PPT-Spatial Point Processes

Eric Feigelson Penn State University Arcetri Observatory April 2014 Background on Spatial Point Processes Study of spatial point processes is a part of the field of spatial statistics that includes graph map network data lattice data eg images . T state 8712X action or input 8712U uncertainty or disturbance 8712W dynamics functions XUW8594X w w are independent RVs variation state dependent input space 8712U 8838U is set of allowed actions in state at time brPage 5br Policy action is function Brazilian cities. An ESRC pathfinder project. http://www.ccsr.ac.uk/documents/spatial_segregation_of_poverty.pdf. Kuznetz. Curve (1958). Source: Wilkinson & Pickett, The Spirit Level (2009). Preston Curve. 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. . Adam Dennett*, Kimberley . Claydon. †. , Pablo . Mateos. †. *Centre for Advanced Spatial Analysis. †Department of Geography. University College London. Presentation to the British Society for Population Studies – Annual Conference, 9. Sixth International Longevity Risk and Capital Markets Solutions Conference. Sydney Australia. 9 and 10 September 2010. Michael Sherris (with Andy Tang). Australian School of Business, UNSW. Mortality rates are known to vary by geographical location and to depend on socio-economic factors. . Chapter One. Spatial Analysis. Patterns of spatially distributed points.. Correlation with environmental variables.. Interpolations and predictive models.. Spatial autocorrelation -> spatial patterns, aggregation. Based on distance to neighbors. Kaplan-Meier estimator, Moran’s I.. Dr Kirk Harland. What is a Spatial . Microsimulation. ?. Static Spatial . Microsimulation. Deterministic Reweighting. Conditional Probabilities. Simulated Annealing. Dynamic . Microsimulation. This . Lu Jiang. 1. , Wei Tong. 1. , Deyu Meng. 2. , Alexander G. Hauptmann. 1. 1. . School of Computer Science, Carnegie Mellon University. 2. School of Mathematics and Statistics, Xi'an . Jiaotong. University. ©. The following pastels are visual representations of the initial . “. contact. ”. with extraterrestrials through energetic frequencies and signals.. Las . siguientes. . imagenes. son . representaciones. D.M. Bannerman, M.A. Good, S.P. Butcher, M. Ramsay & R.G.M. Morris. GROUP A3. Bonnie Chan | Anastasia Christopher | Herman Gill . Marisa Leung | Sarah McNeil | Carol . Rego. Overall Evaluations. - the Shetland experience. Rachel . Shucksmith. Marine Spatial Planning Manager. NAFC Marine Centre UHI. Shetland. . Bergen. . Scotland . Spatial Planning Framework . 2006- . SMSP. . i. nitiated through . What can we do with GIS?. SPATIAL STATISTICS. What can we do with GIS?. SPATIAL STATISTICS. We utilize map data! . What can we do with GIS?. Designed for use with maps. Uses either . RASTER. or . Dong Xie. *, Feifei Li*, Bin Yao. . , Gefei Li. . , Liang Zhou. . , . Minyi. . Guo. . Spatial Data is Ubiquitous!. Location-based Services. IoT. Projects & Sensor Networks. Social Media. Problems of Existing Systems. and . Downscaling . of. Climate Variables. Jared . Oyler. – FOR 532 . 11/17/2010. Climate Variables. What are the minimum required climate variables to drive an ecosystem model like Biome-BGC?. Surface air temperature.