“Spatial analysis is the process of analysing the relationship between locations, attributes, and the relationship of features through analytical techniques. Spatial analysis defines the relationship b”
This module looks at a variety of spatial analysis techniques that can be used to answer geographic questions.
Goal: You are a resident of a neighbourhood and have been provided with crime data and police stations data. Use the datasets to answer interesting questions about your area.
Questions:
Name | Expectation |
---|---|
Data |
crime.csv from stats-analysis, police_stations, districts, ne_10m_roads from stats-analysis/ne.sqlite |
Count Algorithm |
Points In polygon |
Sum Algorithm |
Sum line lengths |
length expression |
$length or length($geometry) |
Diagram |
Bar Chart |
Virtual layer |
select a.*,b.geometry from crime as a join police_station as b on a.name = b.name |
Spatial analysis is the crux of GIS. It allows us to answer complicated questions that with relations to spatial data. When undertaking spatial analysis it is important to categorize the problem and define the category of tools you will be using. Effective spatial analysis requires an intelligent user.
Layers a loaded in QGIS does not show the geometry definition in the attribute table. QGIS can still access the geometry for the layers and through this, some spatial operations can be done which are based on the geometry of the layers. Example of geometry functions available in QGIS include $area used to calculate the area of polygons and $length which is used to calculate the length of line features.
Because humans are very good at interpreting visual data it is important to provide the outputs visually. Symbolisation acts as a nice visualisation tool. QGIS provides diagram tools for visualisation. The tools available are pie charts and Histogram.
Which statement is true with regards to attribute based join:
Which of these is an example of spatial operation:
Can you see the geometry definition of features in the attribute table: