Merge branch 'main' into dev

content/Modul_3/en_module_3_overview.md

@@ -17,9 +17,11 @@ values and see their spatial distribution.
 
 | __Chapter__ | __Competences & Objectives__ |
 | ----------- | ---------------------------- |
-| __[Chapter 1: Digitisation](/content/Module_3/en_qgis_digitalisation.md)__ | At the end of this chapter, you should: Understand the process of digitisation; Know how to create and edit vector data; Know which digitising errors to avoid. | 
-| __[Chapter 2: Geodata Classification](/content/Module_3/en_qgis_data_classification.md)__ | At the end of this chapter, you should: Know how to classify geodata in order to gain useful insights; Know how and when to use categorised classification; Know how and when to use graduated classification. |
-| __[Chapter 3: Geodata Selection and Queries](/content/Module_3/en_qgis_data_queries.md)__ | At the end of this chapter, you should: Know how to select features manually; Know how to select features based on attributes; Know how to formulate a data query with the Expression builder; Know how to select features by location; Know the geometric operators. | 
-| __[Exercises for Module 3](/content/Module_3/en_qgis_modul_3_exercises.md)__ | Here, you can find all the exercises for module 3. | 
+| __[Chapter 1: Digitisation](/content/Modul_3/en_qgis_digitalisation.md)__ | At the end of this chapter, you should: Understand the process of digitisation; Know how to create and edit vector data; Know which digitising errors to avoid. | 
+| __[Chapter 2: Geodata Classification](/content/Modul_3/en_qgis_data_classification.md)__ | At the end of this chapter, you should: Know how to classify geodata in order to gain useful insights; Know how and when to use categorised classification; Know how and when to use graduated classification. |
+| __[Chapter 3: Geodata Selection and Queries](/content/Modul_3/en_qgis_data_queries.md)__ | At the end of this chapter, you should: Know how to select features manually; Know how to select features based on attributes; Know how to formulate a data query with the Expression builder; Know how to select features by location; Know the geometric operators. | 
+| __[Chapter 4: Georeferencing](/content/Modul_3/en_qgis_georeferencing.md)__ | At the end of this chapter, you should: Know how to georeference a map in QGIS; know how to set the transparency of a georeferenced (raster) layer; Know how to digitise vector features from a georeferenced map. | 
+| __[Exercises for Module 3](/content/Modul_3/en_qgis_modul_3_exercises.md)__ | Here, you can find all the exercises for module 3. | 
+
 
 <!--ADD: after revamp of chapter 2 this needs to be adjusted-->

content/Modul_4/en_module_4_overview.md

@@ -4,7 +4,12 @@ This chapter focuses on the visualisation and representation of Geodata. The fir
 
 | __Chapter__ | __Competences & Objectives__ |
 | ----------- | ---------------------------- |
-| __[Chapter 1: Symbology and Colours](/content/Modul_4/en_qgis_map_design_I.md)__ | At the end of this chapter you should: Know the different visual variables; Know how to open the styling panel; Know how to configure the symbology, colour, and labels for vector data; Know what to consider when visualising certain types of information; Know how to load and save styles. |
-| __[Chapter 2: The Print Layout](/content/Modul_4/en_qgis_map_design_2.md)__ | At the end of this chapter, you should: Know the basics of good map composition; Understand the print layout composer in QGIS; Know which elements are essential for a completed map; Know how to create map templates; Know how to use the Atlas function. | 
-| __[Chapter 3: Examples of Good Map Design](/content/Modul_4/en_qgis_map_examples.md)__ | At the end of this chapter, you should: Know a few examples of good map design and how to recreate them; Know good practices and which mistakes to avoid; Know the four semiological errors. | 
+| __[Chapter 1: Symbology and Colours](/content/Modul_4/en_qgis_map_design_I.md)__ | At the end of this chapter, you should: Know the different visual variables; Know what to consider when visualising certain types of information; Know how to load and save styles. |
+| __[Chapter 2: Styling Vector Data](/content/Modul_4/en_qgis_styling_vector_data.md)__ | At the end of this chapter, you should: Know how to open the styling panel; Know how to configure the symbology and colour for vector data. |
+| __[Chapter 3: Labels for Vector Data](/content/Modul_4/en_qgis_labels_vector.md)__ | At the end of this chapter, you should: Know how to set up labels for vector and know what to consider when setting up labels. | 
+| __[Chapter 4: Exporting and Importing Styles](/content/Modul_4/en_qgis_working_with_styles.md)__ | At the end of this chapter, you should: Know how to import and export styles in QGIS, know how to share styles with colleagues to facilitate collaborations. |
+| __[Chapter 5: Symbologiy for Raster Data](/content/Modul_4/en_qgis_symbology_raster.md)__ | At the end of this chapter, you should: Know whats different about styling raster data compared to vector data, know how to set up a colour ramp for raster data. |
+| __[Chapter 6: The Print Layout](/content/Modul_4/en_qgis_map_design_2.md)__ | At the end of this chapter, you should: Know the basics of good map composition; Know which elements are essential for a completed map; Know how to create map templates; Know how to use the Atlas function. | 
+| __[Chapter 7: Understanding the Print Layout Composer](/content/Modul_4/en_qgis_understanding_print_layout.md)__ | At the end of this chapter, you should: Understand the print layout composer in QGIS; Know how to add and configure elements to the print layout; know how to export finished maps; know how to create and use map templates; know how to use the Atlas function. | 
+| __[Chapter 8: Good Map Design & Semiological Errors](/content/Modul_4/en_qgis_map_examples.md)__ | At the end of this chapter, you should: Know a few examples of good map design and how to recreate them; Know which semiological errors to avoid. | 
 | __[Exercises for Module 4](/content/Modul_4/en_qgis_modul_4_exercises.md)__ | Here you can find all the exercises related to module 4. | 

content/Modul_4/en_qgis_labels_vector.md

@@ -1,4 +1,4 @@
-## Labels for vector data
+## Labels for Vector Data
 
 Labels are text that display information or values of the data. In QGIS, you can either select __Single Labels__ or 
 __Rule-based Labelling__. For each option, an attribute (`value`) that will be displayed on the map. For example, the 

content/Modul_4/en_qgis_map_design_2.md

@@ -1,4 +1,4 @@
-# Map Design: The Print layout
+# The Print layout
 
 The print layout in QGIS is where you design and finalise the map in order to print or export it as a PDF (or file format of your choice). Here you can add important elements such as the legend, title, explanatory text, and anything you need to create a comprehensive map. By adding layout elements (legend, title, scale bar, sources, etc.) to a map, you provide your audience with the necessary information to contextualise and evaluate the information shown on the map.
 

content/Modul_4/en_qgis_map_examples.md

@@ -1,12 +1,7 @@
 # Good Map Design & Semiological Errors
 
-🚧This page on the training platform is under ⚠️construction⚠️🚧
 
-In this chapter we will discuss well designed maps and give examples of how to recreate specific design elements in QGIS. A second part of this chapter will focus on common mistakes and good practices when designing maps.
-
-
-
-In this section, we will present some well-designed maps and discuss how to create similar maps. If you need further examples for good map design, check out these websites/repositories:
+In this chapter we will discuss well designed maps and give examples of how to recreate specific design elements in QGIS. A second part of this chapter will focus on common semiological missteps. If you need further examples for good map design, check out these websites/repositories:
 
 - [impact-initiatives.org/resource-centre maps](https://www.impact-initiatives.org/resource-centre/?category%5B%5D=information_products&category%5B%5D=data_methods&type%5B%5D=281&order=latest&limit=10)
 - [geo.msf.org maps](https://geo.msf.org/catalogue/DOCID-1877329211-4979?from=0&sort=_score&desc=true)
@@ -87,19 +82,53 @@ Infrastructure Map Kunduz Province
 ```
 -->
 
-## Common Semiological Errors
+## Common Missteps in Semiology
 
 <!---ADD: Insert Image examples for these errors-->
 
-### 1. Proportional circles vs. solid colors
+### 1. The Modifiable Areal Unit Problem
 
 ```{caution}
-DO NOT represent __quantitative__ data with a __solid colour__.
+Be careful when representing data in administrative regions. 
 ```
 
-This is one of the most common mistakes in mapping. While this representation is graphically appealing, it is still false and distracts from the message of the map.
+The Modifiable Areal Unit Problem (MAUP) is a statistical bias that arises when spatial data is aggregated into regions. It highlights how the results of spatial analysis can change depending on how data is grouped into areal units (spatial zones).
 
-It is a mistake because:
+The Modifiable Areal Unit Problem has two key components:
+
+__Scale Effect:__
+
+The scale of aggregation (small vs. large areas) affects the results.
+
+- When smaller units (e.g., census blocks) are used, the analysis may capture fine-grained local variations.
+- When larger units (e.g., counties or states) are used, local variations get smoothed out, and the results may show broader trends. For example, average income might vary significantly at the neighborhood level but look more uniform at the county level.
+
+__Zoning Effect:__
+
+The shape and arrangement of the zones used for aggregation can also affect the results.
+
+- Changing the boundaries of zones (e.g., splitting a city into east-west vs. north-south regions) can lead to different outcomes, even if the total population or data remains the same. This happens because boundaries influence how values are averaged or summed.
+
+__Why is this important in GIS?__
+
+- Policy Decisions: If the analysis depends on arbitrary boundaries, decisions (e.g., allocating resources) might be based on misleading results.
+- Spatial Statistics: Correlations, regressions, and other analyses involving spatial data can be biased due to MAUP.
+
+```{figure} /fig/en_modifiable_areal_unit_problem_diagram.png
+---
+name: modifiable_areal_unit_problem
+width: 500 px
+---
+Visualising the Modifiable Areal Unit Problem: The same indicator represented at three different scales (Source: Kitchin, Rob & Lauriault, Tracey & McArdle, Gavin. (2015). Knowing and governing cities through urban indicators, city benchmarking and real-time dashboards. Regional Studies, Regional Science. 2. 6-28. 10.1080/21681376.2014.983149. )
+```
+
+### 2. Proportional circles vs. solid colors
+
+```{caution}
+Be cautious when representing __quantitative__ data with a __solid colour__.
+```
+
+While it is graphically appealing, representing quantitative data with solid colours can lead to problems and distract from the message of the map:
 
 - You lose the __order relationship between the data__ (a circle can be twice as big as another one, a colour cannot be "twice as dark")
 - Countries with a large surface area stand out visually (e.g. Russia in the example below)
@@ -108,7 +137,7 @@ It is a mistake because:
 
 <!---Add example-->
 
-### 2. Color gradient vs. distinct color palette
+### 3. Color gradient vs. distinct color palette
 
 ```{caution}
 DO NOT use a __separate__ colour palette to represent __ordered entities__
@@ -121,16 +150,16 @@ It is a mistake because:
 - By using a differentiating colour variable, __you lose the ordinal relationship between entities__. Instead, a __gradient of the same colour__ that should be used.
 - Different colours are used to differentiate between distinct entities.
 
-### 3. Gradient in a single colour vs. Gradient between two colours
+### 4. Gradient in a single colour vs. Gradient between two colours
 
 ```{Caution}
-DO NOT use a gradient across two different colours for data that is always positive (or negative).
+Be cautious when using a __gradient across two different colours__ for data that is __always positive__ (or negative).
 ```
 
-This is a mistake that often occurs because our brains are used to prioritising certain colours, especially green to red, or blue to red. We must remember that __if our values do not have a meaningful zero point, we must stay in the same single colour and use different shades of that colour to indicate different values.
+This is a difficult because our brains are used to prioritising certain colours, especially green to red, or blue to red. We must remember that __if our values do not have a meaningful zero point__, it might be better to stay in the same single colour and use different shades of that colour to indicate different values. Alternatively, a colour gradient that is not diverging can be used. 
 <!--What about height?-->
 
-A gradient between two colours can be used when it is necessary to show a gradation that can go from negative to positive. As for temperatures, it makes sense to distinguish negative values (in shades of blue for example) and positive values (in shades of red).
+A diverging gradient between two colours can be used when it is necessary to show a gradation that can go from negative to positive. As for temperatures, it makes sense to distinguish negative values (in shades of blue for example) and positive values (in shades of red).
 
 It is a mistake because:
 
@@ -139,7 +168,7 @@ It is a mistake because:
 - The map will send a message of divergence, of opposition between certain values, when we are simply trying to represent a hierarchy between values
 - In this way, the colour itself directly indicates information about the trend (positive/negative or increasing/decreasing).
 
-### 4. Limited geometric symbols vs. complex icons and symbols
+### 5. Limited geometric symbols vs. complex icons and symbols
 
 ```{Caution}
 DO NOT use __too many symbols__ in a thematic map

content/Modul_4/en_qgis_styling_vector_data.md

@@ -61,7 +61,7 @@ Most simple markers consist of a __fill__ and an __outline__. Depending on the t
 - You can either style a single symbol for each layer or use different styles based on a [categorisation method](/content/Modul_3/en_qgis_data_classification.md). 
 
 In the Symbology Tab, you can select between various symbolization 
-methods (see {numref}`symbolisation_methods_m4`). The most important ones are 
+methods (see {numref}`symbolisation_methods_m4`). The most important ones are __Single Symbol__, __Categorised__, __Graduated__, and __Rule-based__. 
 
 ```{figure} /fig/en_3.36_m4_symbolisation_methods.png
 ---
@@ -331,7 +331,6 @@ width: 500px
 ---
 Regions affected by explosions in Nigeria
 ```
-:::
 
 :::{dropdown} Video: Set up different symbols in a single layer
 

content/Modul_4/en_qgis_symbology_raster.md

@@ -1,4 +1,4 @@
-## Symbology for raster data
+## Symbology for Raster Data
 
 As we have already learned, raster data are basically a grid of pixels with different (numerical) values. As such, you can't style the shape, fill or outline of raster data. Raster data is visualized by assigning a colour ramp to the pixel value. QGIS offers several options to visualise raster data. For example, you can create a hillshade with digital elevation model (DEM). 
 

content/Modul_5/en_module_5_overview.md

@@ -5,6 +5,6 @@ This chapter introduces more intermediate GIS operations that you will most like
 
 | __Chapter__ | __Competences & Objectives__ | 
 | ----------- | ---------------------------- |
-| __[Chapter 1: Spatial Geodataprocessing](/content/Modul_5/en_qgis_spatial_tools.md)__ | At the end of this chapter, you should: Know how to perform clips, buffers, dissolves, or spatial joins; Know how to select by location, or create centroids. |
-| __[Chapter 2: Non-Spatial Geodataprocessing](/content/Modul_5/en_qgis_non_spatial_tools.md)__ | At the end of this chapter, you should: Know how to use table functions; Know how to perform non-spatial data queries; Know how to perform non-spatial joins. |
+| __[Chapter 1: Spatial Data Processing](/content/Modul_5/en_qgis_spatial_tools.md)__ | At the end of this chapter, you should: Know how to perform clips, buffers, dissolves, or spatial joins; Know how to select by location, or create centroids. |
+| __[Chapter 2: Non-Spatial processing](/content/Modul_5/en_qgis_non_spatial_tools.md)__ | At the end of this chapter, you should: Know how to use table functions; Know how to perform non-spatial data queries; Know how to perform non-spatial joins. |
 | __[Exercises for Module 5](/content/Modul_5/en_qgis_modul_5_exercises.md)__ | Here you can find all exercises for module 5. |