# QGIS Trigger Workflow for Somalia <a id="qgis-trigger-workflow-for-somalia"></a>

:::{attention}

Due to the changes in the availability of FEWSNET data, we are using IPC food insecurity classification instead of the FEWSNET classification. We are currently updating the documentation for the updated trigger model. 

:::

The QGIS workflow presented in this article was developed in the framework of the Forecast-based-Action (FbF) Project of the Somalia Red Cresent Society (SRCS), the German Red Cross (GRC) and the Heidelberg Institute for Geoinformation Technology (HeiGIT).

The workflow consists of 15 steps of which 9 are automated in the form of a QGIS Model. In this article, we explain how all 15 steps can be done manually. In practice one needs to do only 6 steps manually, the rest is done by the QGSI Model.
The chapter Workflow Automated explains the process and how it is intended in practice. The chapter Workflow Manually is to understand what happens inside of the QGIS Model.

## Background <a id="background"></a>

Setting triggers is one of the cornerstones of the Forecast-based Financing system. For a National Society to have access to automatically released funding for their early actions, their Early Action Protocol needs to clearly define where and when funds will be allocated, and assistance will be provided. In FbF, this is decided according to specific threshold values, so-called triggers, based on weather and climate forecasts, which are defined for each region (see [FbF Manual](https://manual.forecast-based-financing.org/en/chapter/set-the-trigger/)).

For the development of the Somaliland-Somalia Drought Trigger mechanism various datasources were thoroughly analysed.
Finally, the main parameters chosen for the trigger based on the historical impact assessment are the twelve month Standard Precipitation Index (SPI12) and the IPC acute food insecurity classification. The exact data used are the documented and forecasted SPI12 (source: ICPAC) and the forecasted IPC classification (8 month forecast, source: FEWSNET), that is used to calculate a population weighted index of food insecurity. The trigger thresholds for both components were optimised towards the most favourable proportion of hit rate and false alarm rate. The emerging thresholds were <-1 for the SPI12 and >=0,7 for the IPC based index. The triggering is done on district level and per district just one trigger initiation per year is possible.

## Trigger Statement <a id="trigger-statement"></a>

When ICPAC issues a SPI-12 forecast of less than -1 for a district AND the current IPC food insecurity projection reaches at least 0.7 in its 
derived population weighted index in the same district, then we will act in this district. We expect the lead-time to be 90 days.


## Trigger Input Data <a id="trigger-input-data"></a>

For the trigger mechanism to work properly we currently use different datasets: data that we assume to be fixed in the near term, and variable data which describe the datasets that will be checked for triggering on a monthly base. 

### Fixed Data <a id="fixed-data"></a>

By fixed data we mean datasets that are needed for the trigger to work, that will most probably not change in the near term. In the long term these datasets can be adapted easily.

| Dataset| Source | Description |
| ----- | --- | --- |
| Administrative boundaries | [HDX](https://data.humdata.org/dataset/cod-ab-som?) | The administrative boundaries on level 0-2 for Somalia and Somaliland can be accessed via HDX. For this trigger mechanism we provide the administrative boundaries on level 2 (district level) as a shapefile.  |
| Population Counts | [Worldpop](https://hub.worldpop.org/doi/10.5258/SOTON/WP00534) | The worldpop dataset in `.geotif` raster format provides population estimates per hectar for the year 2020. |

<!--OUTDATED: admin boundaries (keep in for visualisation?)
"We have added the population number for each district derived from Worldpop."-->


### Monitoring Data <a id="monitoring-data"></a>

:::{attention}

The dataset used for monitoring the food insecurity phase has been updated to the classification and forecast published by the [Integrated Food Security Phase Classification](https://www.ipcinfo.org) as of March 2025. Prior to this, the food insecurity forecast published by FEWSNET had been used. 

:::

The drought trigger mechanism is based on two variable monitoring datasets updated monthly: The SPI-12 forecast produced by ICPAC and the Food Insecurity projection produced by FEWSNET. The SPI-12 is used to capture hazard forecasts while the Food Insecurity Projection captures the dynamic vulnerability. 
In this way upcoming drought events (SPI) that most probably will lead to food insecurity (IPC) will be captured.

| Dataset| Source | Description |
| ----- | --- | --- |
| SPI-12 forecast| [ICPAC](https://www.icpac.net/) | meteorological drought indicator to monitor precipitation anomalies over 12-month accumulation periods|
| IPC Projections | [IPC](https://www.ipcinfo.org/ipc-country-analysis/details-map/en/c/1159510/?iso3=SOM) | five-phase scale providing common standards for classifying the severity of acute or anticipated acute food insecurity. |



### What is the Standarized Precipitation Index (SPI-12)? <a id="what-is-the-standarized-precipitation-index-spi-12"></a>

The Standardized Precipitation Index (SPI) is a widely used index to characterize meteorological drought.
The Standardized Precipitation Index (SPI-12) compares the total rainfall received at a particular location during the last 12 months with the long-term rainfall mean (42 years) for the same period of time at that location.


### What is IPC Food Security Projection Data? <a id="what-is-ipc-food-security-projection-data"></a>
 
The IPC is a commonly accepted measure and classification to describe the current and anticipated severity of acute food insecurity. 
The classification is based on a convergence of available data and evidence, including indicators related to food consumption, livelihoods, malnutrition and mortality. Food Insecurity is one of the prioritized impacts of droughts in Somalia which is why it is also used for the triggering mechanism, in a population-weighted index. 

| Colour | Phase | Descriptions |
| ----- | --- | --- |
| ![](../../../fig/IPC_Class_1.drawio.svg)| 1. Minimal   | Households are able to meet essential food and non-food needs without engaging in atypical and unsustainable strategies to access food and income.   |
| ![](../../../fig/IPC_Class_2.drawio.svg)| 2. Stressed   | Households have minimally adequate food consumption but are unable to afford some essential non-food expenditures without engaging in stress-coping strategies.  |
| ![](../../../fig/IPC_Class_3.drawio.svg)| 3. Crisis   | Households either have food consumption gaps that are reflected by high or above-usual acute malnutrition __OR__ are marginally able to meet minimum food needs but only by depleting essential livelihood assets or through crisis-coping strategies.  |
| ![](../../../fig/IPC_Class_4.drawio.svg)| 4. Emergency | Households either have large food consumption gaps which are reflected in very high acute malnutrition and excess mortality; __OR__ are able to mitigate large food consumption gaps but only by employing emergency livelihood strategies and asset liquidation.|
| ![](../../../fig/IPC_Class_5.drawio.svg)| 5. Famine | Households have an extreme lack of food and/or other basic needs even after full employment of coping strategies. Starvation, death, destitution, and extremely critical acute malnutrition levels are evident. (For Famine Classification, area needs to have extreme critical levels of acute malnutrition and mortality.)  |


#### IPC Food Security Projection: <a id="ipc-food-security-projection"></a>


Three times a year (February, June, and October) FEWSNET estimates most likely IPC classes for the upcoming 8 month (near-term and mid-term projection), available from 2019-current. The near-term projection is called ML1 and is a projection for the upcoming 4 month, the mid-term projection is called ML2 and projects the IPC classes for the 4 subsequent months. For the triggering ML1 (near-term) as well as ML2 (mid-term) projections will be considered. 

:::{admonition} UPDATE: IPC Classification Data
:type: attention

The food security classification projections are generally published twice a year and usually includes a projection for a period of three months and a current phase, which also spans three months. Due to the unavailability of FEWSNET projections, the trigger model is using the [IPC data](www.ipcinfo.org/ipc-country-analysis/details-map/en/c/1156097/?iso3=SOM)

:::

Outlook updates are produced almost every month and are also taken into account.


#### IPC-Population Weighted Index <a id="ipc-population-weighted-index"></a>

To better operationalise the IPC data a simple population-weighted index was developed. Relative population numbers are weighted based on the respective IPC class they falling, in order to give the amount of people in a certain IPC class the importance instead of the IPC class only.
Furthermore, population located in a higher IPC class is more important than population located in a lower class. The index is calculated as follows:

$ IPC\ Index =  Weights \times \frac{District\ Pop\ per\ IPC\ Phase}{Total\ District\ Pop}$

Where the weights are defined as:

| IPC Phase | Weight |
| ----- | --- |
|IPC 1  |0  |
|IPC 2  |0  |
|IPC 3  |1  |
|IPC 4  |3  |
|IPC 5  |6  |


The IPC Index represents low-population districts equal to high-population districts. No under-representation of high food insecurity of small districts occurs.


# Trigger Workflow Automated <a id="trigger-workflow-automated"></a>

As explained in the beginning of this [chapter](https://giscience.github.io/gis-training-resource-center/english/content/en/GIS_AA/en_qgis_drought_trigger_somalia.html#qgis-trigger-workflow-for-somalia), the 9 main steps of the developed trigger workflow are done automatically by a QGIS model. In the previous chapters you have learned the purpose and needed tools of each step and how to perform them manually. In this chapter it is explained how to run the automated model.

The [QGIS Model Designer](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_automatisation_wiki.html#the-qgis-model-designer) is a visual tool that allows users to create and edit a workflow with all tools available in QGIS that can be used repeatedly in a simple and time-efficient manner. It provides a graphical interface to build workflows by connecting geoprocessing tools and algorithms. The user can define inputs, outputs, and the flow of data between different processing steps.

<!--The Model designer chapter is completely unfinished. Also, what are the previous chapters? the modules?-->

:::{admonition} Troubleshooting the model
:class: note

When updating the monitoring, make sure you compare the new input layers with the previous input layers.
It can happen that the data structure from FEWSNET or ICPAC changes. For example, the attribute columns are called differently, or the values for the classes change. In these cases, the model can break and output error messages. 

To fix these issues, take a look at the subsection on [Troubleshooting the model](https://giscience.github.io/gis-training-resource-center/english/content/en/GIS_AA/en_qgis_drought_trigger_somalia.html#troubleshooting-the-model).

:::

## Step 1: Setting up folder structure <a id="step-1-setting-up-folder-structure"></a>


```{figure} ../../../fig/Drought_EAP_Worklow_Step_1_1.png
---
width: 1000px
name: 
align: center
---
```
__Purpose:__ In this step we set up the correct folder structure to make the analysis easier and to ensure consistent results. 

__Tool:__ No special tools or programs are needed

``````{list-table}
:header-rows: 1
:widths: 10 25

* - Instruction
  - Folder Structure
* - 1. Open the Folder “FbF_Drought_Monitoring_Trigger"
    2. Open the subfolder "Monitoring"
    3. Copy the Template folder “TEMPLATE_Year_Month” and change the name to the current year and month. The result could be the folder "2022_05"
    
  -
    ```{figure} ../../../fig/Folder_structure_FbF_Drought_Monitoring_Trigger.drawio.svg
    ---
    width: 450px
    name: 
    align: center
    ---
    ```
``````

The Video below shows the process for setting up the folder for december 2023.


```{dropdown} Video: Setting up folder structure 
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_Trigger_folder_setup.mp4"></video>
```

## Step 2: Download of the forecast data <a id="step-2-download-of-the-forecast-data"></a>

```{figure} ../../../fig/Drought_EAP_Worklow_Step_2_2.png
---
width: 1000px
name: SOM_drought_EAP_step_2
align: center
---
```


__Tool:__ FileZilla and Internet Browser

The current plans provide that ICPAC will monthly provide the SPI-12 forecast whereas the IPC data will be pulled from the FEWSNET website. FEWS NET publishes IPC data on its website. 
The main data publications plus the updates of the IPC data amount to the publication of new data almost monthly.

### SPI-12 Data <a id="spi-12-data"></a>


ICPAC will provide the SPI-12 forecasts on their FTP (File Transfer Protocol). There are different ways to access the FTP-Server. We recommend to install and once set up [FileZilla](https://filezilla-project.org/download.php?platform=win64). This will make your work easily repeatable on a monthly basis.

1. Download Filezilla [here](https://filezilla-project.org/download.php?platform=win64).
2. Install the `.exe` file you have downloaded 
3. Open FileZilla


4. Establish a connection to the FTP Server by inserting the credentials you have been passed (Host, Username and Password) and clicking `Quickconnect`.


In FileZilla you have four windows. On the left hand side you will see the folder on your computer in the upper window. By clicking on a folder, the documents in the folder will be shown in the lower left window.
On the right hand side, you will see in the upper window the FTP data folder and by clicking on it, the data will be shown in the lower right window.

In order to pass the data from the FTP Server to your own machine you can simply drag and drop the folder or data from the right hand side windows (FTP-Server) to the left hand side windows (your Computer). To do so, firstly navigate to your folder where you need the latest SPI-12 data to be located `.../FbF_Drought_Monitoring_Trigger/Monitoring/Year_Month_template/SPI_12`. Then drag and drop the latest SPI-12 into the folder.



```{figure} ../../../fig/FileZilla.PNG
---
height: 400px
name: FileZilla Interface
align: center
---
```

### IPC Data <a id="ipc-data"></a>

The IPC Projection data is provided and regularly updated on the [IPC Website](https://www.ipcinfo.org/ipc-country-analysis/details-map/en/c/1159510/?iso3=SOM). 
To navigate to the latest IPC Projection data on Somalia, navigate to `Latest Analyses` in the top bar > `IPC Analyses` > `Acute Food Insecurity Classification`. Here you look for the latest analysis for Somalia. 

<!---```{Warning}
The FEWSNET pages change often!
```

```{admonition} Updates to FEWSNET
:class: warning

As of December 2024, the FEWSNET Website does not offer the IPC data for ML1 and ML2 as two distinct shapefiles contained in a zip-file. Instead, you can download the GeoJSON-file, which contains a polygon layer with both the ML1 and ML2 polygons. The model and the documentation has been updated to work with the GeoJSON-file.

```
-->

1. Go to the [IPC website](https://www.ipcinfo.org)
2. In the top bar, navigate to `Latest Analyses` > `IPC Analyses` > `Acute Food Insecurity Classification`.
3. On the new website, select Somalia as a country and select the newest dataset.
4. On this website, you will see both a map of the current and the projected IPC phase classifications, as well as some metadata. On the right side of the map, click on the button `Download GIS format`. This will download the analysis in a GeoJSON format, containing polygons for the administrative boundaries and IPC phases, as well as points for the IPC phase classification for IDP camps. 


```{figure} ../../../fig/en_IPCinfo_website_dl_som.png
---
height: 350px
name: IPCinfo_download_projections
align: center
---
```

4. Download the __GeoJSON file__. The filename is composed of the country name, the analysis type, and Year and month of publication. E.g., `Somalia-Acute Food Insecurity January 2025.geoJSON`

:::{note}

In some cases, your operating system (Windows) misidentifies the GeoJSON-file as a `.customization`-file. This does not change anything and can be loaded into your QGIS-project.

:::

5. Copy the GeoJSON-file into the input monitoring folder.
  * Example path: `/FbF_Drought_Monitoring_Trigger/Input_monitoring/Year_Month_template/Somalia-Acute Food Insecurity January 2025.geoJSON`


<!---
::::::{dropdown} Download workflow for shapefiles (if available)

4. Download the one with the __ZIP__ Data
5. When you have downloaded the data, right-click on the file and click on `Extract all` -> `Extract`
6. Open the extracted folder and copy the ML1 data in the IPC_ML1 folder you have created in step 1. 
  * The filename is composed of "SO" for Somalia, year and month of the report month e.g `SO_202308_ML1.shp`
  Example path: `.../FbF_Drought_Monitoring_Trigger/Monitoring/Year_Month_template/IPC_ML1`
7. Copy the ML2 data into IPC_ML2 folder you have created in step 1.
  * The filename is composed of "SO" for Somalia, year and month of the report month e.g `SO_202308_ML2.shp`
  Example path: `.../FbF_Drought_Monitoring_Trigger/Monitoring/Year_Month_template/IPC_ML2`
```{Warning}
Make sure to not use the ML1_IDP data which comes in the .zip folder as well!
```

::::{Warning}
Remember that you need to copy over all components that the respective [shapefile](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_geodata_types_wiki.html#vector-data) is composed of. Most probably it has 5 components: .cpg, .dbf, .prj, .shp, and .shx.

```{figure} ../../../fig/IPC_zip.PNG
---
height: 300px
name: Content of .zip file downloaded containing ML1 and ML2 IPC projections
align: center
---
```

::::

:::::
--->

<!---
```{tip}
On the [main FEWSNET page](https://fews.net/) you can also sign up for information on latest updates via email. For this option scroll down to the end of the page and click on `Sign up for Emails`. You will then get the option to choose updates only for Somalia.

```{figure} ../../../fig/IPC_Newsletter.png
---
height: 60px
name: FEWSNET Newsletter
align: center
---
```
--->

## Step 3: Loading data into QGIS <a id="step-3-loading-data-into-qgis"></a>

```{figure} ../../../fig/Drought_EAP_Worklow_Step_3_1.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__ In this step, all the data needed will be loaded into QGIS.

__Tool:__ No specific tools are needed, only QGIS.

1. Open QGIS and create a [new project](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_projects_folder_structure_wiki.html#step-by-step-setting-up-a-new-qgis-project-from-scratch) by clicking on `Project` -> `New`
2. Once the project is created save the project in the folder you created in Step 1 (e.g. 2022_05). To do that click on `Project` -> `Save as` and navigate to the folder. Give the project the same name as the folder you created (e.g. 2022_05). Then click `Save`
3. Load all input data in QGIS by [drag and drop](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_import_geodata_wiki.html#open-raster-data-via-drag-and-drop). Click on `Project` -> `Save` 
  * From the input monitoring folder you created in step 1:
    * IPC Phase Classification
    * SPI-12
  * From the `Fixed_data` folder:
    * district_pop_som
    * Regions
    * risk_assessment.gpkg
    * WorldPop_som.tif

__Result:__ QGIS project with all necessary data ready to be analysed. 

This video shows how to setup the QGIS project for April 2022 and how to import all data into the project.

```{dropdown} Video: Loading data into QGIS
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_Trigger_step_3.mp4"></video>
```

## Step 4: Load the model in the QGIS Model Designer <a id="step-4-load-the-model-in-the-qgis-model-designer"></a>

```{figure} ../../../fig/Drought_EAP_Worklow_Step_4_1_automated_model.png
---
width: 1000px
name: 
align: center
---
```


1. Open the tool under `Processing` -> `Graphical Modeler`
2. In the upper panel click `Model` -> `Open Model` and navigate to your folder "FbF_Drought_Monitoring_Trigger", mark the "Triggermodel_Somalia.model3" (or the updated model: "IPC_Som_drought_revision_2.1.model3") file an click on `Open`. The model will open and you will see yellow, white and green boxes.

```{dropdown} Video: Open Model
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/load_model.mp4"></video>
```

```{figure} ../../../fig/SOM_model_designer_2.1.png
---
width: 700 px
name: Triggermodel_Somalia_3
align: center
---
```

| Box | Significance | Description |
| ----- | --- | --- |
|Yellow| Model Input |Definition of the input data for the model the model will perform on|
|White| Algorithms | Algorithms or Tools are specific geoprocessing steps that perform specific tasks, such as clipping, reprojecting or buffering. |
|Green| Model Output| The results created by the model (Output layers) are automatically added to your layers panel in your QGIS project interface|


## Step 5: Run the model <a id="step-5-run-the-model"></a>

```{figure} ../../../fig/Drought_EAP_Worklow_Step_5_1_automated_model.png
---
width: 1000px
name: 
align: center
---
```

__Model Input & Output__

```{Attention}  
In the dropdown list, only layers that are currently loaded in your QGIS Project will be displayed.
```

For each of these mandatory inputs, you click on the dropdown arrow and choose the respective file.

1. In the upper panel click on `Model` -> `Run Model`. A window will open where you need to define the model input and output.
2. The model needs the following 3 inputs:
    1. `Somalia-Acute Food Insecurity January 2025`: IPC Projection
    3. `SPI12` (SPI12 forecast): SPI-12 raster data
    4. `Worldpop` (Population Raster data): Worldpop raster data
3. Further down, you have to specify where to save the output: 
    1. `Trigger_activation`: Click on the three points ![](../../../fig/Three_points.png)-> `Save to File` and navigate to `Results`folder in the folder you created in step 1 (Year_month). Give the output the name: 
    ```md
    Trigger_activation
    ```

    2. `Indices`: Click on the three points ![](../../../fig/Three_points.png)-> `Save to File` and navigate to `Results`folder in the folder you created in step 1 (Year_month). Give the output the name: 
    ```md
    Indices
    ```

    3. `IPC_Phase_C`:Click on the three points ![](../../../fig/Three_points.png)-> `Save to File` and navigate to `Results`folder in the folder you created in step 1 (Year_month). Give the output the name: 
    ```md
    IPC_Phase_C
    ```

    4. `IPC_Phase_P`:Click on the three points ![](../../../fig/Three_points.png)-> `Save to File` and navigate to `Results`folder in the folder you created in step 1 (Year_month). Give the output the name: 
    ```md
    IPC_Phase_P
    ```

4. Click `Run`. Your results layer will appear in the main QGIS window. You can close the graphical modeller window.

```{dropdown} Video: Input and output Model
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/model_input_output.mp4"></video>
```

```{figure} ../../../fig/SRCS_Model_input.png
---
width: 500px
name: 
align: center
---
```

<!---
::::{dropdown} Workflow for the old model (with shapefiles)

```{figure} ../../../fig/Model_Designer.PNG
---
width: 700px
name: Triggermodel_Somalia_1
align: center
---
```

2. The model needs these 5 inputs:
    1. `IPC_Projection_ML1`: ML 1 data
    2. `IPC_Projection_ML2`: ML 2 data
    3. `Pop_per_district`: district_pop_sum
    4. `SPI12` (SPI12 forecast): SPI-12 data
    5. `Worldpop` (Population Raster data): Worldpop data
3. Further down, you have to specify where to save the output: 
    1. `Trigger_activation`: Click on the three points ![](../../../fig/Three_points.png)-> `Save to File` and navigate to `Results`folder in the folder you created in step 1 (Year_month). Give the output the name: 
    ```md
    Trigger_activation
    ```

    2. `ML2_ML1_Indices_joined`: Click on the three points ![](../../../fig/Three_points.png)-> `Save to File` and navigate to `Results`folder in the folder you created in step 1 (Year_month). Give the output the name: 
    ```md
    ML2_ML1_Indices_joined
    ```

    3. `SPI12_mean_IPC_Indices_joined`:Click on the three points ![](../../../fig/Three_points.png)-> `Save to File` and navigate to `Results`folder in the folder you created in step 1 (Year_month). Give the output the name: 
    ```md
    SPI12_mean_IPC_Indices_joined
    ```
4. Click `Run`. Your results layer will appear in the main QGIS window. You can close the graphical modeller window.

```{dropdown} Video: Input and output Model
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/model_input_output.mp4"></video>
```

```{figure} ../../../fig/SRCS_Model_input.png
---
width: 500px
name: 
align: center
---
```

::::
-->

## Step 6: Visualisation of results <a id="step-6-visualisation-of-results"></a>

```{figure} ../../../fig/Drought_EAP_Worklow_Step_14_1.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__ Definition of how features are represented visually on the map.

__Tool:__ [Symbology tab](https://giscience.github.io/gis-training-resource-center/english/content/en/Module_4/en_qgis_map_design_I.html#symbology-for-vector-data)

__Trigger Activation__

1. Right click on the “Trigger_activation” layer -> `Properties` -> `Symbology`
2. In the down left corner click on `Style` -> `Load Style`
3. In the new window click on the three points ![](../../../fig/Three_points.png). Navigate to the “FbF_Drought_Monitoring_Trigger/layer_styles” folder and select the file __“Style_Trigger_Activation.qml”__.
4. Click `Open`. Then click on `Load Style`
5. Back in the “Layer Properties” Window click `Apply` and `OK`

```{dropdown} Info: Trigger Activation Layer
You will now see districts where no trigger is activated in green and districts with trigger activation in pink.

The “Style_Trigger_Activation.qml” style layer is configured to show the district names only where the trigger is actually activated. If there is no trigger activation you can activate the admin 1 boundary layer for better map orientation (see __Administrative 2 Boundaries__ below)

```{figure} ../../../fig/Map_yes_trigger.PNG
---
width: 1000px
name: 
align: center
---
```

__Risk Assessment__


7. Right click on the "risk_assessment_districts" layer -> `Properties` -> `Symbology`
8. In the down left corner click on `Style` -> `Load Style`
9. In the new window click on the three points ![](../../../fig/Three_points.png). Navigate to the “FbF_Drought_Monitoring_Trigger/layer_styles” folder and select the file __“somalia_risk_assessment_style.qml”__ style layer.
10. Move the "risk_assessment_district" layer __below__ "Trigger_Activation" layer ([Layer Concept](https://giscience.github.io/gis-training-resource-center/english/content/en/Module_2/en_qgis_geodata_concept.html?highlight=layer#layer-concept)).
11. Back in the “Layer Properties” Window click `Apply` and `OK`


```{dropdown} Info: Risk Assessment Layer
For the creation of an __Intervention Map__ we will have to add the risk assessment data and the respective style file.
For this first of all load from "FbF_Drought_Monitoring_Trigger/Fixed_data/Risk_Assessment" the file "risk_assessment_districts.gpkg". This file is the output of the conducted risk assessment and contains a risk value for each district of Somaliland and Somalia.  In order to visualize it 
```

__Administrative 2 Boundaries (Regions)__

12. Right click on the "Som_Admbnda_Adm1_UNDP" (Regiond) layer -> `Properties` -> `Symbology`
13. In the down left corner click on `Style` -> `Load Style`
14. In the new window click on the three points ![](../../../fig/Three_points.png). Navigate to the “FbF_Drought_Monitoring_Trigger/layer_styles” folder and select the file __“somalia_risk_assessment_style.qml”__.
15. Click `Open`. Then click on `Load Style` 
16. Back in the “Layer Properties” Window click `Apply` and `OK`
17. Add a the OpenStreetMap basemap by clicking on `Layer` -> `Add Layer` -> `Add XYZ layer...` -> Select the OpenStreetMap. Click `Add`. ([Wiki basemap](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_basemaps_wiki.html?highlight=osm#basemaps))
18. Place the OpenStreetMap basemap on the bottom.
19. Delet all layers exept:
    * Trigger_activation
    * risk_assessment_districts
    * Som_Admbnda_Adm1_UNDP
    * OpenStreetMap

```{dropdown} Video: Visualisation of results
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/Trigger_model_style.mp4"></video>
```

``````{list-table}
:header-rows: 1
:widths: 20 20

* - Intervention Map __without__ Trigger activation
  - Intervention Map __with__ Trigger activation
* - 
    ```{figure} ../../../fig/Map_no_trigger.PNG
    ---
    width: 1000px
    name: 
    align: center
    ---
    ```
    
  -
    ```{figure} ../../../fig/Map_yes_trigger.PNG
    ---
    width: 450px
    name: 
    align: center
    ---
    ```
``````

```{Attention}
Remember the [layer concept](https://giscience.github.io/gis-training-resource-center/english/content/en/Module_2/en_qgis_geodata_concept.html?highlight=layer#layer-concept) and make sure the basemap layer is at the bottom of your layers panel.
```



## Step 7: Making the Print Map <a id="step-7-making-the-print-map"></a>

```{figure} ../../../fig/Drought_EAP_Worklow_Step_15_1.png
---
width: 1000px
name: 
align: center
---
```
__Purpose:__ Viualisation of the map features in a printable map layout

__Tool:__  [Print Layout](https://giscience.github.io/gis-training-resource-center/english/content/en/Module_4/en_qgis_map_design_2.html?highlight=print+layout#print-layout)


1. If not done before, delet all layers expect __Trigger_activation__, __risk_assessment_districts__ and __OpenStreetMap__
2. Open a new print layout by clicking on `Project` -> `New Print Layout` -> enter the name of your current Project e.g "2022_04".
3. Go the the __FbF_Drought_Monitoring_Trigger__` folder and drag and drop the file `Trigger_activation_Intervention_map.qpt` in the print layout
4. Change the date to the current date by clicking on "Further map info…" in the items panel. Click on the `Item Properties` tab and scroll down. Here you can change the date in the `Main Properties` field.
5. Adjust the Lgend by clicking on the legend in the  `Item Properties` tab and scroll down until you see the `Legend items` field. If it is not there check if you have to open the dropdown. Make sure `Auto update` is not checked.
    * Remove all itemes in the legend be clicking on the item and then on the red minus icon below.
    * Add __Trigger_activation__ and __risk_assessment_districts__ to the legend by clicking on the green plus and click on the layer and click `ok`
 

```{dropdown} Video: Making print map
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_Trigger_print_map.mp4"></video>
```

```{Attention}
Make sure you edit the Map Information on the template, e.g. current date. Also make sure to check the legend items: Remove unnecessary items and eventually change the names to meaning descriptions.
```


In order to easily visualize the output of the trigger analysis we provide you with a 
[map template](https://giscience.github.io/gis-training-resource-center/english/content/en/Module_4/en_qgis_map_design_2.html#map-templates) that can be used as a base for your visualization. You can find the template in the following directory: ".../FbF_Drought_Monitoring_Trigger/maps_somalia_template_risk_assessment.qpt".

You can also adapt the template to your needs and preferences. You can find help [here](https://giscience.github.io/gis-training-resource-center/english/content/en/Module_4/en_qgis_map_design_2.html#print-layout).

```{Attention}
Make sure you edit the Map Information on the template, e.g. current date. Also make sure to check the legend items: Remove unnecessary items and eventually change the names to meaning descriptions.
```

## Step 8: Exporting the Map <a id="step-8-exporting-the-map"></a>


```{figure} ../../../fig/Drought_EAP_Worklow_Step_16_1.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__ Export the designed and finalized map layout in order tp print it as a pdf or format of your choice.


__Tool:__ [Print Layout](https://giscience.github.io/gis-training-resource-center/english/content/en/Module_4/en_qgis_map_design_2.html?highlight=print+layout#print-layout)

When you have finished the design of you map you can export it as pdf or image file in different datafromats.

__Export as Image__

1. In the print layout click on `Layer` -> `Export as Image`
2. Chose the __Result__ folder in the folder you have created in step 1. Give the file the name of the project e.g 2022_04
3.  Click on `Save`
4. The window "Image Export Options" will appear. Click `Save`
Now the image can be found in the result folder in the folder you created in Step 1


__Export as PDF__

1. In the print layout click on `Layer` -> `Export as PDF`
2. Chose the __Result__ folder in the folder you have created in step 1. Give the file the name of the project e.g 2022_04
3.  Click on `Save`
4. The window "PDF Export Options" will appear.  For the best results, select the `lossless` image compression.
5. Click `Save`
Now the image can be found in the result folder in the folder you created in Step 1

```{dropdown} Video: Export image and PDF
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_trigger_export_image_pdf.mp4"></video>
```


```{figure} ../../../fig/map_output_example2.png
---
width: 1000px
name: 
align: center
---
```

## Troubleshooting the Model <a id="troubleshooting-the-model"></a>

In some cases, for example when the data structure of the input layers change, the model can break. To make sure that the model functions correctly, follow these troubleshooting steps. In most cases, the problems are happening at the input stage (yellow boxes).

1. When monitoring the trigger, take a closer look at the new data downloaded from FEWSNET or ICPAC. Are there any changes in the names of the columns or values?
2. If you get an error message, read the error message. Which input or which step is producing the error?
3. Take a look at the attribute table of the input layer that is responsible for this layer and at the processing algorithm (white boxes) this layer is feeding into. You can open the parameters for the algorithms by clicking on the `...` in the algorithm box. A new window will open with the parameters for the algorithm. What value is the algorithm expecting? What values or data is available in the input layer?
4. Adjust the values the algorithms is expecting or preprocess the input layer so the columns and values are exactly what the algorithm expects. 

__For example__,

FEWSNET changed the structure of the IPC Food Security Projection Data:
- The data for ML1 and ML2 is no longer available as two distinct shapefiles, but the (overlapping) polygons for both scenarios are contained in a single geojson file. 
- Furthermore, the values for the [different food insecurity phase](https://giscience.github.io/gis-training-resource-center/english/content/en/GIS_AA/en_qgis_drought_trigger_somalia.html#what-is-ipc-food-security-projection-data) (1 to 5: Minimal, Stressed, Crisis, Emergency, Famine) are no longer in a column called "ML1" and "ML2" respectively, but in a column with the name __"value"__.
- The model components "weighing pop-sum based on IPC phase" are expecting a column with the name "ML1" and "ML2", but the columns with this information (IPC Phase) with the new input layers are no longer called "ML1" and "ML2" and are called "value".

```{figure} ../../../fig/troubleshooting_model_example.png
---
name: troubleshoot_model_SOM
align: center
widht: 750 px
---
```

To fix the model, we need to do the following:

- Extract the "ML1" and "ML2" polygons as two separate vector layers. We can use the tool "Extract by Attribute".
- In the field calculator, we need to adjust the expression so it includes the correct column. Change "ML1" and "ML2" into "value" respectively. 

```{figure} ../../../fig/troubleshooting_model_fix_example.png
---
name: troubleshoot_model_SOM
align: center
widht: 750 px
---
```


# Trigger Workflow Manually <a id="trigger-workflow-manually"></a>

:::{attention}

As of may 2025, the trigger model uses the IPC Phase Classification analysis by the IPC and no longer by FEWSNET. 
The data format has changed and the manual workflow no longer works as described below. 
Due to differences in the data structure as well as the extent of the geometries, the manual workflow has changed considerably.

:::

## Step 1: Setting up folder structure <a id="step-1-setting-up-folder-structure-2"></a>


```{figure} ../../../fig/Drought_EAP_Worklow_Step_1_1.png
---
width: 1000px
name: 
align: center
---
```
__Purpose:__ In this step we set up the correct folder structure to make the analysis easier and to ensure consitent results. 

__Tool:__ No special tools or programs are needed.

``````{list-table}
:header-rows: 1
:widths: 10 25

* - Instruction
  - Folder Structure
* - 1. Open the Folder “FbF_Drought_Monitoring_Trigger"
    2. Open the subfolder "Monitoring"
    3. Copy the Template folder “TEMPLATE_Year_Month” and change the name to the current year and month. The result could be the folder "2022_05"
    
  -
    ```{figure} ../../../fig/Folder_structure_FbF_Drought_Monitoring_Trigger.drawio.svg
    ---
    width: 450px
    name: 
    align: center
    ---
    ```
``````

The Video below shows the process for setting up the folder for decmber 2023.


```{dropdown} Video: Setting up folder structure 
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_Trigger_folder_setup.mp4"></video>
```

## Step 2: Download of the forecast data <a id="step-2-download-of-the-forecast-data-2"></a>

```{figure} ../../../fig/Drought_EAP_Worklow_Step_2_2.png
---
width: 1000px
name: 
align: center
---
```

__Tool:__ FileZilla and Interent Browser

The current plans provide that ICPAC will monthly provide the SPI-12 forcast whereas the IPC data will be pulled from the FEWSNET website. FEWS NET publishes IPC data on its website. 
The main data publications plus the updates of the IPC data amount to the publication of new data almost monthly.

### SPI-12 Data <a id="spi-12-data-2"></a>


ICPAC will provide the SPI-12 forecasts on their FTP (File Transfer Protocol). There are different ways to access the FTP-Server. We recommend to install and once set up [FileZilla](https://filezilla-project.org/download.php?platform=win64). This will make your work easily repeatable on a monthly basis.

1. Download Filezilla [here](https://filezilla-project.org/download.php?platform=win64).
2. Install the `.exe` file you have downloaded. 
3. Open FileZilla.


4. Establish a connection to the FTP Server by insterting the credentials you have been passed (Host, Username and Password) and clicking `Quickconnect`.


In FileZilla you have four windows. On the left hand side you will see the folder on your computer in the upper window. By clicking on a folder, the documents in the folder will be shown in the lower left window.
On the right hand side, you will see in the upper window the FTP data folder and by clicking on it, the data will be shown in the lower right window.

In order to pass the data from the FTP Server to your own machine you can simply drag and drop the folder or data from the righthandside windows (FTP-Server) to the lefthandside windows (your Computer). To do so, firstly navigate to your folder where you wneed the latest SPI-12 data to be located `.../FbF_Drought_Monitoring_Trigger/Monitoring/Year_Month_template/SPI_12`. Then drag and drop the latest SPI-12 into the folder.



```{figure} ../../../fig/FileZilla.PNG
---
height: 400px
name: FileZilla Interface
align: center
---
```

### IPC Data <a id="ipc-data-2"></a>

The IPC Projection data is provided and regularly updated on the [IPC Website](https://www.ipcinfo.org/ipc-country-analysis/details-map/en/c/1159510/?iso3=SOM). 
To navigate to the latest IPC Projection data on Somalia, navigate to `Latest Analyses` in the top bar > `IPC Analyses` > `Acute Food Insecurity Classification`. Here you look for the latest analysis for Somalia. 

<!---```{Warning}
The FEWSNET pages change often!
```

```{admonition} Updates to FEWSNET
:class: warning

As of December 2024, the FEWSNET Website does not offer the IPC data for ML1 and ML2 as two distinct shapefiles contained in a zip-file. Instead, you can download the GeoJSON-file, which contains a polygon layer with both the ML1 and ML2 polygons. The model and the documentation has been updated to work with the GeoJSON-file.

```
-->

1. Go to the [IPC website](https://www.ipcinfo.org)
2. In the top bar, navigate to `Latest Analyses` > `IPC Analyses` > `Acute Food Insecurity Classification`.
3. On the new website, select Somalia as a country and select the newest dataset.
4. On this website, you will see both a map of the current and the projected IPC phase classifications, as well as some metadata. On the right side of the map, click on the button `Download GIS format`. This will download the analysis in a GeoJSON format, containing polygons for the administrative boundaries and IPC phases, as well as points for the IPC phase classification for IDP camps. 


```{figure} ../../../fig/en_IPCinfo_website_dl_som.png
---
height: 350px
name: IPCinfo_download_projections
align: center
---
```

4. Download the __GeoJSON file__. The filename is composed of the country name, the analysis type, and Year and month of publication. E.g., `Somalia-Acute Food Insecurity January 2025.geoJSON`

:::{note}

In some cases, your operating system (Windows) misidentifies the GeoJSON-file as a `.customization`-file. This does not change anything and can be loaded into your QGIS-project.

:::

5. Copy the GeoJSON-file into the input monitoring folder.
  * Example path: `/FbF_Drought_Monitoring_Trigger/Input_monitoring/Year_Month_template/Somalia-Acute Food Insecurity January 2025.geoJSON`

<!--- REMOVED OLD WORKFLOW WITH FEWSNET DATA

The IPC Projection data is provided and regulary updated on the [FEWSNET Website](https://fews.net/).
On the website you will have to click on Somalia to acess the data. Alternativley, you can  navigate through `Data` -> `Acute Food Insecurity Data` and enter „Somalia". In the menu you will see different dataformats for different timestamps. Once you find out which timestamp is the most current one find the ZIP download. We need the data in shapefile (.shp) format, which is only included in the ZIP file and not provided as single download file. 


```{Warning}
The FEWSNET pages change often!
```

```{admonition} Updates to FEWSNET
:class: warning

As of December 2024, the FEWSNET Website does not offer the IPC data for ML1 and ML2 as two distinct shapefiles contained in a zip-file. Instead, you can download the GeoJSON-file, which contains a polygon layer with both the ML1 and ML2 polygons. The model and the documentation has been updated to work with the GeoJSON-file.

```


1. Go to [FEWSNET Website](https://fews.net/). Click on `Data` -> `Acute Food Insecurity`.
2. Scroll down. In `Geograhic Area` typ in “Somalia” and click `Apply`
3. Choose the newest dataset.

```{figure} ../../../fig/IPC_Projections_website.png
---
height: 250px
name: FEWSNET IPC - Download IPC Projections
align: center
---
```

4. Download the GeoJSON file. The filename is composed of "SO" for Somalia, year and month of the report, as well as the projection type. E.g., `SO_202412_ML1ML2.geojson`
5. Copy the GeoJSON-file into the input monitoring folder.
  * Example path: `/FbF_Drought_Monitoring_Trigger/Input_monitoring/Year_Month_template/IPC_ML1ML2`


:::::{dropdown} Download workflow for shapefiles (if available)

4. Download the one with the __ZIP__ Data
5. When you have downloaded the data, right-click on the file and click on `Extract all` -> `Extract`
6. Open the extracted folder and copy the ML1 data in the IPC_ML1 folder you have created in step 1. 
  * The filename is composed of "SO" for Somalia, year and month of the report month e.g `SO_202308_ML1.shp`
  Example path: `.../FbF_Drought_Monitoring_Trigger/Monitoring/Year_Month_template/IPC_ML1`
7. Copy the ML2 data into IPC_ML2 folder you have created in step 1.
  * The filename is composed of "SO" for Somalia, year and month of the report month e.g `SO_202308_ML2.shp`
  Example path: `.../FbF_Drought_Monitoring_Trigger/Monitoring/Year_Month_template/IPC_ML2`
```{Warning}
Make sure to not use the ML1_IDP data which comes in the .zip folder as well!
```

```{Warning}
Remember that you need to copy over all components that the respective [shapefile](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_geodata_types_wiki.html#vector-data) is composed of. Most probably it has 5 components: .cpg, .dbf, .prj, .shp, and .shx.
```{figure} ../../../fig/IPC_zip.PNG
---
height: 300px
name: Content of .zip file downloaded containing ML1 and ML2 IPC projections
align: center
---
```

:::::

```{tip}
On the [main FEWSNET page](https://fews.net/) you can also sign up for information on latest updates via email. For this option scroll down to the end of the page and click on `Sign up for Emails`. You will then get the option to choose updates only for Somalia.

```{figure} ../../../fig/IPC_Newsletter.png
---
height: 60px
name: FEWSNET Newsletter
align: center
---
```
-->

## Step 3: Loading data into QGIS <a id="step-3-loading-data-into-qgis-2"></a>

```{figure} ../../../fig/Drought_EAP_Worklow_Step_3_1.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__ In this step, all the data needed will be loaded into QGIS.

__Tool:__ No specific tools are needed, only QGIS.

1. Open QGIS and create a [new project](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_projects_folder_structure_wiki.html#step-by-step-setting-up-a-new-qgis-project-from-scratch) by clicking on `Project` -> `New`
2. Once the project is created save the project in the folder you created in Step 1 (e.g. 2022_05). To do that click on `Project` -> `Save as` and navigate to the folder. Give the project the same name as the folder you created (e.g. 2022_05). Then click `Save`
3. Load all input data in QGIS by [drag and drop](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_import_geodata_wiki.html#open-raster-data-via-drag-and-drop). Click on `Project` -> `Save` 
  * From the folder you created in step 1
    * IPC Phase Classification
    * SPI-12
  * From the `Fixed_data` folder:
    * district_pop_som
    * Regions
    * risk_assessment.gpkg
    * WorldPop_som.tif

__Result:__ QGIS project with all necessary data ready to be analysed. 

This video shows how to setup the QGIS project for April 2022 and how to import all data into the project.

```{dropdown} Video: Loading data into QGIS
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_Trigger_step_3.mp4"></video>
```


## Step 4: Formatting the ADM2-names <a id="step-4-formatting-the-adm2-names"></a>


__Purpose:__ The GeoJSON file from IPC contains a polygon layer that contains the administrative boundaries and the IPC phase for the current analysis (C) and the projection (P). However, it is all contained in one layer. To be able to perform our analysis steps, we need to prepare the data. In the column where the adm2-names are saved, there are several polygons with the same adm names, but have a "(1)" or "(2)" added at the end. We need to remove number in the parantheses so we can dissolve the polygons in the next step. 

__Tool:__ Field Calculator

`````{list-table}
:header-rows: 1
:widths: 20 25

* - Instruction
  - Field Calculator
* - 1. Select the IPC Phase classification layer and open the [field calculator](https://giscience.github.io/gis-training-resource-center/english/content/en/Module_5/en_qgis_non_spatial_tools.html#calculate-field)
    2. Check the box `Update existing field` and select the field "area".
    3. Enter the following expression in the expression box:
    ```
    replace(
        replace(
            replace(
                replace(
                    replace("area", ' (1)', ''),
                    ' (2)', ''
                ),
                ' (3)', ''
            ),
            ' (4)', ''
        ),
        ' (5)', ''
    )
    ```
    4. Click `Ok`. 
  - 
    ```{figure} ../../../fig/drought_EAP_workflow_step_4_march2025.png
    width: 450 px
    align: center
    ---
    
    ```
`````

## Step 5: Dissolving admin 2 polygons <a id="step-5-dissolving-admin-2-polygons"></a>


__Purpose:__ To get a layer of the administrative boundaries for the district, we need to dissolve the polygons  from the formatted layer from the previous step using the field "area". This will output one polygon per distinct "area" value. In other words a layer withe adm2 boundaries. 

__Tool:__ Dissolve

:::{note} 

We cannot use a different polygon layer with the adm2 boundaries as we are calculating the population per polygon in the following steps and the polygons need to match exactly in order to get the correct population weighing. 

:::

`````{list-table}
:header-rows: 1
:widths: 20 25

* - Instruction
  - Dissolve
* - 1. In the [processing toolbox](), search for "Dissolve". Click on it.
    2. `Input Layer`: IPC Phase Classification (formatted as in step 4)
    3. `Dissolve field(s)`: "area"
    4. Click `Run`. A new layer called "Dissolved" will appear in your layers panel. 
  -
    ```{figure} ../../../fig/drought_EAP_workflow_step_5_march2025.png
    ---
    width: 450px
    align: center
    ---
    ```
`````

## Step 6: Add population statistics to the adm2 layer <a id="step-6-add-population-statistics-to-the-adm2-layer"></a>

__Purpose:__ For the calculation of the IPC index, we need to have the population per adm2 polygon. Using the worldpop raster layer, we can calculate the population inside each district using the output from the previous step


## Step 4: Extracting ML1 and ML2 from the GeoJSON layer <a id="step-4-extracting-ml1-and-ml2-from-the-geojson-layer"></a>

```{figure} ../../../fig/Drought_EAP_Worklow_Step_4_1_NEW.png
---
width: 1000 px
align: center
---
```

__Purpose:__ The GeoJSON file from FEWSNET with the IPC data contains both the ML1 and ML2 polygons in the same layer. In order to process these polygons separately in the next step, we need to extract and save them as new layers.

__Tool:__ "Extract by Attributes"

`````{list-table}
:header-rows: 1
:widths: 20 25

* - Instruction
  - Extract by Attribute
* - 1. In the [processing toolbox](), search for "Extract by attribute". Click on it.
    2. `Input Layer`: ML1 and ML2 geojson (`Year_Month_ML1ML2`)
    3. `Selection attribute`: scenario
    4. `Value`: ML1
    5. Under `Extraced (Attribute)`, click on the three points ![](../../../fig/Three_points.png) -> `Save to File` and navigate to your monitoring folder [Year_Month]. Give the output the name "IPC_Year_Month_ML1" and click `Save`.
    6. Under `Extracted (non-matching)`, click on the three points ![](../../../fig/Three_points.png) -> `Save to File` and navigate to your monitoring folder [Year_Month]. Give the output the name "IPC_Year_Month_ML2" and click `Save`.
    7. Click `Run`
  -
    ```{figure} ../../../fig/SRCS_Trigger_step_4_Extract_by_attribute.png
    ---
    width: 450px
    name: 
    align: center
    ---
    ```
`````

## Step 5: Fixing the Geometries for the ML 1 & ML 2 layers <a id="step-5-fixing-the-geometries-for-the-ml-1-and-ml-2-layers"></a>

```{figure} ../../../fig/Drought_EAP_Worklow_Step_5_1_NEW.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__ The aim is to fix the [errors in the geometries](https://giscience.github.io/gis-training-resource-center/english/content/en/Module_3/en_qgis_digitalisation.html#spatial-digitisation-errors-in-qgis) of each layer. Otherwise, we would receive error messages in the further steps.

```{Attention}
You need to perform this step two times. One time for ML 1 and a second time for ML 2.
```

__Tool:__ Fix geometries

`````{list-table}
:header-rows: 1
:widths: 20 25

* - Instruction
  - Fix geometries
* - 1. In the [processing toolbox](), search for "Fix geometries". Click on it.
    2. `Input Layer`: ML1 and ML2
    3. `Repair Method`: structure
    4. Under `Extraced (Attribute)`, click on the three points ![](../../../fig/Three_points.png) -> `Save to File` and navigate to your monitoring folder [Year_Month]. Give the output the name "IPC_Year_Month_ML1_fixed" and click `Save`.
    5. Click `Run`
  -
    ```{figure} ../../../fig/SRCS_Trigger_step_5_fix_geometries_NEW.png
    ---
    width: 450px
    name: 
    align: center
    ---
    ```
`````


## Step 6: Intersection of ML 1 & ML 2 data with the district polygons <a id="step-6-intersection-of-ml-1-and-ml-2-data-with-the-district-polygons"></a>

```{figure} ../../../fig/Drought_EAP_Worklow_Step_6_1_NEW.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__ The goal is to receive polygon layers which share both the borders and the attributes of both input layers.

```{Attention}
You need to perform this step two times. One time for ML 1 and a second time for ML 2.
```

__Tool:__ [`Intersection`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_geoprocessing_wiki.html#intersection)


`````{list-table}
:header-rows: 1
:widths: 20 25

* - Instruction
  - Intersection
* - 1. Click on `Vector` -> `Geoprocessing Tools` -> [`Intersection`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_geoprocessing_wiki.html#intersection)
    2.`Input Layer`: ML 1 or ML 2
    3. `Overlay layer`: district_pop_sum
    4. Under `Intersection` click on the three points ![](../../../fig/Three_points.png)-> `Save to File` and navigate to you monitoring folder [Year_Month]. Give the output the name "ML1_Intersection" or "ML2_Intersection" and click `Save`
    5. Click `Run`
  -
    ```{figure} ../../../fig/SRCS_Trigger_step_4_Intersection.png
    ---
    width: 450px
    name: 
    align: center
    ---
    ```
`````

__Result:__ After doing this for ML1 and ML2 you should have two polygon layers, each containing all columns of ML1 (or ML2) and district_pop_sum.

```{Note}
The resulting layer can have more rows than the original layers.
```


The video shows the whole process on the example of ML 1.
```{dropdown} Video: Intersection of ML 1 & ML 2 data with the district polygons 
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_Trigger_step_4_Intersection.mp4"></video>
```

## Step 7: Calculation of Population per Intersection Polygon <a id="step-7-calculation-of-population-per-intersection-polygon"></a>

```{figure} ../../../fig/Drought_EAP_Worklow_Step_7_1_NEW.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__ Here we calculate the population in each polygon of the intersection layer from step 4.

```{Attention}
You need to perform this step two times: One time for ML 1 and a second time for ML 2.
```

__Tool:__  [`Zonal Statistics`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_raster_basic_wiki.html#zonal-statistics)

``````{list-table}
:header-rows: 1
:widths: 20 25

* - Instruction
  - Zonal Statistics
* - 1.  In the `Toolbox` -> Search for [`Zonal Statistics`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_raster_basic_wiki.html#zonal-statistics)
    * Tip: If the `Toolbox` is not opne click `Processing`-> `Toolbox`
    2. `Input Layer`: "ML1_Intersection" or "ML2_Intersection"
    3. `Raster Layer`: "som_ppp_2020_UNadj_constrained.tif"
    4. Statistics to calculate: Only `Sum`
    5.  Under `Zonal Statistics` click on the three points ![](../../../fig/Three_points.png)-> `Save to File` and navigate to you monitoring folder [Year_Month]. Give the output the name "ML1_zonal_statistic" or "ML2_zonal_statistic" and click `Save`
    5. Click `Run
  -
    ```{figure} ../../../fig/SRCS_Trigger_step_5_zonal_statistic.png
    ---
    width: 450px
    name: 
    align: center
    ---
    ```
``````

__Result:__ The result should be the “ML1_zonal_statistic” and “ML2_zonal_statistic” polygon layers. These layers should have the same columns in the attribute table __plus__ the column “_sum”, which is the number of people living in the single parts of the polygons.


```{dropdown} Video:  Calculation of Population per Intersection Polygon
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_Trigger_step_5_zonal_statistic.mp4"></video>
```

## Step 8: Weighting of the Population based on IPC-Phase <a id="step-8-weighting-of-the-population-based-on-ipc-phase"></a>

```{figure} ../../../fig/Drought_EAP_Worklow_Step_8_1_NEW.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__ The purpose of this step is the weighting of the population in the five IPC phases as described in [IPC Data](https://giscience.github.io/gis-training-resource-center/english/content/en/GIS_AA/en_qgis_drought_trigger_somalia.html#ipc-population-weighted-index).

```{Attention}
You need to perform this step two times. One time for ML 1 and a second time for ML 2.
```
__Tool:__  [`Field Calculator`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_table_functions_wiki.html#calculate-field)


1. Right-click on the layer “ML1_zonal_statistic” (or “ML2_zonal_statistic”) -> `Open Attribute Table`-> click on [`Field Calculator`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_table_functions_wiki.html#calculate-field) ![](../../../fig/mActionCalculateField.png) to open the field calculator
2. Check “Create new field"
3. `Output field name`: Name the new column “pop_sum_weighted”
4. `Result field type`: Decimal number (real)
5. Add the code block from Input into the `Expression` field and click `ok`

``````{list-table}
:header-rows: 1
:widths: 15 15

* - ML 1
  - ML 2
* - ```md
    CASE

    WHEN "value" = 3 THEN "_sum" * 1
    WHEN "value" = 4 THEN "_sum" * 3
    WHEN "value" = 5 THEN "_sum" * 6
    ELSE "_sum"

    END
    ```
  - ```md
    CASE

    WHEN "value" = 3 THEN "_sum" * 1
    WHEN "value" = 4 THEN "_sum" * 3
    WHEN "value" = 5 THEN "_sum" * 6
    ELSE "_sum"

    END
    ```
``````
6. Save the new column by clicking on ![](../../../fig/mActionSaveEdits.png) in the attribute table and end the editing mode by clicking on ![](../../../fig/mActionToggleEditing.png)

Here is the `Field Calculator` window of how it should look to calculate pop_sum_weighted for ML1.

```{figure} ../../../fig/SRCS_Trigger_step_6_field_calculator.png
---
width: 500px
name: 
align: center
---
```
__Result:__ The two layers “ML1_zonal_statistic” and “ML2_zonal_statistic” should now both have the column “pop_sum_weighted”.


The video shows the whole process with the the example of ML 1.

```{dropdown} Video: Weighting of the Population based on IPC-Phase
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_Trigger_step_6_field_calculators.mp4"></video>
```

## Step 9: Adding the total district population to Intersection Polygons <a id="step-9-adding-the-total-district-population-to-intersection-polygons"></a>

```{figure} ../../../fig/Drought_EAP_Worklow_Step_9_1_NEW.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__ Now we want to add a column with the total district population to “ML1_zonal_statistic” and “ML2_zonal_statistic”.

```{Attention}
You need to perform this step two times. One time for ML 1 and a second time for ML 2.
```

__Tool:__ [`Join attributes by field value`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_non_spatial_joins_wiki.html#join-attributes-by-field-value)

``````{list-table}
:header-rows: 1
:widths: 20 25

* - Instruction
  - Join attributes by field value
* - 1. In the `Toolbox`-> Search for [`Join attributes by   field value`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_non_spatial_joins_wiki.html#join-attributes-by-field-value)
      * Tip: If the `Toolbox` is not opne click `Processing`-> `Toolbox`
    2. `Input Layer`: Select “ML1_zonal_statistic” (or “ML2_zonal_statistic”)
    3. `Table field`: Select “admin2Name”
    4. `Input Layer 2`: Select the layer “district_pop_som”
    5. `Table field 2`: Select “admin2Name”
    6. `Layer 2 field to copy`: Click on the three points ![](../../../fig/Three_points.png) and select “admin2Name” and “districtpo”
    7. `Join type`: Select the option “Take attributes of the first matching feature only (one-to-one)
    8. Under `Join Layer [optional]` click on the three points ![](../../../fig/Three_points.png)-> `Save to File` and navigate to you monitoring folder [Year_Month]. Give the output the name "ML1_join" or "ML2_join" and click `Save`
    9. Click `Run`
  -
    ```{figure} ../../../fig/SRCS_Trigger_step_7_join.png
    ---
    width: 450px
    name: 
    align: center
    ---
    ```
``````

__Result:__ Now you should have to new polygon layer named “ML1_join” and ML2_Join” containing the column districtpo.


```{dropdown} Video: Adding the total district population to Intersection Polygons
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_Trigger_step_7_join.mp4"></video>
```

## Step 10: Calculation of the Population Proportion per Intersection Polygon <a id="step-10-calculation-of-the-population-proportion-per-intersection-polygon"></a>

```{figure} ../../../fig/Drought_EAP_Worklow_Step_10_1_NEW.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__ In this step we calculating the [IPC-Population Weighted Index](https://giscience.github.io/gis-training-resource-center/english/content/en/GIS_AA/en_qgis_drought_trigger_somalia.html#ipc-population-weighted-index) for every small part of the polygon layer. 
```{Attention}
You need to perform this step two times. One time for ML 1 and a second time for ML 2.
```

__Tool:__[`Field Calculator`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_table_functions_wiki.html#calculate-field)

1. Right-click on Intersection_population Polygons layer -> “Attribute Table”-> click on  [`Field Calculator`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_table_functions_wiki.html#calculate-field) ![](../../../fig/mActionCalculateField.png)to open the field calculator
2. Check `Create new field`
3. `Output field name`: Name the new column “Index_per_IPCPolygon_ML1” (or "Index_per_IPCPolygon_ML2”)
4. `Result field type`: Decimal number (real)
5. Add the code into the `Expression` field
```md
"pop_sum_weighted"/"districtpo"
```
6. Click `ok`
7. Save the new column by clicking on ![](../../../fig/mActionSaveEdits.png) in the attribute table and end the editing mode by clicking on ![](../../../fig/mActionToggleEditing.png)

```{figure} ../../../fig/SRCS_Trigger_step_8_field_calculator.png
---
width: 500px
name: 
align: center
---
```

__Result:__ Both layer “ML1_join” and ML2_Join” should now have the column “Index_per_IPCPolygon_ML1” or “Index_per_IPCPolygon_ML2”. The numbers in this column have to be smaller than in the “district” column.

The video shows the whole process with the the example of ML 1.

```{dropdown} Video: Calculation of Population Proportion per Intersection Polygon
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_TRigger_step_8_field_calculator.mp4"></video>
```

## Step 11: Calculate the IPC Index per District <a id="step-11-calculate-the-ipc-index-per-district"></a>
```{figure} ../../../fig/Drought_EAP_Worklow_Step_11_1_NEW.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__  The purpose of this step is to calculate a population weighted mean over the IPC classes that fall within a district, in order to give the amount of people living in a certain IPC class more importance than just the area affected by a certain IPC class. The result is a IPC Index value for each district.

__Tool:__ `Join attribute by location (summary)`

``````{list-table}
:header-rows: 1
:widths: 20 25

* - Instruction
  - Join attribute by location (summary)
* - 1. In the `Toolbox`-> Search for `Join attribute by location (summary)`
      * Tip: If the `Toolbox` is not opne click `Processing`-> `Toolbox` 
    2. `Input Layer`: Select your “district_pop_som” layer
    3. `Input Layer 2`: Select “ML1_join” (or ML2_Join”)
    4. `Geometric predicate`: Select “Intersection”
    5. `Field to summarise`: Select “Index_per_IPCPolygon_ML1” (or “Index_per_IPCPolygon_ML2” )
    6. `Summaries to calculate`: Chose only the option “mean”
    7. Under `Join Layer` click on the three points ![](../../../fig/Three_points.png)-> `Save to File` and navigate to you monitoring folder [Year_Month]. Give the output the name "ML1_join_location" or "ML2_join_location" and click `Save`
    8. Click `Run`
  -
    ```{figure} ../../../fig/SRCS_Trigger_step_9_join_location.png
    ---
    width: 450px
    name: 
    align: center
    ---
    ```
``````

__Result:__ As a result, your two layers "ML1_join_location" and "ML2_join_location" should have the column “Index_per_IPCPolygon_ML1_mean” or “Index_per_IPCPolygon_ML2_mean”. Furthermore, the number of rows should be the exact number of districts in Somalia and the polygons should have the exact shape of the districts.

```{dropdown} Video: Calculate IPC Index per District
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_Trigger_step_9_join_location.mp4"></video>
```


## Step 12.: Join ML1 and ML2 <a id="step-12-join-ml1-and-ml2"></a>
```{figure} ../../../fig/Drought_EAP_Worklow_Step_12_1_NEW.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__ The purpose of this step is to merge “ML1_join_location" and "ML2_join_location” into one layer so we have the IPC-Index for all districts.

__Tool:__ [`Join attributes by field value`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_non_spatial_joins_wiki.html#join-attributes-by-field-value)

``````{list-table}
:header-rows: 1
:widths: 20 25

* - Instruction
  - Join attribute by location (summary)
* - 1. In the `Toolbox`-> Search for [`Join attributes by field value`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_non_spatial_joins_wiki.html#join-attributes-by-field-value)
    * Tip: If the `Toolbox` is not opne click `Processing`-> `Toolbox` 
    2. `Input Layer`: Select your "ML1_join_location" layer 
    3. `Table field`: Select “admin2Name”
    4. `Input Layer 2`: Select your "ML2_join_location" layer 
    5. `Table field 2`: Select “admin2Name”
    6. `Layer 2 field to copy`: Click on the three points and  select “Index_per_IPCPolygon_ML2_mean”
    7. `Join type`: Select the option “Take attributes of the first matching feature only (one-to-one)
    8. Under `Join Layer` click on the three points ![](../../../fig/Three_points.png)-> `Save to File` and navigate to you monitoring folder [Year_Month]. Give the output the name "IPC_index_district" and click `Save`
    9. Click `Run`
  -
    ```{figure} ../../../fig/SRCS_Trigger_step_10_IPC_Index_district.png
    ---
    width: 450px
    name: 
    align: center
    ---
    ```
``````

__Result:__ Layer with the districts of Somalia and the IPC-Index of each district.

```{dropdown} Video: Join ML1 and ML2 I
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_Trigger_step_10_join.mp4"></video>
```

## Step 13: Calculation of SPI-12 Mean per District <a id="step-13-calculation-of-spi-12-mean-per-district"></a>

```{figure} ../../../fig/Drought_EAP_Worklow_Step_13_1_NEW.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__ Calculate the mean value over the SPI-12 values of all pixels that fall within a scertain districts area, in order to have one SPI-12 value for each district.

__Tool:__ [`Zonal Statistics`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_raster_basic_wiki.html#zonal-statistics)

``````{list-table}
:header-rows: 1
:widths: 20 25

* - Instruction
  - Zonal Statistics
* - 1. In the `Toolbox` -> Search for [`Zonal Statistics`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_raster_basic_wiki.html#zonal-statistics)
    * Tip: If the `Toolbox` is not open click `Processing`-> `Toolbox`
    2. `Input Layer`: district_pop_som
    3. `Raster Layer`: SPI Forecast
    4. `Output column prefix`: Use  "SPI12_"
    5. `Statistics to calculate`: “Mean”
    6.  Under `Zonal Statistics` click on the three points ![](../../../fig/Three_points.png)-> `Save to File` and navigate to you monitoring folder [Year_Month]. Give the output the name "SPI12_district" and click `Save`
    5. Click `Run``
  -
    ```{figure} ../../../fig/SRCS_Trigger_step_11_IPC_zonal_district.png
    ---
    width: 450px
    name: 
    align: center
    ---
    ```
``````

__Result:__ A layer of all districts of Somalia with the mean SPI-12.


```{dropdown} Video: Calculation of SPI12 Mean per District
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_Trigger_step_11_zonal_staistics.mp4"></video>
```

## Step 14: Join SPI-12 Mean to the IPC Index <a id="step-14-join-spi-12-mean-to-the-ipc-index"></a>

```{figure} ../../../fig/Drought_EAP_Worklow_Step_14_1_NEW.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__ The purpose of this step is to merge data from two different data sources into one data frame so that it can be jointly analysed.

__Tool:__[`Join attributes by field value`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_non_spatial_joins_wiki.html#join-attributes-by-field-value)

``````{list-table}
:header-rows: 1
:widths: 20 25

* - Instruction
  - Join attributes by field value
* - 1.  In the `Toolbox`-> Search for [`Join attributes by field value`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_non_spatial_joins_wiki.html#join-attributes-by-field-value)
      * Tip: If the `Toolbox` is not opne click `Processing`-> `Toolbox`
    2. `Input Layer`: Select your “IPC_index_district”
    3. `Table field`: Select “admin2Name”
    4. `Input Layer 2`: Select your “SPI12_district”
    5. `Table field 2`: Select “admin2Name”
    6. `Join type`: Select the option “Take attributes of the first matching feature only (one-to-one)"
    7. Under `Join Layer` click on the three points ![](../../../fig/Three_points.png)-> `Save to File` and navigate to you monitoring folder [Year_Month]. Give the output the name "IPC_index_SPI_12_district" and click `Save`
    8. Click `Run`
  -
    ```{figure} ../../../fig/SRCS_Trigger_step_12_IPC_SPI12_join.png
    ---
    width: 450px
    name: 
    align: center
    ---
    ```
``````

__Result:__ The result will be a layer of all districts of Somalia with the mean SPI-12 and the IPC-Index of each district.


```{dropdown} Video: Join SPI12 Mean to the IPC Index
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_Trigger_step_12_join_IPC_SPI12.mp4"></video>
```

## Step 15: Evaluate the Trigger Activation <a id="step-15-evaluate-the-trigger-activation"></a>

```{figure} ../../../fig/Drought_EAP_Worklow_Step_15_1_NEW.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__ The purpose of this step is to gain a quick overview of possible trigger activation without having to revise the actual data. Instead we will have a binary column with trigger = yes or trigger=no values.

__Tool:__ [`Field Calculator`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_table_functions_wiki.html#calculate-field)



1. Right-click on "IPC_index_SPI_12_district" layer -> `Attribute Table`-> click on  [`Field Calculator`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_table_functions_wiki.html#calculate-field) ![](../../../fig/mActionCalculateField.png) to open the field calculator
2. Check `Create new field`
3. `Output field name`: Name the new column “Trigger_activation”
4. `Result field type`: Text (string)
5. Add the code below into the `Expression` field
``````{list-table}
:header-rows: 1
:widths: 15

* - Code
* - ```md
    CASE

    WHEN "Index_per_IPCPolygon_ML1_mean" >0.7 AND "Index_per_IPCPolygon_ML2_mean" > 0.7
    AND
    "SPI12_mean" < -1
    THEN 'yes'
    ELSE 'no'

    END
    ```
``````
6. Click `ok`
7. Save the new column by clicking on ![](../../../fig/mActionSaveEdits.png) in the attribute table and end the editing mode by clicking on ![](../../../fig/mActionToggleEditing.png)

__Result:__ A layer with all districts of Somalia with a column of "Yes" and "No" values indicating whether the trigger levels have been reached or not.

```{figure} ../../../fig/SRCS_Trigger_step_13_trigger_evaluation.png
---
width: 500px
name: 
align: center
---
```

```{dropdown} Video: Evaluate Trigger Activation 
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_Trigger_step_13_trigger_activation.mp4"></video>
```

## Step 16: Visualisation of results <a id="step-16-visualisation-of-results"></a>
```{figure} ../../../fig/Drought_EAP_Worklow_Step_16_1_NEW.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__ Definition of how features are represented visually on the map.

__Tool:__ [Symbology](https://giscience.github.io/gis-training-resource-center/english/content/en/Module_4/en_qgis_map_design_I.html#symbology-for-vector-data)

__Trigger Activation__

1. Right cklick on the “Trigger_activation” layer -> `Properties` -> `Symbology`
2. In the down left corner click on `Style` -> `Load Style`
3. In the new window click on the three points ![](../../../fig/Three_points.png). Navigate to the “FbF_Drought_Monitoring_Trigger/layer_styles” folder and select the file __“Style_Trigger_Activation.qml”__.
4. Click `Open`. Then click on `Load Style`
5. Back in the “Layer Properties” Window click `Apply` and `OK`

```{dropdown} Info: Trigger Activation Layer
You will now see districts where no trigger is activated in green and districts with trigger activation in pink.

The “Style_Trigger_Activation.qml” style layer is configured to show the district names only where the trigger is actually activated. If there is no trigger activation you can activate the admin 1 boundary layer for better map orientation (see __Administrative 2 Boundaries__ below)

```{figure} ../../../fig/Map_yes_trigger.PNG
---
width: 1000px
name: 
align: center
---
```

__Risk Assessment__


7. Right click on the "risk_assessment_districts" layer -> `Properties` -> `Symbology`
8. In the down left corner click on `Style` -> `Load Style`
9. In the new window click on the three points ![](../../../fig/Three_points.png). Navigate to the “FbF_Drought_Monitoring_Trigger/layer_styles” folder and select the file __“somalia_risk_assessment_style.qml”__ style layer.
10. Move the "risk_assessment_district" layer __below__ "Trigger_Activation" layer ([Layer Concept](https://giscience.github.io/gis-training-resource-center/english/content/en/Module_2/en_qgis_geodata_concept.html?highlight=layer#layer-concept)).
11. Back in the “Layer Properties” Window click `Apply` and `OK`


```{dropdown} Info: Risk Assessment Layer
For the creation of an __Intervention Map__ we will have to add the risk assessment data and the respective style file.
For this first of all load from "FbF_Drought_Monitoring_Trigger/Fixed_data/Risk_Assessment" the file "risk_assessment_districts.gpkg". This file is the output of the conducted risk assessment and contains a risk value for each district of Simaliland and Somalia.  In order to visualize it 
```

__Administrative 2 Boundaries (Regions)__

12. Right click on the "Som_Admbnda_Adm1_UNDP" (Regiond) layer -> `Properties` -> `Symbology`
13. In the lower right corner click on `Style` -> `Load Style`
14. In the new window, click on the three points ![](../../../fig/Three_points.png). Navigate to the “FbF_Drought_Monitoring_Trigger/layer_styles” folder and select the file __“somalia_risk_assessment_style.qml”__.
15. Click `Open`. Then click on `Load Style` 
16. Back in the “Layer Properties” Window click `Apply` and `OK`
17. Add a the OpenStreetMap basemap by clicking on `Layer` -> `Add Layer` -> `Add XYZ layer...` -> Select the OpenStreetMap. Click `Add`. ([Wiki basemap](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_basemaps_wiki.html?highlight=osm#basemaps))
18. Place the OpenStreetMap basemap on the bottom.
19. Delet all layers exept:
    * Trigger_activation
    * risk_assessment_districts
    * Som_Admbnda_Adm1_UNDP
    * OpenStreetMap

```{dropdown} Video: Visualisation of results
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/Trigger_model_style.mp4"></video>
```

``````{list-table}
:header-rows: 1
:widths: 20 20

* - Intervention Map __without__ Trigger activation
  - Intervention Map __with__ Trigger activation
* - 
    ```{figure} ../../../fig/Map_no_trigger.PNG
    ---
    width: 1000px
    name: 
    align: center
    ---
    ```
    
  -
    ```{figure} ../../../fig/Map_yes_trigger.PNG
    ---
    width: 450px
    name: 
    align: center
    ---
    ```
``````

```{Attention}
Remember the [layer concept](https://giscience.github.io/gis-training-resource-center/english/content/en/Module_2/en_qgis_geodata_concept.html?highlight=layer#layer-concept) and make sure the basemap layer is at the bottom of your layers panel.
```



## Step 17: Making the print map <a id="step-17-making-the-print-map"></a>

```{figure} ../../../fig/Drought_EAP_Worklow_Step_17_1_NEW.png
---
width: 1000px
name: 
align: center
---
```
__Purpose:__ Viualization of the map features in a printable map layout

__Tool:__  [Print Layout](https://giscience.github.io/gis-training-resource-center/english/content/en/Module_4/en_qgis_map_design_2.html?highlight=print+layout#print-layout)


1. If not done before, delet all layers expect __Trigger_activation__, __risk_assessment_districts__ and __OpenStreetMap__
2. Open a new print layout by clicking on `Project` -> `New Print Layout` -> enter the name of your current Project e.g "2022_04".
3. Go the the __FbF_Drought_Monitoring_Trigger__` folder and drag and drop the file `Trigger_activation_Intervention_map.qpt` in the print layout
4. Change the date to the current date by clicking on "Further map info…" in the items panel. Click on the `Item Properties` tab and scroll down. Here you can change the date in the `Main Properties` field.
5. Adjust the Lgend by clicking on the legend in the  `Item Properties` tab and scroll down until you see the `Legend items` field. If it is not there check if you have to open the dropdown. Make sure `Auto update` is not checked.
    * Remove all itemes in the legend be clicking on the item and then on the red minus icon below.
    * Add __Trigger_activation__ and __risk_assessment_districts__ to the legend by clicking on the green plus and click on the layer and click `ok`
 

```{dropdown} Video: Making print map
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_Trigger_print_map.mp4"></video>
```

```{Attention}
Make sure you edit the Map Information on the template, e.g. current date. Also make sure to check the legend items: Remove unnecessary items and eventually change the names to meaning descriptions.
```


In order to easily visualize the output of the trigger analysis we provide you with a 
[map template](https://giscience.github.io/gis-training-resource-center/english/content/en/Module_4/en_qgis_map_design_2.html#map-templates) that can be used as a base for your visualization. You can find the template in the following directory: ".../FbF_Drought_Monitoring_Trigger/maps_somalia_template_risk_assessment.qpt".

You can also adapt the template to your needs and preferences. You can find help [here](https://giscience.github.io/gis-training-resource-center/english/content/en/Module_4/en_qgis_map_design_2.html#print-layout).

```{Attention}
Make sure you edit the Map Information on the template, e.g. current date. Also make sure to check the legend items: Remove unnecessary items and eventually change the names to meaning descriptions.
```

## Step 18: Exporting the Map <a id="step-18-exporting-the-map"></a>


```{figure} ../../../fig/Drought_EAP_Worklow_Step_18_1_NEW.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__ Export the designed and finalized map layout in order tp print it as a pdf or format of your choice.


__Tool:__ [Print Layout](https://giscience.github.io/gis-training-resource-center/english/content/en/Module_4/en_qgis_map_design_2.html?highlight=print+layout#print-layout)

When you have finished the design of you map you can export it as pdf or image file in different datafromats.

__Export as Image__

1. In the print layout click on `Layer` -> `Export as Image`
2. Chose the __Result__ folder in the folder you have created in step 1. Give the file the name of the project e.g 2022_04
3.  Click on `Save`
4. The window "Image Export Options" will appear. 
5. Click `Save`.

Now the image can be found in the result folder in the folder you created in Step 1


__Export as PDF__

1. In the print layout click on `Layer` -> `Export as PDF`
2. Chose the __Result__ folder in the folder you have created in step 1. Give the file the name of the project e.g 2022_04
3.  Click on `Save`
4. The window "PDF Export Options" will appear.  For the best results, select the `lossless` image compression.
5. Click `Save`.

Now the image can be found in the result folder in the folder you created in Step 1.


```{figure} ../../../fig/map_output_example2.png
---
width: 1000px
name: 
align: center
---
```

::::::{dropdown} Workflow for the old model (with shapefiles)

__Step 1 to Step 3 are the same as with the new model.__

## Step 4: Intersection of ML 1 & ML 2 data with the district polygons <a id="step-4-intersection-of-ml-1-and-ml-2-data-with-the-district-polygons"></a>

```{figure} ../../../fig/Drought_EAP_Worklow_Step_4_1.png
---
width: 1000px
name: 
align: center
---
```
__Purpose:__ The goal is to receive polygon layers which share both the borders and the attributes of both input layers.

```{Attention}
You need to perform this step two times. One time for ML 1 and a second time for ML 2.
```

__Tool:__ [`Intersection`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_geoprocessing_wiki.html#intersection)


``````{list-table}
:header-rows: 1
:widths: 20 25

* - Instruction
  - Intersection
* - 1. Click on `Vector` -> `Geoprocessing Tools` -> [`Intersection`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_geoprocessing_wiki.html#intersection)
    2.`Input Layer`: ML 1 or ML 2
    3. `Overlay layer`: district_pop_sum
    4. Under `Intersection` click on the three points ![](../../../fig/Three_points.png)-> `Save to File` and navigate to you monitoring folder [Year_Month]. Give the output the name "ML1_Intersection" or "ML2_Intersection" and click `Save`
    5. Click `Run`
  -
    ```{figure} ../../../fig/SRCS_Trigger_step_4_Intersection.png
    ---
    width: 450px
    name: 
    align: center
    ---
    ```
``````

__Result:__ After doing this for ML1 and ML2 you should have two polygon layers, each containing all columns of ML1 (or ML2) and district_pop_sum.

```{Note}
The resulting layer can have more rows than the original layers.
```


The video shows the whole process on the example of ML 1.
```{dropdown} Video: Intersection of ML 1 & ML 2 data with the district polygons 
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_Trigger_step_4_Intersection.mp4"></video>
```

## Step 5: Calculation of Population per Intersection Polygon <a id="step-5-calculation-of-population-per-intersection-polygon"></a>

```{figure} ../../../fig/Drought_EAP_Worklow_Step_5_1.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__ Here we calculate the population in each polygon of the intersection layer from step 4.

```{Attention}
You need to perform this step two times: One time for ML 1 and a second time for ML 2.
```

__Tool:__  [`Zonal Statistics`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_raster_basic_wiki.html#zonal-statistics)

``````{list-table}
:header-rows: 1
:widths: 20 25

* - Instruction
  - Zonal Statistics
* - 1.  In the `Toolbox` -> Search for [`Zonal Statistics`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_raster_basic_wiki.html#zonal-statistics)
    * Tip: If the `Toolbox` is not opne click `Processing`-> `Toolbox`
    2. `Input Layer`: "ML1_Intersection" or "ML2_Intersection"
    3. `Raster Layer`: "som_ppp_2020_UNadj_constrained.tif"
    4. Statistics to calculate: Only `Sum`
    5.  Under `Zonal Statistics` click on the three points ![](../../../fig/Three_points.png)-> `Save to File` and navigate to you monitoring folder [Year_Month]. Give the output the name "ML1_zonal_statistic" or "ML2_zonal_statistic" and click `Save`
    5. Click `Run
  -
    ```{figure} ../../../fig/SRCS_Trigger_step_5_zonal_statistic.png
    ---
    width: 450px
    name: 
    align: center
    ---
    ```
``````

__Result:__ The result should be the “ML1_zonal_statistic” and “ML2_zonal_statistic” polygon layers. These layers should have the same columns in the attribute table __plus__ the column “_sum”, which is the number of people living in the single parts of the polygons.


```{dropdown} Video:  Calculation of Population per Intersection Polygon
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_Trigger_step_5_zonal_statistic.mp4"></video>
```

## Step 6: Weighting of the Population based on IPC-Phase <a id="step-6-weighting-of-the-population-based-on-ipc-phase"></a>

```{figure} ../../../fig/Drought_EAP_Worklow_Step_6_1.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__ The purpose of this step is the weighting of the population in the five IPC phases as described in [IPC Data](https://giscience.github.io/gis-training-resource-center/english/content/en/GIS_AA/en_qgis_drought_trigger_somalia.html#ipc-population-weighted-index).

```{Attention}
You need to perform this step two times. One time for ML 1 and a second time for ML 2.
```
__Tool:__  [`Field Calculator`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_table_functions_wiki.html#calculate-field)


1. Right-click on the layer “ML1_zonal_statistic” (or “ML2_zonal_statistic”) -> `Open Attribute Table`-> click on [`Field Calculator`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_table_functions_wiki.html#calculate-field) ![](../../../fig/mActionCalculateField.png) to open the field calculator
2. Check “Create new field"
3. `Output field name`: Name the new column “pop_sum_weighted”
4. `Result field type`: Decimal number (real)
5. Add the code block from Input into the `Expression` field and click `ok`

``````{list-table}
:header-rows: 1
:widths: 15 15

* - ML 1
  - ML 2
* - ```md
    CASE

    WHEN "ML1" = 3 THEN "_sum" * 1
    WHEN "ML1" = 4 THEN "_sum" * 3
    WHEN "ML1" = 5 THEN "_sum" * 6
    ELSE "_sum"

    END
    ```
  - ```md
    CASE

    WHEN "ML2" = 3 THEN "_sum" * 1
    WHEN "ML2" = 4 THEN "_sum" * 3
    WHEN "ML2" = 5 THEN "_sum" * 6
    ELSE "_sum"

    END
    ```
``````
6. Save the new column by clicking on ![](../../../fig/mActionSaveEdits.png) in the attribute table and end the editing mode by clicking on ![](../../../fig/mActionToggleEditing.png)

Here is the `Field Calculator` window of how it should look to calculate pop_sum_weighted for ML1.

```{figure} ../../../fig/SRCS_Trigger_step_6_field_calculator.png
---
width: 500px
name: 
align: center
---
```
__Result:__ The two layers “ML1_zonal_statistic” and “ML2_zonal_statistic” should now both have the column “pop_sum_weighted”.


The video shows the whole process with the the example of ML 1.

```{dropdown} Video: Weighting of the Population based on IPC-Phase
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_Trigger_step_6_field_calculators.mp4"></video>
```

## Step 7: Adding the total district population to Intersection Polygons <a id="step-7-adding-the-total-district-population-to-intersection-polygons"></a>

```{figure} ../../../fig/Drought_EAP_Worklow_Step_7_1.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__ Now we want to add a column with the total district population to “ML1_zonal_statistic” and “ML2_zonal_statistic”.

```{Attention}
You need to perform this step two times. One time for ML 1 and a second time for ML 2.
```

__Tool:__ [`Join attributes by field value`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_non_spatial_joins_wiki.html#join-attributes-by-field-value)

``````{list-table}
:header-rows: 1
:widths: 20 25

* - Instruction
  - Join attributes by field value
* - 1. In the `Toolbox`-> Search for [`Join attributes by   field value`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_non_spatial_joins_wiki.html#join-attributes-by-field-value)
      * Tip: If the `Toolbox` is not opne click `Processing`-> `Toolbox`
    2. `Input Layer`: Select “ML1_zonal_statistic” (or “ML2_zonal_statistic”)
    3. `Table field`: Select “admin2Name”
    4. `Input Layer 2`: Select the layer “district_pop_som”
    5. `Table field 2`: Select “admin2Name”
    6. `Layer 2 field to copy`: Click on the three points ![](../../../fig/Three_points.png) and select “admin2Name” and “districtpo”
    7. `Join type`: Select the option “Take attributes of the first matching feature only (one-to-one)
    8. Under `Join Layer [optional]` click on the three points ![](../../../fig/Three_points.png)-> `Save to File` and navigate to you monitoring folder [Year_Month]. Give the output the name "ML1_join" or "ML2_join" and click `Save`
    9. Click `Run`
  -
    ```{figure} ../../../fig/SRCS_Trigger_step_7_join.png
    ---
    width: 450px
    name: 
    align: center
    ---
    ```
``````

__Result:__ Now you should have to new polygon layer named “ML1_join” and ML2_Join” containing the column districtpo.


```{dropdown} Video: Adding the total district population to Intersection Polygons
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_Trigger_step_7_join.mp4"></video>
```

## Step 8: Calculation of the Population Proportion per Intersection Polygon <a id="step-8-calculation-of-the-population-proportion-per-intersection-polygon"></a>

```{figure} ../../../fig/Drought_EAP_Worklow_Step_8_1.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__ In this step we calculating the [IPC-Population Weighted Index](https://giscience.github.io/gis-training-resource-center/english/content/en/GIS_AA/en_qgis_drought_trigger_somalia.html#ipc-population-weighted-index) for every small part of the polygon layer. 
```{Attention}
You need to perform this step two times. One time for ML 1 and a second time for ML 2.
```

__Tool:__[`Field Calculator`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_table_functions_wiki.html#calculate-field)

1. Right-click on Intersection_population Polygons layer -> “Attribute Table”-> click on  [`Field Calculator`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_table_functions_wiki.html#calculate-field) ![](../../../fig/mActionCalculateField.png)to open the field calculator
2. Check `Create new field`
3. `Output field name`: Name the new column “Index_per_IPCPolygon_ML1” (or "Index_per_IPCPolygon_ML2”)
4. `Result field type`: Decimal number (real)
5. Add the code into the `Expression` field
```md
"pop_sum_weighted"/"districtpo"
```
6. Click `ok`
7. Save the new column by clicking on ![](../../../fig/mActionSaveEdits.png) in the attribute table and end the editing mode by clicking on ![](../../../fig/mActionToggleEditing.png)

```{figure} ../../../fig/SRCS_Trigger_step_8_field_calculator.png
---
width: 500px
name: 
align: center
---
```

__Result:__ Both layer “ML1_join” and ML2_Join” should now have the column “Index_per_IPCPolygon_ML1” or “Index_per_IPCPolygon_ML2”. The numbers in this column have to be smaller than in the “district” column.

The video shows the whole process with the the example of ML 1.

```{dropdown} Video: Calculation of Population Proportion per Intersection Polygon
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_TRigger_step_8_field_calculator.mp4"></video>
```

## Step 9: Calculate the IPC Index per District <a id="step-9-calculate-the-ipc-index-per-district"></a>
```{figure} ../../../fig/Drought_EAP_Worklow_Step_9_1.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__  The purpose of this step is to calculate a population weighted mean over the IPC classes that fall within a district, in order to give the amount of people living in a certain IPC class more importance than just the area affected by a certain IPC class. The result is a IPC Index value for each district.

__Tool:__ `Join attribute by location (summary)`

``````{list-table}
:header-rows: 1
:widths: 20 25

* - Instruction
  - Join attribute by location (summary)
* - 1. In the `Toolbox`-> Search for `Join attribute by location (summary)`
      * Tip: If the `Toolbox` is not opne click `Processing`-> `Toolbox` 
    2. `Input Layer`: Select your “district_pop_som” layer
    3. `Input Layer 2`: Select “ML1_join” (or ML2_Join”)
    4. `Geometric predicate`: Select “Intersection”
    5. `Field to summarise`: Select “Index_per_IPCPolygon_ML1” (or “Index_per_IPCPolygon_ML2” )
    6. `Summaries to calculate`: Chose only the option “mean”
    7. Under `Join Layer` click on the three points ![](../../../fig/Three_points.png)-> `Save to File` and navigate to you monitoring folder [Year_Month]. Give the output the name "ML1_join_location" or "ML2_join_location" and click `Save`
    8. Click `Run`
  -
    ```{figure} ../../../fig/SRCS_Trigger_step_9_join_location.png
    ---
    width: 450px
    name: 
    align: center
    ---
    ```
``````

__Result:__ As a result, your two layers "ML1_join_location" and "ML2_join_location" should have the column “Index_per_IPCPolygon_ML1_mean” or “Index_per_IPCPolygon_ML2_mean”. Furthermore, the number of rows should be the exact number of districts in Somalia and the polygons should have the exact shape of the districts.

```{dropdown} Video: Calculate IPC Index per District
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_Trigger_step_9_join_location.mp4"></video>
```


## Step 10.: Join ML1 and ML2 <a id="step-10-join-ml1-and-ml2"></a>
```{figure} ../../../fig/Drought_EAP_Worklow_Step_10_1.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__ The purpose of this step is to merge “ML1_join_location" and "ML2_join_location” into one layer so we have the IPC-Index for all districts.

__Tool:__ [`Join attributes by field value`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_non_spatial_joins_wiki.html#join-attributes-by-field-value)

``````{list-table}
:header-rows: 1
:widths: 20 25

* - Instruction
  - Join attribute by location (summary)
* - 1. In the `Toolbox`-> Search for [`Join attributes by field value`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_non_spatial_joins_wiki.html#join-attributes-by-field-value)
    * Tip: If the `Toolbox` is not opne click `Processing`-> `Toolbox` 
    2. `Input Layer`: Select your "ML1_join_location" layer 
    3. `Table field`: Select “admin2Name”
    4. `Input Layer 2`: Select your "ML2_join_location" layer 
    5. `Table field 2`: Select “admin2Name”
    6. `Layer 2 field to copy`: Click on the three points and  select “Index_per_IPCPolygon_ML2_mean”
    7. `Join type`: Select the option “Take attributes of the first matching feature only (one-to-one)
    8. Under `Join Layer` click on the three points ![](../../../fig/Three_points.png)-> `Save to File` and navigate to you monitoring folder [Year_Month]. Give the output the name "IPC_index_district" and click `Save`
    9. Click `Run`
  -
    ```{figure} ../../../fig/SRCS_Trigger_step_10_IPC_Index_district.png
    ---
    width: 450px
    name: 
    align: center
    ---
    ```
``````

__Result:__ Layer with the districts of Somalia and the IPC-Index of each district.

```{dropdown} Video: Join ML1 and ML2 I
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_Trigger_step_10_join.mp4"></video>
```

## Step 11: Calculation of SPI-12 Mean per District <a id="step-11-calculation-of-spi-12-mean-per-district"></a>
```{figure} ../../../fig/Drought_EAP_Worklow_Step_11_1.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__ Calculate the mean value over the SPI-12 values of all pixels that fall within a scertain districts area, in order to have one SPI-12 value for each district.

__Tool:__ [`Zonal Statistics`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_raster_basic_wiki.html#zonal-statistics)

``````{list-table}
:header-rows: 1
:widths: 20 25

* - Instruction
  - Zonal Statistics
* - 1. In the `Toolbox` -> Search for [`Zonal Statistics`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_raster_basic_wiki.html#zonal-statistics)
    * Tip: If the `Toolbox` is not open click `Processing`-> `Toolbox`
    2. `Input Layer`: district_pop_som
    3. `Raster Layer`: SPI Forecast
    4. `Output column prefix`: Use  "SPI12_"
    5. `Statistics to calculate`: “Mean”
    6.  Under `Zonal Statistics` click on the three points ![](../../../fig/Three_points.png)-> `Save to File` and navigate to you monitoring folder [Year_Month]. Give the output the name "SPI12_district" and click `Save`
    5. Click `Run``
  -
    ```{figure} ../../../fig/SRCS_Trigger_step_11_IPC_zonal_district.png
    ---
    width: 450px
    name: 
    align: center
    ---
    ```
``````

__Result:__ A layer of all districts of Somalia with the mean SPI-12.


```{dropdown} Video: Calculation of SPI12 Mean per District
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_Trigger_step_11_zonal_staistics.mp4"></video>
```

## Step 12: Join SPI-12 Mean to the IPC Index <a id="step-12-join-spi-12-mean-to-the-ipc-index"></a>
```{figure} ../../../fig/Drought_EAP_Worklow_Step_12_1.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__ The purpose of this step is to merge data from two different data sources into one data frame so that it can be jointly analysed.

__Tool:__[`Join attributes by field value`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_non_spatial_joins_wiki.html#join-attributes-by-field-value)

``````{list-table}
:header-rows: 1
:widths: 20 25

* - Instruction
  - Join attributes by field value
* - 1.  In the `Toolbox`-> Search for [`Join attributes by field value`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_non_spatial_joins_wiki.html#join-attributes-by-field-value)
      * Tip: If the `Toolbox` is not opne click `Processing`-> `Toolbox`
    2. `Input Layer`: Select your “IPC_index_district”
    3. `Table field`: Select “admin2Name”
    4. `Input Layer 2`: Select your “SPI12_district”
    5. `Table field 2`: Select “admin2Name”
    6. `Join type`: Select the option “Take attributes of the first matching feature only (one-to-one)"
    7. Under `Join Layer` click on the three points ![](../../../fig/Three_points.png)-> `Save to File` and navigate to you monitoring folder [Year_Month]. Give the output the name "IPC_index_SPI_12_district" and click `Save`
    8. Click `Run`
  -
    ```{figure} ../../../fig/SRCS_Trigger_step_12_IPC_SPI12_join.png
    ---
    width: 450px
    name: 
    align: center
    ---
    ```
``````

__Result:__ The result will be a layer of all districts of Somalia with the mean SPI-12 and the IPC-Index of each district.


```{dropdown} Video: Join SPI12 Mean to the IPC Index
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_Trigger_step_12_join_IPC_SPI12.mp4"></video>
```

## Step 13: Evaluate the Trigger Activation <a id="step-13-evaluate-the-trigger-activation"></a>
```{figure} ../../../fig/Drought_EAP_Worklow_Step_13_1.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__ The purpose of this step is to gain a quick overview of possible trigger activation without having to revise the actual data. Instead we will have a binary column with trigger = yes or trigger=no values.

__Tool:__ [`Field Calculator`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_table_functions_wiki.html#calculate-field)



1. Right-click on "IPC_index_SPI_12_district" layer -> `Attribute Table`-> click on  [`Field Calculator`](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_table_functions_wiki.html#calculate-field) ![](../../../fig/mActionCalculateField.png) to open the field calculator
2. Check `Create new field`
3. `Output field name`: Name the new column “Trigger_activation”
4. `Result field type`: Text (string)
5. Add the code below into the `Expression` field
``````{list-table}
:header-rows: 1
:widths: 15

* - Code
* - ```md
    CASE

    WHEN "Index_per_IPCPolygon_ML1_mean" >0.7 AND "Index_per_IPCPolygon_ML2_mean" > 0.7
    AND
    "SPI12_mean" < -1
    THEN 'yes'
    ELSE 'no'

    END
    ```
``````
6. Click `ok`
7. Save the new column by clicking on ![](../../../fig/mActionSaveEdits.png) in the attribute table and end the editing mode by clicking on ![](../../../fig/mActionToggleEditing.png)

__Result:__ A layer with all districts of Somalia with a column of "Yes" and "No" values indicating whether the trigger levels have been reached or not.

```{figure} ../../../fig/SRCS_Trigger_step_13_trigger_evaluation.png
---
width: 500px
name: 
align: center
---
```

```{dropdown} Video: Evaluate Trigger Activation 
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_Trigger_step_13_trigger_activation.mp4"></video>
```

## Step 14: Visualisation of results <a id="step-14-visualisation-of-results"></a>
```{figure} ../../../fig/Drought_EAP_Worklow_Step_14_1.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__ Definition of how features are represented visually on the map.

__Tool:__ [Symbology](https://giscience.github.io/gis-training-resource-center/english/content/en/Module_4/en_qgis_map_design_I.html#symbology-for-vector-data)

__Trigger Activation__

1. Right cklick on the “Trigger_activation” layer -> `Properties` -> `Symbology`
2. In the down left corner click on `Style` -> `Load Style`
3. In the new window click on the three points ![](../../../fig/Three_points.png). Navigate to the “FbF_Drought_Monitoring_Trigger/layer_styles” folder and select the file __“Style_Trigger_Activation.qml”__.
4. Click `Open`. Then click on `Load Style`
5. Back in the “Layer Properties” Window click `Apply` and `OK`

```{dropdown} Info: Trigger Activation Layer
You will now see districts where no trigger is activated in green and districts with trigger activation in pink.

The “Style_Trigger_Activation.qml” style layer is configured to show the district names only where the trigger is actually activated. If there is no trigger activation you can activate the admin 1 boundary layer for better map orientation (see __Administrative 2 Boundaries__ below)

```{figure} ../../../fig/Map_yes_trigger.PNG
---
width: 1000px
name: 
align: center
---
```

__Risk Assessment__


7. Right click on the "risk_assessment_districts" layer -> `Properties` -> `Symbology`
8. In the down left corner click on `Style` -> `Load Style`
9. In the new window click on the three points ![](../../../fig/Three_points.png). Navigate to the “FbF_Drought_Monitoring_Trigger/layer_styles” folder and select the file __“somalia_risk_assessment_style.qml”__ style layer.
10. Move the "risk_assessment_district" layer __below__ "Trigger_Activation" layer ([Layer Concept](https://giscience.github.io/gis-training-resource-center/english/content/en/Module_2/en_qgis_geodata_concept.html?highlight=layer#layer-concept)).
11. Back in the “Layer Properties” Window click `Apply` and `OK`


```{dropdown} Info: Risk Assessment Layer
For the creation of an __Intervention Map__ we will have to add the risk assessment data and the respective style file.
For this first of all load from "FbF_Drought_Monitoring_Trigger/Fixed_data/Risk_Assessment" the file "risk_assessment_districts.gpkg". This file is the output of the conducted risk assessment and contains a risk value for each district of Simaliland and Somalia.  In order to visualize it 
```

__Administrative 2 Boundaries (Regions)__

12. Right click on the "Som_Admbnda_Adm1_UNDP" (Regiond) layer -> `Properties` -> `Symbology`
13. In the lower right corner click on `Style` -> `Load Style`
14. In the new window, click on the three points ![](../../../fig/Three_points.png). Navigate to the “FbF_Drought_Monitoring_Trigger/layer_styles” folder and select the file __“somalia_risk_assessment_style.qml”__.
15. Click `Open`. Then click on `Load Style` 
16. Back in the “Layer Properties” Window click `Apply` and `OK`
17. Add a the OpenStreetMap basemap by clicking on `Layer` -> `Add Layer` -> `Add XYZ layer...` -> Select the OpenStreetMap. Click `Add`. ([Wiki basemap](https://giscience.github.io/gis-training-resource-center/english/content/en/Wiki/en_qgis_basemaps_wiki.html?highlight=osm#basemaps))
18. Place the OpenStreetMap basemap on the bottom.
19. Delet all layers exept:
    * Trigger_activation
    * risk_assessment_districts
    * Som_Admbnda_Adm1_UNDP
    * OpenStreetMap

```{dropdown} Video: Visualisation of results
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/Trigger_model_style.mp4"></video>
```

``````{list-table}
:header-rows: 1
:widths: 20 20

* - Intervention Map __without__ Trigger activation
  - Intervention Map __with__ Trigger activation
* - 
    ```{figure} ../../../fig/Map_no_trigger.PNG
    ---
    width: 1000px
    name: 
    align: center
    ---
    ```
    
  -
    ```{figure} ../../../fig/Map_yes_trigger.PNG
    ---
    width: 450px
    name: 
    align: center
    ---
    ```
``````

```{Attention}
Remember the [layer concept](https://giscience.github.io/gis-training-resource-center/english/content/en/Module_2/en_qgis_geodata_concept.html?highlight=layer#layer-concept) and make sure the basemap layer is at the bottom of your layers panel.
```



## Step 15: Making the print map <a id="step-15-making-the-print-map"></a>

```{figure} ../../../fig/Drought_EAP_Worklow_Step_15_1.png
---
width: 1000px
name: 
align: center
---
```
__Purpose:__ Viualization of the map features in a printable map layout

__Tool:__  [Print Layout](https://giscience.github.io/gis-training-resource-center/english/content/en/Module_4/en_qgis_map_design_2.html?highlight=print+layout#print-layout)


1. If not done before, delet all layers expect __Trigger_activation__, __risk_assessment_districts__ and __OpenStreetMap__
2. Open a new print layout by clicking on `Project` -> `New Print Layout` -> enter the name of your current Project e.g "2022_04".
3. Go the the __FbF_Drought_Monitoring_Trigger__` folder and drag and drop the file `Trigger_activation_Intervention_map.qpt` in the print layout
4. Change the date to the current date by clicking on "Further map info…" in the items panel. Click on the `Item Properties` tab and scroll down. Here you can change the date in the `Main Properties` field.
5. Adjust the Lgend by clicking on the legend in the  `Item Properties` tab and scroll down until you see the `Legend items` field. If it is not there check if you have to open the dropdown. Make sure `Auto update` is not checked.
    * Remove all itemes in the legend be clicking on the item and then on the red minus icon below.
    * Add __Trigger_activation__ and __risk_assessment_districts__ to the legend by clicking on the green plus and click on the layer and click `ok`
 

```{dropdown} Video: Making print map
<video width="100%" controls muted src="https://github.com/GIScience/gis-training-resource-center/raw/main/fig/SRCS_Trigger_print_map.mp4"></video>
```

```{Attention}
Make sure you edit the Map Information on the template, e.g. current date. Also make sure to check the legend items: Remove unnecessary items and eventually change the names to meaning descriptions.
```


In order to easily visualize the output of the trigger analysis we provide you with a 
[map template](https://giscience.github.io/gis-training-resource-center/english/content/en/Module_4/en_qgis_map_design_2.html#map-templates) that can be used as a base for your visualization. You can find the template in the following directory: ".../FbF_Drought_Monitoring_Trigger/maps_somalia_template_risk_assessment.qpt".

You can also adapt the template to your needs and preferences. You can find help [here](https://giscience.github.io/gis-training-resource-center/english/content/en/Module_4/en_qgis_map_design_2.html#print-layout).

```{Attention}
Make sure you edit the Map Information on the template, e.g. current date. Also make sure to check the legend items: Remove unnecessary items and eventually change the names to meaning descriptions.
```

## Step 16: Exporting the Map <a id="step-16-exporting-the-map"></a>


```{figure} ../../../fig/Drought_EAP_Worklow_Step_16_1.png
---
width: 1000px
name: 
align: center
---
```

__Purpose:__ Export the designed and finalized map layout in order tp print it as a pdf or format of your choice.


__Tool:__ [Print Layout](https://giscience.github.io/gis-training-resource-center/english/content/en/Module_4/en_qgis_map_design_2.html?highlight=print+layout#print-layout)

When you have finished the design of you map you can export it as pdf or image file in different datafromats.

__Export as Image__

1. In the print layout click on `Layer` -> `Export as Image`
2. Chose the __Result__ folder in the folder you have created in step 1. Give the file the name of the project e.g 2022_04
3.  Click on `Save`
4. The window "Image Export Options" will appear. 
5. Click `Save`.

Now the image can be found in the result folder in the folder you created in Step 1


__Export as PDF__

1. In the print layout click on `Layer` -> `Export as PDF`
2. Chose the __Result__ folder in the folder you have created in step 1. Give the file the name of the project e.g 2022_04
3.  Click on `Save`
4. The window "PDF Export Options" will appear.  For the best results, select the `lossless` image compression.
5. Click `Save`.

Now the image can be found in the result folder in the folder you created in Step 1.


```{figure} ../../../fig/map_output_example2.png
---
width: 1000px
name: 
align: center
---
```

::::::