SOLUTION: Spatial Regression and Surface Analysis | My Assignment Tutor

1Session 9 – Near Things More Related Than Distance Things in London(SpatialDependence, Spatial Regression and Surface Analysiswith GeoDa and QGIS)Objectives: To analyse spatial dependence / correlation for geographic profiling andreasoning. To analyse spatial regression for analytic prediction modelling. To interpolate pointevents and analyse raster data with surface techniques.Task 1: Spatial Dependence / Correlation of Crimes and Deprivation in LondonProblem solving: Measuring, mapping and analysing spatial dependence / correlationof crimes and deprivation to support policing strategiesFunctionality: Moran’s I in GeoDaData set: Crime variables and Multiple Index of Deprivation by London BoroughInput the Shape file of “london_life_polygon.shp” in GeoDa, and create a weights filefor calculating Moran’s I:Geoda -> Tools -> Weights -> Create (suggest to select Rook Contiguity)On “london_life_polygon.shp”, measure spatial dependence with followingfunctionalities by variables of ‘DEPRIV’ (score of deprivation), ‘CRIME_1000’ (totalcounts of crime per thousand persons), ‘BURGLARY’ (counts of burglary per thousandpersons), ‘CRIM_DAMAG’ (counts of crime damage per thousand persons),‘DRUG_OFFEN’ (counts of drug offence per thousand persons), ‘VEHICLES’ (counts ofvehicle theft per thousand persons), ‘VIOLENCE’ (counts of violence crime perthousand persons).GeoDa -> Space -> Univariate Moran’s I-> Univariate Local Moran’s IDoes deprivation has strong spatial dependence? Which type of crime hashighest spatial dependence? What does the Univariate Moran’s I imply fordeprivation, total counts of crime and counts of burglary at the geographicscale of borough? Copy Moran Scatter Plot and Cluster Map of ‘DEPRIV’,‘CRIME_1000’ and ‘BURGLARY’ to your portfolio.On “london_life_polygon.shp”, measure spatial correlation with followingfunctionalities by the pair of ‘DEPRIV’ & ‘CRIME_1000’ and the pair of ‘DEPRIV’ &‘BURGLARY’.GeoDa -> Space -> Bivariate Moran’s I-> Bivariate Local Moran’s IWhat does the Bivariate Moran’s I imply for the pair of ‘DEPRIV’ andCRIME_1000’ and the pair of ‘DEPRIV’ and ‘BURGLARY’ at the geographic scaleof borough? Copy Moran Scatter Plots and Cluster Maps to your portfolio.2On “london_life_polygon.shp”, measure smoothed (or adjusted) spatial dependencewith following functionalities by rates of ‘BURGLARY’ (event variable) / ‘CRIME_1000’(base variable), and ‘DRUG_OFFEN’ (event variable) / ‘CRIME_1000’ (base variable).GeoDa -> Space -> Moran’s I with EB Rate-> Local Moran’s I with EB RateCan you see any difference in results for ‘BURGLARY’ and ‘DRUG_OFFEN’ fromMoran’s I with EB Rate and Univariate Moran’s I ?Try “london_ward_met_per1000.shp” with Univariate Local Moran’s I. by variables of‘Total’ (total counts of crime per thousand persons) and ‘Burglary’ (counts of crimeburglary per thousand persons).Find out any difference in spatial dependence between borough-level andward-level caused by MAUP. Copy Moran Scatter Plots and Cluster Maps toyour portfolio.Try “london_pop20112016_plg.shp”, measure spatial-temporal dependence withfollowing functionalities by the population estimates in 2011and 2016.GeoDa -> Space -> Differential Moran’s I-> Differential Local Moran’s IWhat does the Differential Moran’s I imply for temporal change of populationat the geographic scale of borough? Copy Moran Scatter Plots and ClusterMaps to your portfolio.Task 2: Spatial Regression of Health Indicators in LondonProblem solving: Modelling spatial Regression of health indicators to supporthealthcare strategiesFunctionality: Regression in GeoDaData set: Helath variables and Multiple Index of Deprivation by London BoroughOn “london_life_polygon.shp”, run regression modelling with following functionalityby ‘LIFE_MALE’ (life expectancy of male residents) as Dependent Variable and‘DEPRIV’ (score of deprivation), ‘P_SMOKE’ (population percentage of smokers),‘P_BINGE’ (population percentage of binge drinkers), ‘P_OBESE’ (populationpercentage of obesity) and ‘P_HEALTHY’ (population percentage of healthy residents)as Covariates. Please try both Classic and Spatial Lag models.GeoDa -> RegressionCopy regression reports to your portfolio.Try Session9_regression.r and copy results of regression modelling to yourportfolio. Please compare results from GeoDa and R.3Task 3: Population Surface in HaringeyProblem solving: Develop surfaces of social variables with interpolation to compareor integrate data at different spatial scalesFunctionality: interpolation in QGISData set: Population centroids of LSOA in HaringeyAdd “Population_Haringey_LSOA2011PWC.shp” and “haringey_boundary.shp”. Clickthe button of “Zoom Full”.QGIS -> Raster -> Interpolation(In the window of Interpolation, Select Inverse Distance Weighting (IDW) asInterpolation method. Choose “Distance Coefficient” as 4, click “Set to currentextent”, take default numbers of columns and rows as 300×300)QGIS -> Raster -> Extraction -> ClipperQGIS -> Layer -> Properties -> Style(right click of mouse -> Properties -> Style -> Render type -> Singlebandpseudocolor, then change the legend)(could be choose 5 classes)QGIS -> Raster -> Extraction -> Contour(try interval of contour lines as 100)Try interpolation with different methods and parameters. Is interpolationsensitive to methods and parameter settings? (just try, don’t need to copy toportfolio)Task 4: Terrain Surface around Waterloo BridgeProblem solving: Explore natural surfaces with remote sensing techniques to provideinformation for spatial data analysisFunctionality: Terrain Analysis in QGISData set: LiDA DSM around Waterloo BridgeAdd “TQ3080_DSM_2M.asc”, Analysis the DSM with following functionalities:QGIS -> Raster -> Terrain Analysis -> Slope-> Aspect-> Hillshade-> Relief4Please export specified Scatter Plots and Cluster Maps from Task 1 (three variables forUnivariate Local Moran’s I, one pair of variables for Bivariate Local Moran’s I, one variable forLocal Moran’s I with EB Rate, one variable for “london_ward_met_per1000.shp” withUnivariate Local Moran’s I, the population estimates in 2011and 2016 for Differential LocalMoran’s I), and put them into your portfolio.Please copy results of regression modelling from Task 2, export the interpolated rasterimage from Task 3, and put them into your portfolio.(QGIS: Project -> Save as Images, GeoDa: right click of you mouse -> Save Image as)