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The Remote Sensing Data and Spatial Intelligence for China and Global Studies

The Remote Sensing Data and Spatial Intelligence for China and Global Studies. Shuming Bao China Data Center University of Michigan Guoqing Li Centre for Earth Observation and Digital Earth Chinese Academy of Sciences Chaoyang Fang The Key Lab of Poyang Wetland and Watersheds

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The Remote Sensing Data and Spatial Intelligence for China and Global Studies

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  1. The Remote Sensing Data and Spatial Intelligence for China and Global Studies Shuming Bao China Data Center University of Michigan Guoqing Li Centre for Earth Observation and Digital Earth Chinese Academy of Sciences Chaoyang Fang The Key Lab of Poyang Wetland and Watersheds Jiangxi Normal University

  2. Challenges for Data Sharing • Integration of data from different sources and • formats • Integration of data and methodology for data • analysis • Integration of data, methodology and • knowledge for decision support

  3. Data Sources 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

  4. Ukrainian Space GRID Global Grid Network To integrate capabilities of space agencies to share computational and informational resources

  5. Workflow SAR archive (ESA) MODIS archive(CHN) Search andselect data Applicationserver Automatic workflow generation Portal SAR: UAresources SAR(UA) Workflow execution KML MODIS (CHN) Visualization ofderived products (NASU,Andrii, 2009) MODIS: CHNresources 7

  6. Flood Detection Based on MODIS MODISHDF（L1B） （HDF-EOS） Other MODIS（HDF-EOS） Geolocation Flood detection（NDVI） Vectorization KML Format

  7. ASAR From NASU

  8. Karajan Workflow • Commodity Grid（CoG）kits • Karajan (from karajjan technique report)

  9. Portal for Flood Detection

  10. MODIS（L1B）

  11. Geolocated Image

  12. Results in Google Earth

  13. Spatial IntelligenceAn Integration of Information, Methodology and Knowledge supported by Spatial Technology Technology + + Information knowledge Methodology

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

  15. 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

  16. Primary 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） • 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 • Spatial Models 空间模型 • Gravity Models 重力模型 • Export输出 • Data tables (Excel) 数据表格 • Reports (Excel, Word, PDF) 分析报告 • GIS maps (Shape) 数字地图 • Maps (PDF) 打印地图

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

  18. Selection by Groups 分组选择

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

  20. Selection by Establishments 单位选择

  21. Province and City Statistics 政府统计

  22. Data Selection

  23. Interactive Interface

  24. Multiple Outputs

  25. Customize Reports

  26. Exploratory Spatial Data Analysis

  27. Poyang Lake Monitoring and Decision Support System鄱阳湖水生态监测和决策支持系统 1999.12 ~1,000km2 1989.7 ~4,000km2

  28. Environmental Challenges with Regional Development

  29. System Design C# + ENVI/IDL + JavaScript

  30. System Demo 登陆界面 2011.7.4 悬浮泥沙浓度 2011.7.4 水体提取结果 系统主界面 2011.7.4 水质综合污染指数 2011.7.4 水体透明度

  31. Spatial Assessment • Overlap of water areas with demographic and business data • Estimates of population and economic units within buffers

  32. Future Work • Integration of more data sources • Cross-validation and calibration • Improvement of detection algorithms • Full Integration with spatial intelligence for impact assessment • Operational portal for international flood monitoring

  33. Discussions and Suggestions • Challenges for spatial data sharing • Joint initiatives under CODATA

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