjacent to j  - time-series  - spatial autocorrelation autocorrelation

16. Defining Spatial Linkage (Weights) • Criteria: theoretical and empirical • Accessibility (roads, rivers, railways, airlines and Internet) • Economic linkage (commuter flows, migrations, trade flows) • Social linkage (college admission, language) • Locational linkage (neighborhood, geographical distance) • Methodology: • Binary matrix • Row standardized matrix • Weight function (wij=f(x,y..))

17. Identifying Spatial Trend Theoretical Variogram: Experimental Variogram: where N(hk)={(i,j): xi-xi_=h}, |N(hk)|is the number of distinct elements of N(hk), or . Nugget - represent micro-scale variation or measurement error. Its estimated by (0). Sill - represent the variance of the random field limh(h). Range - the distance at which data are no longer autocorrelated.

18. Identifying Spatial Autocorrelation Moran I: Geary C: • Moran I (Z value) is • positive: observations tend to be similar; • negative: observations tend to be dissimilar; • approximately zero: observations are arranged randomly over space. • Geary C: • large C value (>>1): observations tend to be dissimilar; • small C value (<<1) indicates that they tend to be similar.

19. Identifying Local Spatial Associations Local Moran: • significant and negative if location i is • associated with relatively low values in • surrounding locations; • significant and positive if location i is • associated with relatively high values of • the surrounding locations. Local Geary: • significant and small Local Geary (t<0) • suggests a positive spatial association • (similarity); • significant and large Local Geary (t>0) • suggests a negative spatial association • (dissimilarity).

20. Spatial Regression Spatially autoregressive model Spatial moving average model Semi-parametric model where W1 and W2 are spatial weight matrices,  ~ N(0,).

21. 空间数据分析理论与方法研究领域 空间平衡和非平衡理论(Spatial equilibrium theories and unequilibrium theories) 探索性数据分析(Exploratory spatial data analysis) 空间数据抽样(Spatial sampling) 地理统计学(Geostatistics , such as multivariates variogram and kriging) 局部统计分析(Local spatial statistics) 空间聚类分析(Spatial cluster analysis) 空间数据显示(Spatial data visualization - dynamic visualization, statistical graphics, multi-dimensional data visualization)

22. III. Technology

23. Functions for Spatial Analysis • compare the data of different times • compare the data at different locations • aggregate the data by spatial ranges • aggregate the data by different levels of administrative units • integrate the data from different sources • conduct spatial data analysis without GIS skills • extract the data efficiently • make the reports for ready analysis and publications • get the local/community information for survey data analysis • detect outliers, spatial patterns and trends

24. Spatial Intelligence:An Integration of Information, Methodology and Knowledge supported by Spatial Technology Technology + + Information knowledge Methodology

25. New Development: China Geo-ExplorerSpatial Intelligence for Space-Time Data Integration and Analysis Charts Statistics Tables Reports Census Maps GIS

26. China Geo-Explorer- Web Based Platform for Spatial Intelligence • Objectives: • To provide a web-based platform for data integration and spatial analysis • To facilitate multidisciplinary studies and applications by brining new methodology • To promote knowledge sharing with new technology • Features: • Efficient data integration for spatial and non-spatial data • Quick and accurate location analysis and spatial assessment • Identify spatial patterns and trends • Generate time-saving, easy-to-use, and pre-formatted reports as well as customized reports • Dynamic maps for visual analysis • Applications: proximity analysis, buffer analysis, cluster analysis, simulation and projections,….

27. 2000 Population Census with Maps 2000 Population Variables: Basic Structure Minority Age Structure Household Education Fertility Death Marriage Migration Housing Occupation Spatial Hierarchical Structure: Province | Prefecture | County | Township | Sq km Grid

28. 2004 Economic Census Data with ZIP Maps Revenue (10,000 Yuan) 0-30 30---50 50---100 100--300 300--500 500--1000 1000-3000 3000-5000 5000-10000 10000-30000 30000-50000 50000-100000 100000-150000 150000-200000 200000 and over Industries Ownerships Revenue Employee … Employee 1 1-19 20-49 50-99 100-499 500-999 1000-4999 5000-29999 30000-49999 50000+

29. Land Use （ sq km Grid）

30. System Architecture User Data Selection Reports Maps Charts Mashup Integration Flex WebGIS Raster Data Vector Data Time-Series Data Observations GeoGlobe Google Map Statistical Data Other Data …. WMS Server WFS Server Server

31. Featured Functions • Data Selection 数据选择 （政府统计、人口普查、经济普查、工业普查、单位普查、土地、环境） • By administrative units (province, city, county, township) • By groups • By location (X&Y) and spatial range (km or miles) • By time-series statistics (province, city and county) • By establishments (province, city, county and ZIP) • Reporting报告 • Summary report 汇总报告 • Comparison report 比较报告 • Original data report 原始数据报表 • Spatial Analysis 空间分析 • Graphic analysis 图形分析 （直方图， 散点图，多变量图） • ESDA spatial statistics 探索性空间统计分析 • OLS regression 普通回归 • Spatial Regression 空间回归 • Export输出 • Data tables (Excel) 数据表格 • Reports (Excel, Word, PDF) 分析报告 • GIS files (Shape) 数字地图 • Maps (PDF) 打印地图

32. Selection by Administrative Units 行政区选择 Select by map Select by administrative units

33. Selection by Groups 分组选择

34. Selection by Locations 按空间位置选择 Select by X & Y coordinates Select by locations on map

35. Selection by Establishments 单位选择

36. Province and City Statistics 政府统计

37. Export of Space-Time Series Data时空数据分析与输出

38. Exploratory Spatial Data Analysis 空间统计分析

39. Graphic Analysis：Histogram

40. Graphic Analysis：Scatter Plot

41. Graphic Analysis：Multi-Plots

42. Gravity Model for Space-time Data

43. Multiple Outputs 多种报告输出

44. Customized Reports 自定义报告输出

45. Output：Establishments

46. Output：GISMaps

47. Integration with local Gazetteers

48. IV. 应用研究 • Spatial Distribution of Regions • Spatial Structure of Religions • Spatial Trends of Religious Development • Spatial Religion and Population • Spatial Religion and Economy • Spatial Religion and Environment • Spatial Religion and Social Development • Policy Impacts on Religious Development • Location Selection of Religious Sites • Household/Field Surveys

49. Case Study: 宗教与社会空间研究 Reports Web Tool Elevation Charts Religious Clusters Religious Sites

50. Case Study: 宗教与社会调查空间分析