diff --git a/_images/en_greenland_africa.png b/_images/en_greenland_africa.png new file mode 100644 index 000000000..103fa531c Binary files /dev/null and b/_images/en_greenland_africa.png differ diff --git a/_sources/content/Modul_2/en_qgis_geodata_concept.md b/_sources/content/Modul_2/en_qgis_geodata_concept.md index aea845947..289e512ff 100644 --- a/_sources/content/Modul_2/en_qgis_geodata_concept.md +++ b/_sources/content/Modul_2/en_qgis_geodata_concept.md @@ -240,10 +240,9 @@ Layers in a GIS. Source: [CartONG](https://cartong.pages.gitlab.cartong.org/lear ## Projections ### Introduction -:::{dropdown} Video: Why all world maps are wrong -:open: + -::: + An important issue when creating a map of a region, is that it is impossible to create a representation of a sphere on a 2D plane without distorting the map. The transformation of a 3D object onto a flat surface can be done with the help of a __projection__. Over the centuries, cartographers and mathematicians have developed a multitude of different methods to project the earth onto a flat surface. However, it is never possible to correctly represent the world on a flat surface (see the video above). @@ -270,6 +269,8 @@ figure below). Furthermore, the further away from the equator you get, the more The mercator projection is famous for distorting the size of different countries. You can check the true size in comparison to different placements on the map on [TheTrueSize.com website](https://www.thetruesize.com). A popular example is Greenland in comparison with Africa, which seem on the map to be about the same size, but in reality Africa is a lot bigger. +::: + ```{figure} /fig/en_greenland_africa.png --- diff --git a/content/GIS_AA/en_qgis_historical_impact_assessment_sudan.html b/content/GIS_AA/en_qgis_historical_impact_assessment_sudan.html index 75427abd0..c24568912 100644 --- a/content/GIS_AA/en_qgis_historical_impact_assessment_sudan.html +++ b/content/GIS_AA/en_qgis_historical_impact_assessment_sudan.html @@ -3698,7 +3698,7 @@

Step 9: Data analysis in QGIS

Visualise impact quantity data for one year on state level in QGIS#

    -

  1. Import the previously created CSV file into QGIS. Open the Data Source Manager and select the Delimited Text section. Here you can input your CSV-file and depending on the File Format you need to define Costum delimiters or you can just select CSV. Always check the Sample Data output at the bottom to see if the import is working as expected. You propably will also need to check the Record and Fields Options and specify if your first record is a header or already data. Lastly, it is important to specify the Geometry Definition, were you can just select No geometry. An example will be shown in Fig. 242.

    2. +

  2. Import the previously created CSV file into QGIS. Open the Data Source Manager and select the Delimited Text section. Here you can input your CSV-file and depending on the File Format you need to define Costum delimiters or you can just select CSV. Always check the Sample Data output at the bottom to see if the import is working as expected. You propably will also need to check the Record and Fields Options and specify if your first record is a header or already data. Lastly, it is important to specify the Geometry Definition, were you can just select No geometry. An example will be shown in Fig. 243.

Note

@@ -3707,23 +3707,23 @@

Visualise impact quantity data for one year on state level in QGIS ../../_images/en_HIA_csv_import.PNG
-

Fig. 233 Import of the CSV data#

+

Fig. 234 Import of the CSV data#

    -

  1. For this example we will use geodata that contains information about the states of Sudan. Make sure that your geodata has the admin_1_PCODE column that will be used for joining the table data with the geodata. We will use the tool Join attributes by field value. And select the corresponding columns. This is shown in Fig. 243 below.

    2. +

  2. For this example we will use geodata that contains information about the states of Sudan. Make sure that your geodata has the admin_1_PCODE column that will be used for joining the table data with the geodata. We will use the tool Join attributes by field value. And select the corresponding columns. This is shown in Fig. 244 below.

../../_images/en_HIA_join.PNG
-

Fig. 234 Join the table information onto the geodata#

+

Fig. 235 Join the table information onto the geodata#

The information can now be visualized on a spatial scale and maps can be created to transport important information. An example could be to visualize the total affected population for the year of 2020 on state level. But we can also visualize more specific impact types such as damaged schools or damaged sanitation. This is how such a map could look like.

../../_images/en_HIA_map_houses.png
-

Fig. 235 Example map#

+

Fig. 236 Example map#

@@ -3750,7 +3750,7 @@

Flood events in Sudanese states for all the recorded yearsSum flood events.

    -

  1. Now we export this excel sheet as a CSV file and import it into QGIS. We will open the Data Source Manager and select the Delimited Text section. Here we need to do the following specifications (Fig. 245).

    2. +

  2. Now we export this excel sheet as a CSV file and import it into QGIS. We will open the Data Source Manager and select the Delimited Text section. Here we need to do the following specifications (Fig. 246).

Note

@@ -3759,25 +3759,25 @@

Flood events in Sudanese states for all the recorded years ../../_images/en_HIA_import_csv_floods.png
-

Fig. 236 Import of the CSV data#

+

Fig. 237 Import of the CSV data#

    -

  1. The next step follows the same logic as step 2 in the previous example. We will use geodata that contains information about the states of Sudan and join them with the imported CSV data. We will use the Join attributes by field value tool and select the ADM1_PCODE as the table field used for the join. An example is shown in Fig. 246.

    2. +

  2. The next step follows the same logic as step 2 in the previous example. We will use geodata that contains information about the states of Sudan and join them with the imported CSV data. We will use the Join attributes by field value tool and select the ADM1_PCODE as the table field used for the join. An example is shown in Fig. 247.

../../_images/en_HIA_join_floods.png
-

Fig. 237 Join the table information onto the geodata#

+

Fig. 238 Join the table information onto the geodata#

    -

  1. Now we can visualise our results using Graduated and selecting the corresponding column of the attribute table Sum flood events. Select an appropriate color scheme and start creating your map. Your final product could look like Fig. 247.

    2. +

  2. Now we can visualise our results using Graduated and selecting the corresponding column of the attribute table Sum flood events. Select an appropriate color scheme and start creating your map. Your final product could look like Fig. 248.

../../_images/en_HIA_map_floods.png
-

Fig. 238 Example map#

+

Fig. 239 Example map#

We can expand this analysis by also including the affected population an calculate the average number of affected population per flood event on state level.

@@ -3791,21 +3791,21 @@

Flood events in Sudanese states for all the recorded yearsPop_affected. Also make sure to rename the Grand total to Sum affected pop. Export the subset as a CSV file.

    -

  1. The next steps in QGIS will follow the same logic as before. Import the data and join the table onto your output from the previous task. This will look the following Fig. 239.

    2. +

  2. The next steps in QGIS will follow the same logic as before. Import the data and join the table onto your output from the previous task. This will look the following Fig. 240.

../../_images/en_HIA_join_aff_pop.png
-

Fig. 239 Join the table information onto the geodata with the flood information.#

+

Fig. 240 Join the table information onto the geodata with the flood information.#

    -

  1. Now we will calculate the the average number of affected population per flood event on state level. To do so, we need to activate the editing mode for our geodata clicking on this symbol . In the next step we will open the Field calculator . Here we will calculate the sum of the affected population divided by the number of flood events for each state. Your calculation will look like Fig. 240.

    2. +

  2. Now we will calculate the the average number of affected population per flood event on state level. To do so, we need to activate the editing mode for our geodata clicking on this symbol . In the next step we will open the Field calculator . Here we will calculate the sum of the affected population divided by the number of flood events for each state. Your calculation will look like Fig. 241.

../../_images/en_HIA_field_calculator.png
-

Fig. 240 Calculate the average number of affected population per flood event on state level.#

+

Fig. 241 Calculate the average number of affected population per flood event on state level.#

    @@ -3818,7 +3818,7 @@

    Flood events in Sudanese states for all the recorded years ../../_images/en_HIA_map_affected_pop.png
    -

    Fig. 241 Example map#

    +

    Fig. 242 Example map#

    diff --git a/content/GIS_AA/en_qgis_historical_impact_assessment_sudan_ex1.html b/content/GIS_AA/en_qgis_historical_impact_assessment_sudan_ex1.html index 6013991dc..3daea459c 100644 --- a/content/GIS_AA/en_qgis_historical_impact_assessment_sudan_ex1.html +++ b/content/GIS_AA/en_qgis_historical_impact_assessment_sudan_ex1.html @@ -3349,7 +3349,7 @@

    Task 8: Data export using Pivot-Table in Excel ✅We also want to include the Event and Flash-floods as these types can also be associated with flooding events as a result of heavy rainfall, seasonal rainfall, etc. We also want to make sure that we rename the column containing the sum of the flooding events to Sum flood events.

      -

    1. Now we export this excel sheet as a CSV file and import it into QGIS. We will open the Data Source Manager and select the Delimited Text section. Here we need to do the following specifications (Fig. 245).

      2. +

    2. Now we export this excel sheet as a CSV file and import it into QGIS. We will open the Data Source Manager and select the Delimited Text section. Here we need to do the following specifications (Fig. 246).

    @@ -3373,7 +3373,7 @@

    Task 9: Data visualization and analysis in QGIS ../../_images/Sudan_HIA_ex_import_csv_impact.png
    -

    Fig. 242 Import of the CSV data impact quantity 2020 on state level#

    +

    Fig. 243 Import of the CSV data impact quantity 2020 on state level#

      @@ -3393,7 +3393,7 @@

      Task 9: Data visualization and analysis in QGIS ../../_images/Sudan_HIA_ex_join_table.png
      -

      Fig. 243 Join the table information onto the geodata#

      +

      Fig. 244 Join the table information onto the geodata#

        @@ -3413,36 +3413,36 @@

        Task 9: Data visualization and analysis in QGIS ../../_images/en_HIA_map_houses.png
        -

        Fig. 244 Example map of destroyed houses in Sudan 2020#

        +

        Fig. 245 Example map of destroyed houses in Sudan 2020#

        Flood events in Sudanese states for all the recorded years

        In this section we want to analyse and visualise all recorded flooding events for all the Sudanese state. With our filter for the Impact-Type we derive information for the years 2003 until 2021.

          -

        1. Now we impoer the file “Floods_Sudan_all_years” from the input folder. We will open the Data Source Manager and select the Delimited Text section. Here we need to do the following specifications (Fig. 245).

          2. +

        2. Now we impoer the file “Floods_Sudan_all_years” from the input folder. We will open the Data Source Manager and select the Delimited Text section. Here we need to do the following specifications (Fig. 246).

        ../../_images/en_HIA_import_csv_floods.png
        -

        Fig. 245 Import of the CSV data#

        +

        Fig. 246 Import of the CSV data#

          -

        1. The next step follows the same logic as step 2 in the previous example. We will use geodata that contains information about the states of Sudan and join them with the imported CSV data. We will use the Join attributes by field value tool and select the ADM1_PCODE as the table field used for the join. An example is shown in Fig. 246.

          2. +

        2. The next step follows the same logic as step 2 in the previous example. We will use geodata that contains information about the states of Sudan and join them with the imported CSV data. We will use the Join attributes by field value tool and select the ADM1_PCODE as the table field used for the join. An example is shown in Fig. 247.

        ../../_images/en_HIA_join_floods.png
        -

        Fig. 246 Join the table information onto the geodata#

        +

        Fig. 247 Join the table information onto the geodata#

          -

        1. Now we can visualise our results using Graduated and selecting the corresponding column of the attribute table Sum flood events. Select an appropriate color scheme and start creating your map. Your final product could look like Fig. 247.

          2. +

        2. Now we can visualise our results using Graduated and selecting the corresponding column of the attribute table Sum flood events. Select an appropriate color scheme and start creating your map. Your final product could look like Fig. 248.

        ../../_images/en_HIA_map_floods.png
        -

        Fig. 247 Example map#

        +

        Fig. 248 Example map#

        diff --git a/content/Mobile_Data_collection/en_SMT.html b/content/Mobile_Data_collection/en_SMT.html index 3de46e059..40119e14b 100644 --- a/content/Mobile_Data_collection/en_SMT.html +++ b/content/Mobile_Data_collection/en_SMT.html @@ -562,7 +562,7 @@

        What is the Sketch Map Tool?../../_images/SketchMap_Logo_Top.jpg
        -

        Fig. 248 Sketch Map Tool Logo#

        +

        Fig. 249 Sketch Map Tool Logo#

        The Sketch Map Tool simplifies participatory mapping, by facilitating the creation and digitisation of paper-based maps, the so-called Sketch Maps. This low-tech solution enables the offline collection of local knowledge and perceptions with pen and paper maps. Every SketchMap contains a basemap with OpenStreetMap data or satellite imagery, which provides a scale and orientation to the user. Upon uploading pictures of marked maps, the tool automatically digitizes and georeferences the markings to download and integrate into Geographic Information Systems. The Sketch Map Tool combines widely used, analogue mapping with digital analysis, fosters community involvement and the usability of gained results.

        @@ -601,7 +601,7 @@

        Introduction in the Workflow Sketch Map Tool ../../_images/SMT_workflow_Satelite.png
        -

        Fig. 249 Sketch Map Tool workflow#

        +

        Fig. 250 Sketch Map Tool workflow#

    @@ -612,7 +612,7 @@

    The Sketch Map Tool and its use in the EVCA ../../_images/IMG_2178.JPG
    -

    Fig. 250 Usage of Sketch Map Tool in the context of the Enhanced Vulnerability and Capacity Assessment (EVCA) in Colombia#

    +

    Fig. 251 Usage of Sketch Map Tool in the context of the Enhanced Vulnerability and Capacity Assessment (EVCA) in Colombia#

    For more information on the EVCA:

    diff --git a/content/Modul_2/en_data_sources.html b/content/Modul_2/en_data_sources.html index 999904bef..b752836ea 100644 --- a/content/Modul_2/en_data_sources.html +++ b/content/Modul_2/en_data_sources.html @@ -901,7 +901,7 @@

    QuickOSM plugin ../../_images/key_value_quickosm.png
    -

    Fig. 40 Choosing key and value in QuickOSM.#

    +

    Fig. 41 Choosing key and value in QuickOSM.#

      @@ -916,7 +916,7 @@

      QuickOSM plugin ../../_images/quickosm_usage.png
      -

      Fig. 41 Running the QuickOSM plugin.#

      +

      Fig. 42 Running the QuickOSM plugin.#

        @@ -954,7 +954,7 @@

        HOT Export Tool ../../_images/hot_export.png
        -

        Fig. 42 The HOT Export Tool.#

        +

        Fig. 43 The HOT Export Tool.#

          @@ -978,7 +978,7 @@

          HOT Export Tool ../../_images/hot_export_example.png
          -

          Fig. 43 An Example for the HOT Export Tool.#

          +

          Fig. 44 An Example for the HOT Export Tool.#

            @@ -988,7 +988,7 @@

            HOT Export Tool ../../_images/hot_export_running.png
            -

            Fig. 44 The HOT Export Tool is running.#

            +

            Fig. 45 The HOT Export Tool is running.#

              @@ -998,7 +998,7 @@

              HOT Export Tool ../../_images/hot_export_done.png
              -

              Fig. 45 Downloading data from HOT Export Tool.#

              +

              Fig. 46 Downloading data from HOT Export Tool.#

              diff --git a/content/Modul_2/en_qgis_attribute_table.html b/content/Modul_2/en_qgis_attribute_table.html index b1b8f75d8..aea230529 100644 --- a/content/Modul_2/en_qgis_attribute_table.html +++ b/content/Modul_2/en_qgis_attribute_table.html @@ -569,7 +569,7 @@

              Attribute Table ../../_images/en_vector_data_overview.drawio.png
              -

              Fig. 32 Vector Data overview. Source: HeiGIT#

              +

              Fig. 33 Vector Data overview. Source: HeiGIT#

              @@ -584,7 +584,7 @@

              Opening the attribute table ../../_images/en_attributetable_right_click.png
              -

              Fig. 33 Screenshot of Opening the Attribute Table with right click#

              +

              Fig. 34 Screenshot of Opening the Attribute Table with right click#

              @@ -595,7 +595,7 @@

              Opening the attribute table ../../_images/en_attributetable_top_right.png
              -

              Fig. 34 Screenshot of Opening the Attribute Table#

              +

              Fig. 35 Screenshot of Opening the Attribute Table#

              @@ -754,7 +754,7 @@

              Sort the attribute table ../../_images/en_ascending.png
              -

              Fig. 35 Attribute table sorted ascendingly.#

              +

              Fig. 36 Attribute table sorted ascendingly.#

              @@ -766,7 +766,7 @@

              Sort the attribute table ../../_images/en_descending.png
              -

              Fig. 36 Attribute table sorted descendingly.#

              +

              Fig. 37 Attribute table sorted descendingly.#

@@ -822,13 +822,13 @@

Zoom to selected area ../../_images/en_zoom_to_selection_1.png
-

Fig. 37 Screenshot of how to zoom to Selection on the top.#

+

Fig. 38 Screenshot of how to zoom to Selection on the top.#

../../_images/en_zoom_to_selection_2.png
-

Fig. 38 Screenshot of how to zoom to Selection by clicking right.#

+

Fig. 39 Screenshot of how to zoom to Selection by clicking right.#

@@ -848,7 +848,7 @@

Save only selected features as a new file ../../_images/en_save_selection.png
-

Fig. 39 Screenshot of how to save only selected features.#

+

Fig. 40 Screenshot of how to save only selected features.#

diff --git a/content/Modul_2/en_qgis_basic_data_processing.html b/content/Modul_2/en_qgis_basic_data_processing.html index 202742337..145901a33 100644 --- a/content/Modul_2/en_qgis_basic_data_processing.html +++ b/content/Modul_2/en_qgis_basic_data_processing.html @@ -617,7 +617,7 @@

Standard folder structure ../../_images/Standard_project_folder_structure.drawio.svg
-

Fig. 29 Standard folder structure. Source: HeiGIT#

+

Fig. 30 Standard folder structure. Source: HeiGIT#

@@ -717,7 +717,7 @@

Open Delimited Text Layer ../../_images/en_import_delimeted_text.png
-

Fig. 30 Import delimited text.#

+

Fig. 31 Import delimited text.#

    @@ -737,7 +737,7 @@

    Open Delimited Text Layer ../../_images/en_delimited_text_fileformat.png
    -

    Fig. 31 Import delimited text - file format.#

    +

    Fig. 32 Import delimited text - file format.#

      diff --git a/content/Modul_2/en_qgis_geodata_concept.html b/content/Modul_2/en_qgis_geodata_concept.html index f743c7b17..3d40d9f73 100644 --- a/content/Modul_2/en_qgis_geodata_concept.html +++ b/content/Modul_2/en_qgis_geodata_concept.html @@ -811,16 +811,8 @@

      The layer concept#

      Introduction#

      -
      - -Video: Why all world maps are wrong
      -
      -
      -
      -
      -
      -

      An important issue when creating a map of a region, is that it is impossible to create a representation of a sphere +

      An important issue when creating a map of a region, is that it is impossible to create a representation of a sphere on a 2D plane without distorting the map. The transformation of a 3D object onto a flat surface can be done with the help of a projection. Over the centuries, cartographers and mathematicians have developed a multitude of different methods to project the earth onto a flat surface. However, it is never possible to correctly represent the world on a flat surface (see the video above). Every projection distorts either the length between two points, the angles between two lines (directions), or the size of an area. A projection can only correctly represent one of these three dimensions. This means, that depending on the projection method, your world map will not represent the size, angles, or distances correctly.

      @@ -839,29 +831,25 @@

      Introduction
      The mercator projection is famous for distorting the size of different countries. You can check 
 the true size in comparison to different placements on the map on [TheTrueSize.com website](https://www.thetruesize.com).
 A popular example is Greenland in comparison with Africa, which seem on the map to be about the same size, but in reality Africa is a lot bigger.
+
      +

+
+../../_images/en_greenland_africa.png +
+

Fig. 24 Comparison Greenland - Africa. Source: The True Size of#

+
+
+

+In the dropdown below, you can look at the size distortion of mercator yourself.
 
-```{figure} /fig/en_greenland_africa.png
----
-width: 600px
-align: center
-name: Comparison Greenland - Africa
----
-Comparison Greenland - Africa. Source: [The True Size of](https://www.thetruesize.com/#?borders=1~!MTYwODM1MTk.MzkyNDUyNg*MjY5NjM4Mzg(MTA1MjgyOTE~!CONTIGUOUS_US*MTAwMjQwNzU.MjUwMjM1MTc(MTc1)MQ~!IN*NTI2NDA1MQ.Nzg2MzQyMQ)MA~!CN*OTkyMTY5Nw.NzMxNDcwNQ(MjI1)Mg)
-```
+:::{dropdown} TheTrueSize.com - compare the effects of different projections
+
+%%html
+<iframe src="https://www.thetruesize.com/#?borders=1~!MTUxNjUyNzI.MzM1OTE0MQ*MzI2NDc5MjY(NjgwODA4Mg~!GL*OTQ3NTExNQ.MjkxMDYzMzM)Mw" width="750" height="500"></iframe>
-

In the dropdown below, you can look at the size distortion of mercator yourself.

-
- -TheTrueSize.com - compare the effects of different projections
-
-
-
-
- -
-
+

How to choose an appropriate projected coordinate system#

In GIS, we project the earth onto a flat coordinate system (hence the name coordinate reference system or CRS). @@ -883,21 +871,21 @@

How to choose an appropriate projected coordinate system ../../_images/world_mercator_tissots.png
-

Fig. 24 The Mercator Projection (EPSG:54004)#

+

Fig. 25 The Mercator Projection (EPSG:54004)#

Notice how the shape of the circle stays the same. Out of this, we can conclude that the angles stay the same. However, the circles get bigger the further away they are from the equator, and the distance between these circles change the further they they get from the equator. Therefore, we can conclude that the distances and sizes are being distorted with the mercator projection. The strength of the Mercator projection is that it conserves the angles between to lines. We can see this because the circles stay perfectly circular the further they are from the equator.

../../_images/WGS_84_tissots.png
-

Fig. 25 The World Geodetic System 1984 (EPSG:4326)#

+

Fig. 26 The World Geodetic System 1984 (EPSG:4326)#

The WGS 84 is a CRS which consists of an ellipsoid, that resembles the shape of the earth closely. Instead of metrical units of measurements, it uses angular degrees (latitude and longitude). The shape of the Tissot circles is undistorted near the equator, but becomes elongated on the East-West axis the further it gets away from the equator. Unlike the Mercator projection, there is no distortion on the in the North-South direction. As the circles become distorted, we can deduce that the this CRS distorts the angles.

../../_images/World_equidistant_cylindrical_tissots.png
-

Fig. 26 The World Equidistant Cylindrical Projection (EPSG:54002)#

+

Fig. 27 The World Equidistant Cylindrical Projection (EPSG:54002)#

The World Equidistant cylindrical CRS is equidistant (not distorting the length) along any meridian (cricles of longitude; North to South), and along the two standard parallels. The shape, scale and area distort the further they are away from the standard parallels.

@@ -949,7 +937,7 @@

Metric and Geographic Coordinate Reference Systems ../../_images/Problem_distance_geographic_coords.png
-

Fig. 27 A geographic representation of the globe. The distance between the meridians converge towards the north and south pole.#

+

Fig. 28 A geographic representation of the globe. The distance between the meridians converge towards the north and south pole.#

@@ -958,7 +946,7 @@

Local and Global CRS ../../_images/en_local_crs.png
-

Fig. 28 Local and global coordinate reference systems (CRS). Source: British Red Cross (BRC)#

+

Fig. 29 Local and global coordinate reference systems (CRS). Source: British Red Cross (BRC)#

As you can see, smaller regions look skewed and distorted in a global CRS diff --git a/content/Modul_3/en_qgis_data_classification.html b/content/Modul_3/en_qgis_data_classification.html index fa4595025..9d07f6814 100644 --- a/content/Modul_3/en_qgis_data_classification.html +++ b/content/Modul_3/en_qgis_data_classification.html @@ -566,7 +566,7 @@

Geodata Classification ../../_images/classification_basic.drawio.png
-

Fig. 51 Basic classification. Source:#

+

Fig. 52 Basic classification. Source:#

@@ -588,7 +588,7 @@

Single symbol classification ../../_images/Single_symbol_classify.png
-

Fig. 52 Adjust the style of a layer.#

+

Fig. 53 Adjust the style of a layer.#

@@ -634,7 +634,7 @@

Categorised classification ../../_images/Categorized_district_map_SierraLeone.png
-

Fig. 53 Categorised classification.#

+

Fig. 54 Categorised classification.#

@@ -679,7 +679,7 @@

Graduated classification statistic one-o-one ../../_images/Histogramm_example.drawio.svg
-

Fig. 54 Histogramm of population data. Source:#

+

Fig. 55 Histogramm of population data. Source:#

However, if we want to show which districts have a higher population than others on a map, we need to classify the districts.

@@ -688,7 +688,7 @@

Graduated classification statistic one-o-one ../../_images/classification_method_map.drawio.svg
-

Fig. 55 Different classifications. Source:#

+

Fig. 56 Different classifications. Source:#

@@ -748,7 +748,7 @@

How to Graduated classification in QGIS ../../_images/Graduated_histogram.png
-

Fig. 56 Graduated classification. Source:#

+

Fig. 57 Graduated classification. Source:#

    @@ -762,7 +762,7 @@

    How to Graduated classification in QGIS ../../_images/classification_graduated_basic.png
    -

    Fig. 57 Graduated classification in QGIS.#

    +

    Fig. 58 Graduated classification in QGIS.#

    diff --git a/content/Modul_3/en_qgis_digitalisation.html b/content/Modul_3/en_qgis_digitalisation.html index fa1745db8..22d6f7805 100644 --- a/content/Modul_3/en_qgis_digitalisation.html +++ b/content/Modul_3/en_qgis_digitalisation.html @@ -580,7 +580,7 @@

    Digitisation ../../_images/Digitizsation_concept.drawio.svg
    -

    Fig. 46 Digitisation with GIS Concept. Source:#

    +

    Fig. 47 Digitisation with GIS Concept. Source:#

    @@ -616,7 +616,7 @@

    Digitisation toolbars ../../_images/Activate_digitizing_toolbox.png
    -

    Fig. 47 Digitisation Toolbar.#

    +

    Fig. 48 Digitisation Toolbar.#

@@ -809,7 +809,7 @@

Data Creation ../../_images/New_GeoPackage_Layer.png
-

Fig. 48 Digitisation Toolbar.#

+

Fig. 49 Digitisation Toolbar.#

@@ -833,7 +833,7 @@

Creating point data ../../_images/point_creation.png
-

Fig. 49 Point creation.#

+

Fig. 50 Point creation.#

@@ -943,7 +943,7 @@

Digitisation Errors in QGIS ../../_images/Digitization_Errors.PNG
-

Fig. 50 Digitising Errors in QGIS. Source: SpatialPost.#

+

Fig. 51 Digitising Errors in QGIS. Source: SpatialPost.#

diff --git a/content/Modul_4/en_qgis_map_design_2.html b/content/Modul_4/en_qgis_map_design_2.html index a4854bd1d..13e9131ec 100644 --- a/content/Modul_4/en_qgis_map_design_2.html +++ b/content/Modul_4/en_qgis_map_design_2.html @@ -576,7 +576,7 @@

Map Design: The Print layout ../../_images/en_30.30.2_create_print_layout.png
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Fig. 79 Create a new Print Layout#

+

Fig. 80 Create a new Print Layout#

@@ -601,7 +601,7 @@

Understanding the Print Layout Composer ../../_images/en_30.30.2_understanding_the_print_layout_composer.png
-

Fig. 80 The interface of the Print Layout Composer#

+

Fig. 81 The interface of the Print Layout Composer#

    @@ -633,7 +633,7 @@

    Adding a new map ../../_images/en_30.30.2_adding_a_map.png
    -

    Fig. 81 Adding a new map to the Print Layout#

    +

    Fig. 82 Adding a new map to the Print Layout#

    @@ -661,7 +661,7 @@

    Adding a title or a text box ../../_images/en_30.30.2_print_layout_add_text.png
    -

    Fig. 82 Adding text to the print layout#

    +

    Fig. 83 Adding text to the print layout#

    @@ -705,7 +705,7 @@

    Adding a legend ../../_images/en_30.30.2_print_layout_add_legend.png
    -

    Fig. 83 Adding a legend to the print layout#

    +

    Fig. 84 Adding a legend to the print layout#

    In the Item Properties panel, if you keep the Auto update option checked, new layers added to your project will automatically be added to the legend but you cannot control them individually (rename if necessary, reorder ot remove items).
    @@ -739,7 +739,7 @@

    Adding a scale bar ../../_images/en_30.30.2_print_layout_scale.png
    -

    Fig. 84 Make sure that the scale is at a round number#

    +

    Fig. 85 Make sure that the scale is at a round number#

    To add a scale bar, you can use the Add scale bar-button on the left toolbar. In the Item Properties panel, customize the following functions

    @@ -754,7 +754,7 @@

    Adding a scale bar ../../_images/en_30.30.2_print_layout_add_scale_bar.png
    -

    Fig. 85 Add and customise the scale bar#

    +

    Fig. 86 Add and customise the scale bar#

    @@ -791,19 +791,19 @@

    Adding an overview map ../../_images/en_30.30.2_print_layout_overview_map_preparations.png
    -

    Fig. 86 An overview map should show important landmarks and borders so the reader is able to locate the region shown on the map without having specific knowledge of the region.#

    +

    Fig. 87 An overview map should show important landmarks and borders so the reader is able to locate the region shown on the map without having specific knowledge of the region.#

    ../../_images/en_30.30.2_print_layout_add_overview_map.png
    -

    Fig. 87 Add an overview map and lock the layer#

    +

    Fig. 88 Add an overview map and lock the layer#

    ../../_images/en_30.30.2_print_layout_add_map_extent_overview_map.png
    -

    Fig. 88 Add a the extent of the main map to your overview map (the red rectangle in the bottom right corner)#

    +

    Fig. 89 Add a the extent of the main map to your overview map (the red rectangle in the bottom right corner)#

    @@ -894,7 +894,7 @@

    The Atlas function (automatic map generation) ../../_images/en_atlas_toolbar.png
    -

    Fig. 89 Atlas Toolbar#

    +

    Fig. 90 Atlas Toolbar#

    If you can’t see the Atlas Tools, you must first activate the Atlas Toolbar under View > Toolbars > Atlas Toolbar.

    diff --git a/content/Modul_4/en_qgis_map_design_I.html b/content/Modul_4/en_qgis_map_design_I.html index a5d5d0108..823038d34 100644 --- a/content/Modul_4/en_qgis_map_design_I.html +++ b/content/Modul_4/en_qgis_map_design_I.html @@ -605,14 +605,14 @@

    Visualisation of Geodata: Symbology and Colours ../../_images/en_30.30.2_topographic_map_examples.png
    -

    Fig. 58 Examples for topographic maps#

    +

    Fig. 59 Examples for topographic maps#

    Thematic maps display the distribution of specific data or statistically processed information, such as population size, disease incidence, flooding risk, etc. The representation of elements on thematic maps is decided according to the rules of graphic semiology.

    ../../_images/en_30.30.2_thematic_maps_examples.png
    -

    Fig. 59 Examples for thematic maps#

    +

    Fig. 60 Examples for thematic maps#

    These two maps use design elements differently. Topographic maps will use symbols and colours out of convention and readability, whereas in designing thematic maps, the symbols and colours you use depend on the context and the information you want to convey.

    @@ -629,14 +629,14 @@

    Visual Variables ../../_images/en_30.30.2_graphic_semiology_signs.png
    -

    Fig. 60 You can use different graphic signs depending on the type of information you want to display.#

    +

    Fig. 61 You can use different graphic signs depending on the type of information you want to display.#

    Visual variables are the graphical means for visually transcribing information. The visual variables are shape, size, hue, value, texture, and orientation. You can adjust these variables to appropriately represent the data at your disposal. They allows for the expression of relationship of difference, order, association, or quantity between each element, helping to display different information.

    ../../_images/en_visual_variables.png
    -

    Fig. 61 Visual variables according to Bertin (1967)#

    +

    Fig. 62 Visual variables according to Bertin (1967)#

    @@ -662,7 +662,7 @@

    Styling Panel ../../_images/en_30.30.2_styling_panel.png
    -

    Fig. 62 Styling panel in QGIS 3.30.2#

    +

    Fig. 63 Styling panel in QGIS 3.30.2#

    For each layer in QGIS, there is a styling panel where you can change the symbology, colour and label for the features in that layer. There are two ways to open the layer styling options in QGIS:

    @@ -700,21 +700,21 @@

    Colours ../../_images/en_colour_gradients_qualities.png
    -

    Fig. 63 Different types of colouring schemes#

    +

    Fig. 64 Different types of colouring schemes#

    When choosing colour gradients, a clear gradient from lighter to darker colours is usually the most appropriate, as the gradation is easily distinguishable and translates well into black and white. In the figure below, examples A and B are not good colour schemes, as it is difficult to make out the gradation and it does not translate well into black and white. You can achieve a clear sequence by grading the saturation of the colour gradient.

    ../../_images/de_colour_gradients_saturation.png
    -

    Fig. 64 Examples for different colour gradients translated into black and white. Pay attention to the saturation gradient under each example. Source: Stauffer, Reto & Mayr, Georg & Dabernig, Markus & Zeileis, Achim. (2014). Somewhere Over the Rainbow: How to Make Effective Use of Colours in Meteorological Visualizations. Bulletin of the American Meteorological Society. 96. 140710055335002. 10.1175/BAMS-D-13-00155.1.#

    +

    Fig. 65 Examples for different colour gradients translated into black and white. Pay attention to the saturation gradient under each example. Source: Stauffer, Reto & Mayr, Georg & Dabernig, Markus & Zeileis, Achim. (2014). Somewhere Over the Rainbow: How to Make Effective Use of Colours in Meteorological Visualizations. Bulletin of the American Meteorological Society. 96. 140710055335002. 10.1175/BAMS-D-13-00155.1.#

    Colour gradients can also encompass multiple hues:

    ../../_images/colour_gradients_hues.png
    -

    Fig. 65 Single hue gradient on the left; Multiple hue gradient on the right.#

    +

    Fig. 66 Single hue gradient on the left; Multiple hue gradient on the right.#

    @@ -727,7 +727,7 @@

    Colourblindness ../../_images/Colour_Blindness.png
    -

    Fig. 66 Different Colour schemes for the Colour Vision Impaired; Source: Jenny, Bernhard, and Nathaniel Vaughn Kelso. (2007). Color Design for the Color Vision Impaired. Cartographic Perspectives, no. 58 (September 1, 2007): 61-67. https://doi.org/10.14714/CP58.270#

    +

    Fig. 67 Different Colour schemes for the Colour Vision Impaired; Source: Jenny, Bernhard, and Nathaniel Vaughn Kelso. (2007). Color Design for the Color Vision Impaired. Cartographic Perspectives, no. 58 (September 1, 2007): 61-67. https://doi.org/10.14714/CP58.270#

@@ -738,7 +738,7 @@

Symbology for Vector Data ../../_images/en_symbolization_vector_data.png
-

Fig. 67 Symbolization for vector data; Source: White, T. (2017). Symbolization and the Visual Variables. *The Geographic Information Science & Technology Body of Knowledge (2nd Quarter 2017 Edition), John P. Wilson (ed.). DOI: 10.2222/gistbok/2017.2.3#

+

Fig. 68 Symbolization for vector data; Source: White, T. (2017). Symbolization and the Visual Variables. *The Geographic Information Science & Technology Body of Knowledge (2nd Quarter 2017 Edition), John P. Wilson (ed.). DOI: 10.2222/gistbok/2017.2.3#

@@ -821,13 +821,13 @@

Single Labels ../../_images/labels_single_labels_example_nga_adm1.png
-

Fig. 68 Single labels for each administrative region (adm1) in Nigeria. The reader is able to assign each label to the respective administrative entity.#

+

Fig. 69 Single labels for each administrative region (adm1) in Nigeria. The reader is able to assign each label to the respective administrative entity.#

../../_images/en_30.30.2_assigning_value_to_labels.png
-

Fig. 69 Assigning the correct attribute value in the labeling options. QGIS needs to know which attribute (column) of the attribute table should be displayed as a label. In this case, we want the name of the administrative region (ADM1_EN) to be displayed.#

+

Fig. 70 Assigning the correct attribute value in the labeling options. QGIS needs to know which attribute (column) of the attribute table should be displayed as a label. In this case, we want the name of the administrative region (ADM1_EN) to be displayed.#

@@ -844,7 +844,7 @@

Adding Single Labels to a Layer ../../_images/en_30.30.2_setting_up_labels.png
-

Fig. 70 Setting up labels in QGIS 30.30.2#

+

Fig. 71 Setting up labels in QGIS 30.30.2#

-

Fig. 71 Single Labels was selected to display the names of the settlements (red dots). A map with so much text information is unreadable and the information can hardly be understood.#

+

Fig. 72 Single Labels was selected to display the names of the settlements (red dots). A map with so much text information is unreadable and the information can hardly be understood.#

@@ -866,7 +866,7 @@

Rule-based Labelling ../../_images/rule-based_labeling_example_settlements_nga.png
-

Fig. 72 Rule-based labeling allows you to filter datasets. This way, you can display the labels only for selected features without altering the dataset.#

+

Fig. 73 Rule-based labeling allows you to filter datasets. This way, you can display the labels only for selected features without altering the dataset.#

The rules, or filters, are based on an expression. You can use the Expression string builder to the right of the Filter option in the label panel.

@@ -896,7 +896,7 @@

Adding Rule-based Labels to a Layer ../../_images/good_labels_example.png
-

Fig. 73 A good example of label placement and font. Pay attention to the text colours and orientation. Every label can easily be attributed to the correct cartographic feature. (Source: Axis Maps)#

+

Fig. 74 A good example of label placement and font. Pay attention to the text colours and orientation. Every label can easily be attributed to the correct cartographic feature. (Source: Axis Maps)#

@@ -911,7 +911,7 @@

Adding Rule-based Labels to a Layer ../../_images/labels_numerical_values_bad_example.png
-

Fig. 74 Numerical Labels#

+

Fig. 75 Numerical Labels#

@@ -921,7 +921,7 @@

Adding Rule-based Labels to a Layer ../../_images/labels_graduated_symbology_example.png
-

Fig. 75 Graduated Symbology#

+

Fig. 76 Graduated Symbology#

@@ -935,7 +935,7 @@

Adding Rule-based Labels to a Layer ../../_images/label_text_buffer_example.png
-

Fig. 76 A label without a text buffer (left) and a label with a white text buffer (right)#

+

Fig. 77 A label without a text buffer (left) and a label with a white text buffer (right)#

@@ -965,7 +965,7 @@

Assigning a colour gradient to raster data ../../_images/en_30.30.2_raster_data_colour_gradient.png
-

Fig. 77 Colour Ramp Selector#

+

Fig. 78 Colour Ramp Selector#

In the colour ramp selector, you can adjust each colour step. On the bottom, you can see a plot for the Hue, Saturation, Lightness and Opacity. The last three in particular are useful to understand how your colour ramp will appear. Gradients from light to dark are easier to read: Check if the plot for the Lightness has a more or less linear plot.

@@ -1009,7 +1009,7 @@

Saving or exporting styling settings ../../_images/en_30.30.2_save_layer_style_window.png
-

Fig. 78 Save Layer styling window in QGIS 30.30.2.#

+

Fig. 79 Save Layer styling window in QGIS 30.30.2.#

When working with similar data (e.g. building types or flooding risk), it is useful to have template styles, that can be quickly loaded into your QGIS-project or saved in your Styling Template library.

diff --git a/content/Modul_4/en_qgis_map_examples.html b/content/Modul_4/en_qgis_map_examples.html index d6dd98a86..ffa01f3e1 100644 --- a/content/Modul_4/en_qgis_map_examples.html +++ b/content/Modul_4/en_qgis_map_examples.html @@ -594,7 +594,7 @@

Map Example 1: Flood-affected areas and roads in the Somali Region, Ethiopia
../../_images/ET_Somali_Humanitarian_Access_Flooded_Areas_11152023_A4.png
-

Fig. 90 Flood affected areas and roads in the Somali Region, Ethiopia (Source: OCHA)#

+

Fig. 91 Flood affected areas and roads in the Somali Region, Ethiopia (Source: OCHA)#

@@ -629,7 +629,7 @@

Map Example 2: Flooding Risk in the Ouham Region, Central African Republic ../../_images/REACH_CAF_Susceptibilite_inondations_CF32_Juillet2023_A3_FR.png
-

Fig. 91 Flooding risk in the Ouham Region, Central African Republic (Source: REACH)#

+

Fig. 92 Flooding risk in the Ouham Region, Central African Republic (Source: REACH)#

@@ -683,7 +683,7 @@

Key elements of a map ../../_images/en_good_map_composition_example.png
-

Fig. 92 Elements of good map composition#

+

Fig. 93 Elements of good map composition#

@@ -707,7 +707,7 @@

Key elements of a map ../../_images/en_legend_good_practice.png
-

Fig. 93 Example of a well organized legend#

+

Fig. 94 Example of a well organized legend#

The scale bar is essential to a map since it gives the correspondence between a distance measured on the map and the distance in the real world. There are two types of scales:

@@ -718,7 +718,7 @@

Key elements of a map ../../_images/example_scale_bar.png
-

Fig. 94 Scale bar examples#

+

Fig. 95 Scale bar examples#

diff --git a/content/Modul_5/en_qgis_non_spatial_tools.html b/content/Modul_5/en_qgis_non_spatial_tools.html index ad6585119..e4351fb96 100644 --- a/content/Modul_5/en_qgis_non_spatial_tools.html +++ b/content/Modul_5/en_qgis_non_spatial_tools.html @@ -579,7 +579,7 @@

Introduction: ../../_images/en_attribute_table_large.PNG
-

Fig. 108 Screenshot of an attribute table for QGIS version 3.28.4#

+

Fig. 109 Screenshot of an attribute table for QGIS version 3.28.4#

@@ -640,7 +640,7 @@

Calculate field ../../_images/en_field_calculator_red_boxes.png
-

Fig. 109 Screenshot of the Field calculator#

+

Fig. 110 Screenshot of the Field calculator#

The most important groups and their respective functionality that are provided with the field calculator are listed below:

@@ -873,7 +873,7 @@

Query Builder ../../_images/en_query_builder_comment.png
-

Fig. 110 Screenshot of the Query Builder#

+

Fig. 111 Screenshot of the Query Builder#

    @@ -912,7 +912,7 @@

    Non-spatial joins ../../_images/en_join_attributes_by_field_values.PNG
    -

    Fig. 111 Screenshot of the Join attributes by field value tool#

    +

    Fig. 112 Screenshot of the Join attributes by field value tool#

    diff --git a/content/Modul_5/en_qgis_spatial_tools.html b/content/Modul_5/en_qgis_spatial_tools.html index 2972973d9..c8845c518 100644 --- a/content/Modul_5/en_qgis_spatial_tools.html +++ b/content/Modul_5/en_qgis_spatial_tools.html @@ -585,7 +585,7 @@

    Clip# ../../_images/en_clip_sudan.PNG
    -

    Fig. 95 Screenshot of the Clip tool with the input data#

    +

    Fig. 96 Screenshot of the Clip tool with the input data#

    Information on road infrastructure for humanitarian aid operations is of great importance and can be easily retrieved from open-source data sources like OpenStreetMap. However, this information is often included in extensive datasets that contain a significant amount of irrelevant details for specific operations or it covers a lot more area than is necessary for the operation. To make working with this data more efficient, it is common practice to clip the data to the area of interest. In addition to clipping, data can often be filtered, as described in the first part of Module 5.

    @@ -605,7 +605,7 @@

    Exercise: Clipping a roads layer to administrative boundaries ../../_images/en_screenshot_hot_export_tool.PNG
    -

    Fig. 96 Screenshot of the HOT Export tool used to download your OSM data#

    +

    Fig. 97 Screenshot of the HOT Export tool used to download your OSM data#

      @@ -632,7 +632,7 @@

      Exercise: Clipping a roads layer to administrative boundaries ../../_images/en_gdal_clipping_tools.PNG
      -

      Fig. 97 The GDAL tools Clip vector by extent and Clip vector by mask layer#

      +

      Fig. 98 The GDAL tools Clip vector by extent and Clip vector by mask layer#

      @@ -651,7 +651,7 @@

      Exercise: Clipping a roads layer to administrative boundaries ../../_images/en_clip_vector_by_extent.PNG
      -

      Fig. 98 Screenshot of the tool Clip vector by extent#

      +

      Fig. 99 Screenshot of the tool Clip vector by extent#

      @@ -666,7 +666,7 @@

      Exercise: Clipping a roads layer to administrative boundaries ../../_images/en_clip_vector_by_mask_layer.PNG
      -

      Fig. 99 Screenshot of the tool Clip vector by mask layer#

      +

      Fig. 100 Screenshot of the tool Clip vector by mask layer#

    @@ -679,7 +679,7 @@

    Buffer ../../_images/en_buffer_point_line_polygon.png
    -

    Fig. 100 Different kinds of buffer zones
    (Adapted after QGIS Documentation, Version 3.28)    #

    +

    Fig. 101 Different kinds of buffer zones
    (Adapted after QGIS Documentation, Version 3.28)    #

    There are several variations in buffering. The buffer distance or buffer size can vary according to the numerical values provided. The numerical values have to be defined in map units according to the Coordinate Reference System (CRS) used with the data.

    @@ -730,7 +730,7 @@

    Dissolve ../../_images/en_buffer_dissolve.png
    -

    Fig. 101 Buffer zones with dissolved (left) and with intact boundaries (right) showing overlapping areas
    (Source: QGIS Documentation, Version 3.28)    #

    +

    Fig. 102 Buffer zones with dissolved (left) and with intact boundaries (right) showing overlapping areas
    (Source: QGIS Documentation, Version 3.28)    #

    @@ -784,7 +784,7 @@

    Spatial joins ../../_images/en_select_by_location.png
    -

    Fig. 102 Looking for spatial relations between layers
    (Source: QGIS Documentation, Version 3.28)    #

    +

    Fig. 103 Looking for spatial relations between layers
    (Source: QGIS Documentation, Version 3.28)    #

    QGIS provides a range of tools that allow users to delve into spatial relationships and leverage them to enhance their datasets.

    @@ -797,7 +797,7 @@

    Spatial joins ../../_images/en_join_attributes_by_location.PNG
    -

    Fig. 103 Screenshot of the tool Join attributes by location#

    +

    Fig. 104 Screenshot of the tool Join attributes by location#

@@ -808,7 +808,7 @@

Spatial joins ../../_images/en_join_attributes_by_location_summary.PNG
-

Fig. 104 Screenshot of the tool Join attributes by location (summary)#

+

Fig. 105 Screenshot of the tool Join attributes by location (summary)#

@@ -821,7 +821,7 @@

Spatial joins ../../_images/en_join_attributes_by_nearest.PNG
-

Fig. 105 Screenshot of the tool Join attributes by nearest#

+

Fig. 106 Screenshot of the tool Join attributes by nearest#

@@ -867,7 +867,7 @@

Select by location ../../_images/en_ex2_select_by_location_health.PNG
-

Fig. 106 Screenshot of the Select by location tool#

+

Fig. 107 Screenshot of the Select by location tool#

@@ -880,7 +880,7 @@

Centroids ../../_images/en_centroids_screenshot.png
-

Fig. 107 The black points represent the centroids of the features from the input layer.#

+

Fig. 108 The black points represent the centroids of the features from the input layer.#

diff --git a/content/Modul_6/en_qgis_data_analysis_theorie.html b/content/Modul_6/en_qgis_data_analysis_theorie.html index 656116e55..daa183a3d 100644 --- a/content/Modul_6/en_qgis_data_analysis_theorie.html +++ b/content/Modul_6/en_qgis_data_analysis_theorie.html @@ -595,7 +595,7 @@

Spatial analysis ../../_images/multiple_layer_data_analysis.png
-

Fig. 112 Spatial analysis means using multiple layers to gain new insights#

+

Fig. 113 Spatial analysis means using multiple layers to gain new insights#