::::{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` ::: :::: ## Exercise 2: Disaster impact in different regions of Senegal ## Characteristics of the exercise ::::{grid} 2 :::{grid-item-card} ### Aim of the exercise Become familiar with different types of non-spatial analysis and geoprocessing tools. Understand the process of discovering relationships and connections between features in spatial data. #### Type of trainings exercise: - This exercise can be used in online and presence training. - It can be done as a follow-along exercise or individually as a self-study. ::: :::{grid-item-card} #### Focus group (GIS-Knowledge Level) #### These skills are relevant for ::: :::: ::::{grid} 2 :::{grid-item-card} #### Estimated time demand for the exercise. ::: :::{grid-item-card} ## Relevant Wiki Articles * [Geodata Import in QGIS](../Wiki/en_qgis_import_geodata_wiki.md) * [Projections](../Wiki/en_qgis_projections_wiki.md) * [Spatial Queries](../Wiki/en_qgis_spatial_queries_wiki.md) * [Geoprocessing](../Wiki/en_qgis_geoprocessing_wiki.md) * [Categorized classification](/content/Wiki/en_qgis_categorized_wiki.md) ::: :::: ## Instructions for the trainers :::{dropdown} __Trainers Corner__ ### Prepare the training - Take the time to familiarise yourself with the exercise and the provided material. - Prepare a white-board. It can be either a physical whiteboard, a flip-chart, or a digital whiteboard (e.g. Miro board) where the participants can add their findings and questions. - Before starting the exercise, make sure everybody has installed QGIS and has downloaded __and unzipped__ the data folder. - Check out [How to do trainings?](../Trainers_corner/en_how_to_training.md#how-to-do-trainings) for some general tips on facilitating trainings. ### Conduct the training __Introduction:__ - Introduce the idea and aim of the exercise. - Provide the download link and make sure everybody has unzipped the folder before beginning the tasks. __Follow-along:__ - Show and explain each step yourself at least twice and slow enough so everybody can see what you are doing, and follow along in their own QGIS-project. - Make sure that everybody is following along and doing the steps themselves by periodically asking if anybody needs help or if everybody is still following. - Be open and patient to every question or problem that might come up. Your participants are essentially multitasking by paying attention to your instructions and orienting themselves in their own QGIS-project. __Wrap up:__ - Leave time for any issues or questions concerning the tasks at the end of the exercise. - Leave some time for open questions. ::: ### Availbale Data :::{card} :link: https://nexus.heigit.org/repository/gis-training-resource-center/Modul_5/Modul_5_Exercise1_Disaster_effects_in_different_regions_Senegal/Modul5_Exercise1_Disaster_effects_in_different_regions_Senegal.zip __Download all datasets [here](https://nexus.heigit.org/repository/gis-training-resource-center/Modul_5/Modul_5_Exercise1_Disaster_effects_in_different_regions_Senegal/Modul5_Exercise1_Disaster_effects_in_different_regions_Senegal.zip) and save the folder on your computer and unzip the file.__ ::: - `sen_admbnda_adm1_1m_gov_ocha_20190426.shp`: [Senegal boundary data (Admin level 1)](https://data.humdata.org/dataset/senegal-administrative-boundaries) - `DI_Stat924.xls`: [Senegal Desinventar Sendai data](https://www.desinventar.net/DesInventar/profiletab.jsp?countrycode=sen) showing effects of disasters in Senegalese regions - `sen_admpop_adm1_2020.csv`: Senegal administrative level 1 (région) 2019 [projection population statistics](https://data.humdata.org/dataset/senegal-population-statistics) :::{Hint} All files still have their original names. However, feel free to modify their names if necessary to identify them more easily. ::: ### Task Create an overview of the effects of disasters in different regions of Senegal. Use non-spatial joins, table functions and different symbology. :::{Hint} The projected coordinate system for Senegal is `EPSG:32628 WGS 84 / UTM zone 28N` ::: 1. Load the Senegal administrative boundary layer (`sen_admbnda_adm1_1m_gov_ocha_20190426.shp`), as well as population per subnational unit (`sen_admpop_adm1_2020.csv`) and the Desinventar Sendai data of Senegal (`DI_Stat924.xls`) into QGIS. 2. Make sure to reproject the dataset with the administrative boundaries into UTM zone 28N. See the [wiki entry on Projections](../Wiki/en_qgis_projections_wiki.md) for further information. 3. Conduct non-spatial joins based on regions listed in two datasets and the PCODE listed in these same sets. See the [Wiki entry on Non-spatial joins](../Wiki/en_qgis_non_spatial_joins_wiki.md) for further information. :::{figure} ../../../fig/en_ex1_AT_admin_pop_sen.png --- width: 100% name: attributes_all --- Screenshot of the different attribute tables with the corresponding columns highlighted ::: 4. First, add the total population of each administrative area to the shapefiles. Select the correct column that should be added (Hint: search for the column named `Total`). 5. Then, add the number of directly and indirectly affected people. Also select the correct columns that should be added (Hint: search for the column names `Directly affected` and `Indirectly Affected`). :::::{tab-set} ::::{tab-item} Screenshot for task 4 :::{figure} ../../../fig/en_ex1_Join_field.png --- width: 80% name: join_field --- Screenshot of the tool Join Attributes by Field Value for the total population. ::: :::: ::::{tab-item} Screenshot for task 5 :::{figure} ../../../fig/en_ex1_Join_field_2.PNG --- width: 80% name: join_field --- Screenshot of the tool Join Attributes by Field Value for the directly and indirectly affected people. ::: :::: ::::: 6. Use the table functions to calculate the area of each region in square kilometres and the density of the population. See the Wiki entry on [Table functions](../Wiki/en_qgis_table_functions_wiki.md) for further information. - Create a new column/field named `"area_sqkm"` using the field calculator. Ensure decimal numbers are used as the field type. For the calculation use the expression: `$area / (1000 * 1000)` - Create another column/field named `"pop_per_sqkm"` with decimal numbers as field type. Use the expression: `"Total" / "area_sqkm"` for the calculation. You can access the field calculator through your attribute table by activating ![](../../../fig/mActionToggleEditing.png) `Toggle editing mode` and clicking on this symbol ![](../../../fig/mActionCalculateField.png) to `Open field calculator`. :::::{tab-set} ::::{tab-item} Screenshot calculation `"area_sqkm"` :::{figure} ../../../fig/en_ex1_area_sqkm.png --- width: 80% name: field_calculator --- Screenshot of the area calculation using the field calculator. ::: :::: ::::{tab-item} Screenshot calculation `"pop_per_sqkm"` :::{figure} ../../../fig/en_ex1_pop_per_sqkm.png --- width: 80% name: field_calculator_2 --- Screenshot of the population per square km calculation using the field calculator. ::: :::: ::::: 7. Now, we need to rename the `Indirectly Affected` and `Directly Affected` columns so they don't contain spaces. This ensures that the field calculator works properly. For this task we will use the tool `Rename field`. :::{figure} ../../../fig/en_ex1_Rename_field.PNG --- width: 80% name: rename_field --- Screenshot of the Rename field tool. ::: 5. Let us now determine the proportion of the population directly or indirectly affected in relation to the total population per region. - Use the field calculator. Use the expression: `"Indirectly Affected" / ("Total"/100)` - Use the field calculator. Use the expression: `"Directly Affected" / ("Total"/100)` :::::{tab-set} ::::{tab-item} Screenshot indirectly affected :::{figure} ../../../fig/en_ex1_per_indirect_affected.PNG --- width: 80% name: per_indirect_affected --- Calculation of the proportion of the indirectly affected population relative to the total population within each region. ::: :::: ::::{tab-item} Screenshot directly affected :::{figure} ../../../fig/en_ex1_per_direct_affected.PNG --- width: 80% name: per_direct_affected --- Calculation of the proportion of the directly affected population relative to the total population within each region. ::: :::: ::::: 6. Select a colour scheme using the `Symbology` to visualise the share of people directly affected in the different regions (Hint: `Categorized`). - Play around with different modes to find a useful colour/categorisation scheme for the visualisation. - Which regions are more and which are less directly affected? Are there any data gaps? 7. Export the map as a png (Hint: `Project, Import/Export, Export map to Image`). 8. Repeat the previous steps, but this time visualise the indirectly affected people in each region (Hint: `Categorized`, column `Indirectly affected`). 9. What differences can be observed between the regions directly affected and those indirectly affected?