Spatial data processing

Introduction

Spatial processing uses spatial information to extract new meaning from GIS data. It does so by using the spatial relationship of different layers or features. Spatial relationships describe how things are located in relation to one another. In humanitarian work, this helps answer critical questions like “Which communities are near a water source?” or “Which areas are isolated from health services?”. Or, we might want to identify the best locations for distributing aid, assess flood risk areas, or plan evacuation routes.

We have already encountered spatial relationships in module 3 in the subchapter on geometrical operators— also called geometrical predicates in QGIS. The table below describes spatial relationships and gives examples when these spatial relationships are relevant in humanitarian aid.

Spatial Relationships

Spatial Relationship	Description	Humanitarian Example
Proximity	How close one thing is to another	Find the nearest shelters to a displaced community
Containment	Whether something is inside another area/polygon	Identify which schools are within a specific conflict-affected zone
Intersection	Identify geometric features that overlap	Look for areas where damaged infrastructure overlaps with vulnerable populations
Adjacency	Geometric features that share a point or a boundary	Identify regions bordering a conflict zone that may be at risk of displacement
Connectivity	How things are connected through networks such as roads, rivers, or even trade routes	Map the shortest path between villages and hospitals to plan emergency evacuations
Direction	Relative position, like north, south, east, west, or relative position to the flow of a river, for example	Locate villages north of a river that are cut off due to flooding and inaccessibility of connecting bridges

QGIS offers a variety of spatial processing tools that we can use to analyse and create new insights using these spatial relationships. For instance:

• Spatial Joins let us join attribute values from one layer to another based on their spatial relationship. This enables us to enrich datasets and incorporate additional information from layers, which can help us understand a situation.

• The overlay operation Clip can be employed to extract specific areas of interest from multiple layers, allowing us to focus our attention where it is most needed.

• The Dissolve operation allows us to simplify geometries by joining geometries from two distinct layer.

• Using Buffer, we can create zones around features to help identify vulnerable areas and plan evacuation routes in the event of a flooding event.

• Centroids creates point in the geometric centre of the geometries of a layer. This is especially useful when creating graduated symbol maps

Fig. 142 Different spatial geoprocessing tools. Source: Adapted from Saylor Academy

In this chapter, we will first explore spatial joins. Spatial joins, for example, allow us to import attributes from one layer to another on the basis of their location in relation to geofeatures in another layer. These Spatial relationships can also be used to select features of a layer. Furthermore, we will go over the spatial processing tools buffer, clip, and dissolve. These operations allow us to combine geometries from two layers in various ways (see Fig. 142).

Spatial joins

Joins are ways to combine two different data layers. In general, there are two types of joins: non-spatial joins and spatial joins.

• Non-spatial joins rely on specific attribute values, which are used as ID-fields, to combine two layers. These are covered in the chapter “Non-spatial processing tools” in this module.

• Sometimes we want to combine information from different layers that don’t share a common value. In these cases, we can use spatial joins, which let us join data based on location rules.

• Spatial joins in QGIS enhance the attributes of the input layer by adding additional information from the join layer, relying on their spatial relationship. This process enriches your data by incorporating relevant details from one layer into another based on their geographical associations.

• In QGIS, a spatial join creates a new layer by comparing the features of one layer to another, depending on their spatial relationship.

• The restulting joined layer receives attributes from both layers based on the chosen parameters.

For example:

• Any point within a polygon should inherit attributes of the polygon.

Humanitarian Example:

We have a flood depth model and we want to find out which buildings are flooded under this scenario. We can find this out by performing a spatial join to add the flood depth to the polygon layer with the houses.

The resulting map could look something like this:

Fig. 143 A building footprint layer combined with a flood extent layer. By joining them, we can assess which houses are at risk to be damaged by flooding (Source: IFRC).

Geometrical operators

Spatial joins rely on the geometrical operators. In the tabs below, you can find the different geometrical operators available in QGIS and how they affect the data processing.

Intersect

Tests whether the geometry of the two layers intersects with one another. The algorithm returns the value “True” (1), if the geometries intersect spatially. This means that they share any portion of space, overlap, or touch. If they don’t overlap, the algorithms returns the value “False” (0). In the picture below, the algorithm will return the circles 1, 2, and 3.

Disjoint

Disjoint features do not share any portion of space. This means that they don’t touch or overlap. In the picture below, the algorithm would output a layer with only the circle 4.

Equal

The algorithms returns a layer with geometries that are exactly the same (all the points and lines are equal). In the picture below, no circles are returned (added to the output layer).

Touch

Tests whether a geometry touches another. The algorithm outputs a new layer with the geometries that have at least one point in common, but their interiors do not intersect. In the image below, only circle 3 is returned.

Overlap

Tests whether geometries overlap. Returns geometries if they share space, are of the same dimension, but are not completely contained by each other. In the image below, only circle 2 is returned.

Are within

Tests whether one geometry is within another. Returns geometries a if they are completely inside of geometry b. Only circle 1 is returned.

Contain

Returns geometries if and only if no points of b lie in the exterior of a, and at least one point of the interior of b lies in the interior of a. In the picture, no circle is returned, but the rectangle would be if you would look for it the other way around, as it contains circle 1 completely. This is the opposite of “are within”.

Cross

Returns geometries that have some, but not all, interior points in common and the actual crossing is of a lower dimension than the highest supplied geometry. For example, a line crossing a polygon will cross as aline (true). Two lines crossing will cross as a point (true). Two polygons cross as a polygon (false). In the picture below, no circles will be returned.

Fig. 144 Looking for spatial relations between layers
(Source: QGIS Documentation, Version 3.28)

Exercise: Performing a spatial join

Now it’s your turn!

Practical exercise is crucial to understand how GIS, and QGIS, works. You can follow along by downloading the necessary data.

Fig. 145 An example of a situation where you will use a spatial join (Source: BRC)

In the example above (Fig. 145), we have a dataset containing the healthsites by healthsite.io and a dataset with the administrative boundaries (adm2) of Nigeria. We want to know in which state each healthsite is located. To do this, we need to use the tool “Join Attributes by Location”:

Tip

You can find and activate the processing toolbox panel by navigating to View > Panels > Processing Toolbox. It should appear on the right side of your screen.

Join attributes by location

This tool takes two input layers and creates a new vector layer which has the attributes of both layers in its attribute table. The first input layer (see “Join to features in” in Fig. 146) dictates which geometric features will be copied to the new layer. The second input layer (see “By comparing to” in Fig. 146) dictates the attributes that will be added to the new layer on top of the attributes of the first input layer. You can select which of these attributes should be transferred to the new layer.

Fig. 146 The “Join Attributes by Location”-tool in QGIS 3.36.

1. Download the necessary datasets from HDX

   • nigeria-healthsites-shp

   • nga_adm_osgof_20190417.zip

2. Unzip the files, create a new QGIS-project, and load the files into the QGIS-project.

3. Search for the tool “Join Attributes by Location” in the processing toolbox and Double-Click on it. A new window will open (see Fig. 147).

4. Use the health facilities layer as the target (“Join to feature in”) and the adm2 layer as the comparison layer (“By comparing to”).

5. Use the are within geometrical predicate.

6. Select the fields to add: ADM2_EN, ADM2_PCODE

7. Select Discard records that could not be joined

8. Click Run to proceed; the log should confirm success.

9. A new (temporary) layer called “Joined features” will appear in your layers-panel

10. Right-click on the layer and select “Export” or “Make Permanent” to save the new layer.

Fig. 147 Setting the parameters to perform the spatial join in QGIS 3.36

Congratulations, we now have added the information about the administrative region to the health facilities layer! We can symbolise the joined layer with the categorised symbology to verify if it worked (see Fig. 148). Note that the points in the original dataset which were outside of Nigeria’s border have been discarded as they could not be joined.

Fig. 148 The different colours for the points indicate that they are located in a different state (adm2).

More spatial join-tools in QGIS

By default, QGIS provides three different tools to perform spatial joins.

• The first, and the most common one, is the tool “Join attributes by location” which we used in the previous exercise.

• Furthermore, there are also the tools “Join attributes by location (summary)” and “Join attributes by nearest”.

Join attributes by location (summary)

This tool is similar to the “Join Attributes by Location”-tool. However, on top of adding the attributes from one layer to another, this algorithms also calculates statistical summaries for the values from matching features in the second layer. These summaries include a wide range of options, such as minimum and maximum values, mean values, as well as counts, sums, standard deviation, and more.

Fig. 149 Screenshot of the tool Join attributes by location (summary) in QGIS 3.36

Join attributes by nearest

This type of spatial join is similar to the other two joins but the joining of features occurs by identifying the closest features from each of these layers. Furthermore, if a maximum distance is specified, only the features that are within this designated distance will be considered as suitable matches for the joining process.

Fig. 150 Screenshot of the tool Join attributes by nearest in QGIS 3.36

Note

A detailed description of the functions and settings of these tools can be found in the QGIS documentation

Exercise 6: Calculate sum of affected population and flooded area for the Area of interest

In the aftermath of flooding events, data on the affected population and the extent of flooding is crucial. This information can be refined from a nationwide dataset to provide specific numbers for individual districts or states. This can aid in identifying the areas most heavily impacted, leading to more efficient relief operations. In the upcoming exercise, we will calculate the total flooding extent in square kilometers and the affected population for Unity State, South Sudan. To accomplish this, we will utilize the Join attributes by location (summary) tool.

1. Load the necessary data for this exercise into your QGIS. Both datasets were downloaded from HDX:

   • South Sudan - Subnational Administrative Boundaries:
     State_Unity_South_Sudan.shp

   • Satellite detected water extents between 11 and 15 August 2023 over South Sudan: Download the folder FL20220424SSD_SHP.zip, unzip it, and search for the file VIIRS_20230811_20230815_MaximumFloodWaterExtent_SouthSudan.shp

2. Locate the tool named Join attribute by location (summary)

   • Choose state boundaries as the target layer for joining features

   • Set intersect as the spatial relationship

   • Select flood extent layer as the comparison layer

   • Specify the fields to be summarized as Area_km2 and Pop

   • Choose sum as the type of summaries to be calculated

   • Click Run to start the process

3. Once completed, you will have access to information on the total affected population and flooded areas for the entire state of Unity.

Solution: Calculate sum of affected population and flooded area for the Area of interest