1Session 6 – Preparation / Integration of Spatial Data(Spatial Operation and Transformation with QGIS)Objectives: To gain familiarity in a range of spatial operations through QGIS functionalities.Task 1: Basic Practice to edit Spatial FeaturesPractice following editing functionalities:Layer -> Toggling Editing-> Add Feature, Move Feature, Delete Selected-> Rotate Feature, Simplify Feature-> Reshape Feature, Split Feature-> Add Ring, … Continue reading “Basic Practice to edit Spatial Features | My Assignment Tutor”
1Session 6 – Preparation / Integration of Spatial Data(Spatial Operation and Transformation with QGIS)Objectives: To gain familiarity in a range of spatial operations through QGIS functionalities.Task 1: Basic Practice to edit Spatial FeaturesPractice following editing functionalities:Layer -> Toggling Editing-> Add Feature, Move Feature, Delete Selected-> Rotate Feature, Simplify Feature-> Reshape Feature, Split Feature-> Add Ring, Fill Ring, Delete Ring-> Add Part, Delete Part, Split Part-> Node ToolTask 2: Segregating and Aggregating Spatial Study AreasProblem solving: Segregate / aggregate spatial study areas so that data analysiscould be carried out on different geographic scales, which allows local characteristicsto be take into account.Functionality: Boolean Operations on Vector Data – OverlayData set: Map of Postcode Areas around London, Map of Inner-Outer LondonAdd “postarea.shp” and “london_io.shp”, practice the following functionality:Vector -> Geoprocessing Tools -> Intersect (AND)(input layer as “postarea.shp”,intersect layer as “london_io.shp” )Postcode Area is large area geography. For detail analysis, it is necessary tosegregate it into relative smaller area geography. With Intersect, PostcodeAreas are segregated by Inner London region, Outer London region andregion outside of London. Please look at the example of Postcode Area of “E”.Vector -> Geoprocessing Tools -> Dissolve (OR)(input layer as “postarea.shp”,Dissolve field as ‘S_N’ )In contrast to segregation, for overarch analysis, Postcode Area can beaggregated by common characteristics. In this case of Dissolve, PostcodeAreas are aggregated by South of Thames and North of Thames.Please also see Vector -> Data Management Tools -> Merge vector layers (OR)2Vector -> Geoprocessing Tools -> Difference (NOT)(input layer as “postarea.shp”,difference layer as “london_io.shp” )If only Postcode Areas outside of London need to be analysed, simply cut themap of Postcode Areas by London boundary with Difference.Task 3: Creating Spatial Study AreasProblem solving: Create new spatial study areas (or zone systems) in order to carryout analysis, simulation or impact assessment on such study areas.Functionality: Geoprocessing on Vector DataData set: Map of credit unions, Map of motorways, Map of London boroughsAdd “credit_union.shp” and “motorway.shp”, practice the folloewing functionalities:Vector -> Geoprocessing Tools -> Convex Hall-> Fixed distance bufferWith Convex Hall and Buffer (distance=3000m), a study area are can becreated, which covers all locations of credit unions.With Buffer (distance=1000m), a buffer zone along motorways can be createdwhere environmental impact or economic impact can be assessed.On “postarea.shp”, practice the following functionality:Vector -> Geometry Tools -> Polygon CentoridWith Polygon Centorid, create central points of Postcode Areas. Thesecentorids are useful to represent each Postcode Areas or create a new studyarea (for example, with Convex Hall and Buffer) for specified data analysis.On “credit_union.shp”, practice the following functionalities:Vector -> Geometry Tools -> Delaunay triangulationWith Delaunay Triangulation, impact areas can be created for these CreditUnions for impact studies.Delaunay Triangulation is also often used in interpolation of naturallandscape.Create a catchment area using the following functionalityVector -> Geometry Tools -> Voronoi Polygons (10% buffer region)With Voronoi Polygons, catchment areas can be created around each creditunion. In the same way, GP catchment areas or school catchment areas cancreated. On such catchment areas, demand and supply could be analysed.3On “credit_union.shp” and “london_boroughs.shp”, practice following functionality:Vector -> Data Management Tools -> Join Attributes by Location(Target layer – credit_union,Joint layer: london_boroughs)With Join Attributes by Location, local characteristics can be extracted andassigned on point events. In this case, information of local borough can beassigned on each Credit Union for further analysis (e.g. marketing analysis).Task 4: Preparing Remote Sensing DataProblem solving: Extract height information of all features from remote sensing dataFunctionality: Calculation on Raster DataData set: LiDAR data of DTM and DSM around Ravenscourt Park, Hammersmith,LondonAdd “TQ2278_DTM_2M.asc” and “TQ2278_DSM_2M.asc”, practice followingfunctionality:Raster -> Raster CalculatorIn this case, heights of all features are extracted from (DSM – DTM). Theseheights could be further processed / calculated to derive more information,such as roof slope.Task 5: Working with Data on Different FormatsProblem solving: Extract building height using vector data and raster dataFunctionality: Conversion of vector data and raster dataData set: Map of Building polygon and LiDAR data of DSM around Ravensourt Park,Hammersmith, LondonAdd “tq2278_2m.shp”, practice following functionality:Raster -> Conversion -> Rasterise (Vector to raster)Convert Building polygons to building raster data so that Building data can beused with DSM. In this case, if DSM data are multiplied with Building rasterdata, height values of Building can be extracted from all geographic features.On “TQ2278_DSM_2M.asc”, practice following functionality:Raster -> Conversion -> Polygonise (Raster to vector)DSM data can also be converted to polygons which have heights as attributesand can therefore work with other vector data4Task 6: Handling Non-Spatial AttributesProblem solving: Create two new attribute variables – population density andHousehold sizeFunctionality: Attribute TableData set: Map of London boroughsOn “london_boroughs.shp”, practice following functionality:Layer -> Open Attribute Table -> Toggle editing mode-> Select features using expressionWith Attribute Table, create new variables, calculate / update new variables ofpopulation density and Household sizePlease export the map of Intersect (AND) from Task 2, Voronoi Polygon from Task 3, heightimage from Task 4 (Project -> Save as Images), a CSV table from Task 6 (Save the vectorlayer of London_boroughs as CSV), and put them into your portfolio.Because QGIS is an open source software, to which anyone can make contribution. Do youhave any suggestion to improve these functionalities you practiced in this session?
