::::{grid} auto :::{grid-item-card} :class-card: sd-text-center sd-rounded-circle :link: https://giscience.github.io/gis-training-resource-center/english/content/en/intro.html {octicon}`home-fill;1.5em;sd-text-danger` ::: :::: # 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](https://giscience.github.io/gis-training-resource-center/english/content/en/Module_3/en_qgis_data_queries.html#geometric-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 layers. - 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__ create points in the geometric centre of the geometries of a layer. This is especially useful when creating graduated symbol maps :::{figure} ../../../fig/en_module5_spatial_geodataprocessing.PNG --- width: 750 px name: en_module5_spatial_geodataprocessing --- Different spatial geoprocessing tools. Source: Adapted from [Saylor Academy](https://saylordotorg.github.io/text_essentials-of-geographic-information-systems/s11-geospatial-analysis-i-vector-o.html) ::: 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 {numref}`en_module5_spatial_geodataprocessing`). ## 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](en_qgis_non_spatial_tools.md)" 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 resulting 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. ::::{card} __Humanitarian Example:__ ^^^ *A flood depth model is available, and the goal is to determine which buildings are flooded under this scenario. This can be achieved by performing a spatial join to add the flood depth to the polygon layer containing the houses.* *The resulting map could look something like this:* :::{figure} ../../../fig/en_flood_damage_assessement_libya.png --- name: en_flood_damage_assessement_libya width: 450 px --- 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. ::::{tab-set} :::{tab-item} 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 return the circles __1, 2, and 3__. ::: :::{tab-item} 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. ::: :::{tab-item} Equal The algorithm 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). ::: :::{tab-item} 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. ::: :::{tab-item} 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. ::: :::{tab-item} 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. ::: :::{tab-item} 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". ::: :::{tab-item} 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 a line (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. ::: :::: :::{figure} ../../../fig/en_select_by_location.png --- width: 600 px name: en_select_by_location --- Looking for spatial relations between layers
(Source: [QGIS Documentation](https://docs.qgis.org/3.28/en/docs/user_manual/processing_algs/qgis/vectorgeneral.html?highlight=join%20attributes%20location), Version 3.28) ::: ### Exercise: Performing a spatial join :::{admonition} Now it's your turn! :class: tip Practical exercise is crucial to understand how GIS, and QGIS, works. You can follow along by downloading the necessary data. ::: In the example above ({numref}`en_spatial_join_example`), we have a dataset containing the healthsites by healthsite.ioand 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". :::{figure} ../../../fig/en_spatial_join_example.png --- name: en_spatial_join_example width: 400 px --- An example of a situation where you will use a spatial join (Source: BRC) ::: ::::{margin} :::{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. ::: :::: ::::{dropdown} __Tool:__ 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 {numref}`en_spatial_join_1`) dictates which geometric features will be copied to the new layer. - The second input layer (see "By comparing to" in {numref}`en_spatial_join_1`) 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. :::{figure} ../../../fig/en_spatial_join_1.PNG --- width: 450 px name: en_spatial_join_1 --- The "Join Attributes by Location"-tool in QGIS 3.36. ::: :::: 1. Download the necessary datasets from HDX - [nigeria-healthsites-shp](https://data.humdata.org/dataset/nigeria-healthsites) - [nga_adm_osgof_20190417.zip](https://giscience.github.io/gis-training-resource-center/english/content/en/Module_5/en_qgis_spatial_tools.html) 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 {numref}`join_by_location_ex1`). 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` as 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. 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 {numref}`spatial_join_ex1_results_categorised`). Note that the points in the original dataset which were outside of Nigeria's border have been discarded as they could not be joined. :::{figure} ../../../fig/spatial_join_ex1_results_categorised.png --- name: spatial_join_ex1_results_categorised width: 500 px --- 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. - There are also the tools __"Join attributes by location (summary)"__ and __"Join attributes by nearest"__. :::::{tab-set} ::::{tab-item} 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 algorithm 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. :::{figure} ../../../fig/en_spatial_join_3.PNG --- width: 450 px name: en_spatial_join_3 --- Screenshot of the tool Join attributes by location (summary) in QGIS 3.36. ::: :::: ::::{tab-item} 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. :::{figure} ../../../fig/en_spatial_join_2.PNG --- width: 450 px name: en_spatial_join_2 --- 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](https://docs.qgis.org/3.34/en/docs/user_manual/processing_algs/qgis/vectorgeneral.html#join-attributes-by-location) ::: ### Exercise: 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](https://nexus.heigit.org/repository/gis-training-resource-center/Module_5/Spatial_Join/State_Unity_South_Sudan.zip):
__State_Unity_South_Sudan.shp__ - [Satellite detected water extents between 11 and 15 August 2023 over South Sudan](https://data.humdata.org/dataset/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. :::{dropdown} Solution: Calculate sum of affected population and flooded area for the Area of interest ::: ## Self-Assessment Questions ::::{admonition} Test your knowledge :class: note 1. __What differentiates a spatial processing tool from a non-spatial processing tool?__ :::{dropdown} Answer A __spatial processing__ tool operates on the geometry (location, shape, spatial relationship) of features (points, lines, polygons, or raster cells) and uses that spatial information (e.g., distance, adjacency, overlap) in its operation. A __non‑spatial processing__ tool operates only on attribute or tabular data without regard to the geometry (for example sorting a table, calculating a field, joining tables by key). ::: 2. __Name and briefly describe at least three common spatial tools or operations covered (e.g. buffer, clip, dissolve, intersect, union).__ :::{dropdown} Answer - __Buffer:__ Creates a zone at a specified distance around input features (points, lines or polygons). For example, around a road line you create a 100 m buffer zone polygon that represents all area within 100 m of the road. - __Clip:__ Uses one layer (the “clip” layer) to trim or cut another layer so that only the portion of the input layer falling inside (or maybe outside) the clip layer remains. Effectively extracts a subset of geometry. - __Dissolve:__ Merges adjacent or overlapping features in a layer based on a shared attribute (or simply removes internal boundaries) so that features become larger aggregated shapes. For instance, combining many small administrative units into one larger one based on a region code. ::: 3. __If you have a layer of roads and you apply a buffer of 100 m around each road, what is the resulting geometry and what is one possible use case__ :::{dropdown} Answer - The output will be polygon features (zones) that represent all areas within 100 m of each road. So if your input roads are line features, after the buffer you will have polygon(s) that “wrap” around each road line, extending on both sides by 100 m (assuming a simple planar buffer). - A buffer could be used to buffer a cyclone track to approximate the cyclone-affected region (see [QGIS Trigger Workflow for Madagascar](https://giscience.github.io/gis-training-resource-center/english/content/en/GIS_AA/en_qgis_cyclone_trigger_madagascar.html)). ::: 4. __Why is it important to check whether input layers have compatible projections / CRSs before running spatial tools?__ :::{dropdown} Answer - If layers have different CRSs (or datums) and you apply a spatial tool without performing a proper reprojection, the geometry calculations (distances, areas, buffers, overlay) may be incorrect or misleading. For example a buffer of “100 m” may in fact be 100 units of a different coordinate system (degrees or feet) so the real world distance is wrong. - Spatial operations rely on accurate geometric relationships; if one layer is in e.g., WGS84 geographic degrees and another is in a projected metre‐based CRS, the mismatch can cause mis‐alignment, stretching, distortion, or errors in results. - Ensuring compatible projections helps maintain spatial accuracy, area/distance correctness, and valid topological relationships (e.g., overlays, intersections) which are critical for meaningful results. ::::