1Session 5 – Thinking London Spatially Further (Spatial Query with SpatiaLite Advance)Objectives: To develop skills of spatial query with SQL in SpatiaLite. Explore a range ofspatial variables of London.Connect the existing SQLite Database “test.sqlite”Task 1: Spatial Extent of LondonUnion multiple conditionsUsing spatial functions of “Area”, “Mbr” along with “Max”, “Min”Find out London boroughs with the … Continue reading “Thinking London Spatially Further | My Assignment Tutor”

1Session 5 – Thinking London Spatially Further (Spatial Query with SpatiaLite Advance)Objectives: To develop skills of spatial query with SQL in SpatiaLite. Explore a range ofspatial variables of London.Connect the existing SQLite Database “test.sqlite”Task 1: Spatial Extent of LondonUnion multiple conditionsUsing spatial functions of “Area”, “Mbr” along with “Max”, “Min”Find out London boroughs with the smallest / largest area, with the lowest / highestpopulation density, as the southernmost / northernmost / most east / most westborough.Task 2: Neighbour BoroughsJoin tables with multiple conditionsUsing spatial relation of “Touches”Find out adjacent London boroughs.Task 3: An Isolated Island in London?Insert a new row as the isolated islandLeft join neighbour borough to make sure that all London boroughs includedUsing spatial relation of “Disjoint”Using post-processing of “Having” to reduce the result-set of queryFind out isolated district.Task 4: Business / Services within Boroughs (Points within Polygons)Open Visual Shapefile “credit_union.shp”Join or Left Join the Point table and the Polygon tableUsing spatial relation of “Contain”Find out which credit unions within which London boroughs.Try the same procedure with the table of “UndergroundStations”Find out which underground stations within which London boroughs.Task 5: Near Neighbour Business / Services (Distance between Points)(Need to load Shapefile “credit_union.shp”)Using spatial relation of “Distance” calculated by “Length”.Find out all credit Unions within distance