PPT-Spatial Microsimulation and Policy Analysis

Robert Tanton CRICOS 00212K Outline Description of spatial microsimulation Applications of spatial microsimulation Future of spatial microsimulation Further reading CRICOS 00212K. Chris Jochem. Geog. 5161 – Spring 2011. When you know ‘where’, you can start to . ask . ‘why’. John Snow’s map of cholera deaths in London, 1854.. Water pump locations. Need to move beyond simply mapping events and beyond general point pattern analysis.. data . Edward Park. SAC in MATLAB. Digital Globe inc.. Introduction. 1.1 Objective. Objective: . To do the . accuracy assessment. of various classification of raster pixels. . Why?. The . ultimate goal of Geographic Information System (GIS) is to model our world. However, the modeling process is too complicated and requires elaborateness that we should not rely entirely on computer. . Dr Kirk Harland. What is a Spatial . Microsimulation. ?. Static Spatial . Microsimulation. Deterministic Reweighting. Conditional Probabilities. Simulated Annealing. Dynamic . Microsimulation. This . Michael Noble and . Wanga. . Zembe. of SASPRI have found that the poorest municipalities are, without exception, in the old apartheid homelands, and all except one in either the Eastern Cape or KZN . USING CGE MODELS FOR POVERTY AND INEQUALITY ANALYSIS. Jeff Round. February 2012. Poverty impact analysis. Impact of economic shocks on poverty. Various manifestations of poverty. money-metric (income, expenditure, assets), health, . data . Edward Park. SAC in MATLAB. Digital Globe inc.. Introduction. 1.1 Objective. Objective: . To do the . accuracy assessment. of various classification of raster pixels. . Why?. The . ultimate goal of Geographic Information System (GIS) is to model our world. However, the modeling process is too complicated and requires elaborateness that we should not rely entirely on computer. . Ged Ridgway, London. With thanks to John Ashburner. a. nd the FIL Methods Group. Preprocessing overview. fMRI. time-series. Motion corrected. Mean functional. REALIGN. COREG. Anatomical MRI. SEGMENT. Influence Maps. Damián Isla, . Director of Tech. Moonshot Games. Spatial Evaluation. Spreading influence is just one form of spatial function.. Spatial decisions can be made on second-to-second timescales. Overview . of Spatial Big Data and . Analytics. (8:40-9:15am). James B. Pick. University of Redlands School of Business. James_pick@redlands.edu. . Pre-ICIS Workshop on Locational Analytics, Spatial . Historical Geography of Transportation. Transport and Spatial Organization. Transport and Location. Future Transportation. B – Transport and Spatial Organization. 1. Global Spatial Organization. 2. Regional Spatial Organization. Analysis. . of . Social Media Data . Shaowen Wang. CyberInfrastructure and Geospatial Information Laboratory (CIGI). Department of Geography and Geographic Information Science. Department of Computer Science. Daniel J. Chi. , . Alla. . Chavarga. , Taylan S. Ergun, . Stavros . Hadjisolomou. , . Kamil. . Kloskowski. , Israel Abramov . Applied Vision Institute, Psychology Dept., Brooklyn College/CUNY. . Human vision is based on 3 different cones types. Hecht (1949) predicted that missing one type of cone (color blindness) should improve visual acuity; he failed to confirm this. We compared measurements of color vision (Farnsworth-. 3. Filtering . Filtering image data. is a . standard process . used in almost all image processing systems. . Filters. are used to remove . noise. from digital image while keeping the details of image preserved. . the case of SWITCH. Tim Callan. Economic and Social Research Institute. Overview. Context: the role of SWITCH. S. imulating . W. elfare and . I. ncome . T. ax . CH. anges. A tour of the SWITCH model.