Introduction to Spatial Data Analysis (Using ArcGIS)

Introduction to Spatial Data Analysis (Using ArcGIS) Doctoral School in Economics, University of Rome La Sapienza Instructors: Filippo Celata (Sapienza), Federico Martellozzo (ParisTech and Sapienza), Luca Salvati (Consiglio per la Ricerca e la Sperimentazione in Agricoltura). Objectives The course aims at introducing participants to the construction, analysis, modelling and mapping of spatial data in a GIS environment. Participants will familiarize with the use of the software Esri ArcGIS and learn both theoretically and practically how to build and to manage vector and raster spatial datasets, what the specificities of spatial data are, how to analyze geographic patterns using spatial analysis tools ‐ including density maps, autocorrelation and spatial clusters analysis, raster analysis, geostatistics and spatial regressions ‐ and how to produce maps. Programme 1) Introduction to ArcGIS and to the construction of spatial datasets – June 3rd, 3‐7 pm (Celata). The specificities of spatial data, spatial analysis and GIS‐based techniques. Vector and raster geodata. Introduction to coordinate systems. Georeferencing techniques. Primary and secondary sources for spatial data. Introduction of geocoding services. 2) Vector data editing and mapping – June 5th, 3‐7 pm (Celata). Introduction to data processing in ArcGIS. Table and spatial association and selection. Geoprocessing techniques. Introduction to geodata editing. Strumenti di conversione dei geodati. Spatial distribution measures, proximity and accessibility analysis. Mapping. 3) Introduction to spatial analysis with ArcGIS ‐ June 12h, 3‐7 pm (Celata). Introduction to spatial statistics. Typologies and specificities of spatial data. Overview of spatial analysis techniques. Spatial concentration analysis and density maps. Measurement and rendering of local and global autocorrelation and spatial clustering indexes. 4) Raster data analysis ‐ June 16th, 3‐7 pm (Martellozzo). The specificities of raster data. How to manage and edit raster datasets in ArcGIS. Introduction to remote sensing and photo‐interpretation. Raster analysis, map algebra and surface‐based indicators. Introduction to spatial networks analysis. 5) Introduction to geostatistics ‐ June 18th, 3‐7 pm (Salvati). Introduction to spatial interpolation and the analysis of aleatory surfaces: statistical tools, spatial interpolation and estimation methods, geostatistics functions and techniques, deterministic methods (Inverse Distance Weighting), probabilistic methods including Kriging. Introduction to geostatistics with ArcGIS. 6) Regression analysis with ArcGIS ‐ June 20th, 3‐7 pm (Salvati). Introduction to regression analysis of spatial data. Ordinary least square, geographical weighted regression and introduction to spatial autoregression methods. How to manage spatial weights matrixes. Introduction to spatial econometrics. When: 3‐20 June 2014, 24 hours (3 CFU) + final exam Where: PC Lab, 5th floor, room 523 Webpage: http://geostasto.eco.uniroma1.it/utenti/celata/spatial.html Software: Esri ArcGIS 10.2 (advanced), extensions: spatial analysis, spatial statistics, geostatistics. To enrol in the course please send an email to: [email protected]