fix: typo in badge

README.md

@@ -1,19 +1,20 @@
-![](https://img.shields.io/badge/Build%20with%20%E2%9D%A4%EF%B8%8F-at%20Technologiesitftung%20Berlin-blue)
+![](https://img.shields.io/badge/Built%20with%20%E2%9D%A4%EF%B8%8F-at%20Technologiestiftung%20Berlin-blue)
 
-# Gieß den Kiez Tree data 
+# Gieß den Kiez Tree data
 
-*This is a script to harvest tree data from a Web Feature Service from Berlins Geodata Portal and integrate it to our Gieß-den-Kiez-database.*
+_This is a script to harvest tree data from a Web Feature Service from Berlins Geodata Portal and integrate it to our Gieß-den-Kiez-database._
 
 In the application [Gieß-den-Kiez.de](https://giessdenkiez.de), Berlin's street trees are displayed on a map. The data about the trees comes from Berlin's street and green space offices and is made available as open data via Berlin's Geodata portal, the [FIS-Broker](https://fbinter.stadt-berlin.de/fb/index.jsp). The underlying database, the green space information system (GRIS), is continuously maintained by the administration: Trees not yet recorded and newly planted trees are entered and felled trees are deleted. The data set is then updated in the Geodata portal once a year, always in spring. In order to reflect the current status, the data in Gieß den Kiez is therefore also updated once a year when the new [tree dataset](https://fbinter.stadt-berlin.de/fb/index.jsp?loginkey=zoomStart&mapId=k_wfs_baumbestand@senstadt&bbox=389138,5819243,390887,5820322) is published.
 
 We use these Python scripts to automate this. Using the script `get_data_from_wfs.py`, the data can be downloaded from the FIS-Broker in GeoJSON format and saved locally. Using `main.py` we connect to our Gieß-den-Kiez database and the data is then compared with the existing tree data of the database using their GML-IDs (also called technical IDs in the FIS-Broker). In this way, deleted and added trees are identified and removed or added from the database. All matching trees are also identified and updated for the columns specified in `config.yml`.
 
 ![tree_data_schema](https://user-images.githubusercontent.com/61182572/124777121-44cb3080-df40-11eb-9e49-4cccad77b821.png)
 
-## Inputs 
+## Inputs
 
 - New tree data in GML or GeoJSON format
 - config.yaml that configurates paths, tablesnames, overwritting, mapping of column names and columns to update
+
 ```yml
 database:
   parameter-path: .env
@@ -48,7 +49,9 @@ data-schema:
     - gattung
     - pflanzjahr
 ```
+
 - .env that contains database credentials
+
 ```yml
 PG_SERVER=
 PG_PORT=
@@ -60,10 +63,13 @@ PG_DB=
 ## Example Usage
 
 To save newest tree data from the FIS-Broker locally run
+
 ```bash
 python tree_data/get_data_from_wfs.py
 ```
+
 To update database run
+
 ```bash
 python tree_data/main.py
 ```
@@ -74,7 +80,7 @@ In Gieß den Kiez it is visible which trees are maintained by Berlin's street an
 
 1. Extract only the FIS-Broker-ID'S (gmlids) from the Excel sheet to a csv file
 2. Create a new table with this ID's in the database: `CREATE TABLE caretaker_ids(id VARCHAR NOT NULL)`
-3. Import ID’s from CSV-Table into the database table 
+3. Import ID’s from CSV-Table into the database table
 4. Delete old caretaker labels from the trees table: `UPDATE trees SET caretaker = NULL`
 5. JOIN new caretaker labels to the trees: `UPDATE trees t SET caretaker = 'Bezirk XY' FROM caretaker_ids c WHERE t.gmlid = c.id`
 6. Delete the no longer needed table: `DROP TABLE caretaker_ids`