Workshop with Ellen and Charles, two scientists from Makerere University Kampala, Uganda, together with Clein and Rolf from HSRW
Material for HSRW divided in possible lecture days:
Introduction to Geodata. Spatio-temporal data. First approach to python (getting familiar with Notebooks and downloading the material). Installing all the dependencies. (could be replaced by JupyterHub)
DWD_NRW: Using python to download data. Using the ftp server. Using os.makedirs. Data wrangling (“working with data in other languages”). Saving csv data. Importing csv data into QGIS. Import vector data (the admin. Boundaries). Mapping
Get started in QGIS. Baruch college tutorial. Getting started
CRS Theory, but also a practical. Using 4 different files as example for the CRS practical. Divide the data by regions or so. (maybe its more helpful if they are geographically close instead of overlaying)
Geopandas 0130: Creating a polygon layer. Scrapping data with Beatiful soup. To create the generalized polygon vector (DTMs)
WMS, WFS and WCS
Introduction to DTM (Remote Sensing) Airborne laser scanner. Gdal translate from XYZ to TIF. Import layer in QGIS Hillshade model Merging layers
Warming stripes (merging and average calculation) (python) → Change by precipitation instead To show temporal controller
Altitude Vs Temperature (python)
Georeferencing (digitizing)
Database management systems (installing Postgresql). Database Setup. Create users and databases. Create example relations. Create tables. Relational Algebra
Database normalization. Examples and 1NF, 2NF and 3NF
Groundwater Lanuv: Reading the data from Lanuv. Problem with data obfuscation. PostGIS: using geopandas. Time series. SQL
Time Series management (generating videos and co.)
Satellite imagery (NDVI and so on)
Material from Makerere University: Course GIS and Remote Sensing in Natural Resource Management
Lecture 1 introduction to RS
Lecture 2 RS
Lecture 3 Remote Sensing
Lecture 4 Photogrametry → Drones
Lecture 5 Introduction to GIS → Data acquisition, input… GIS functions
Lecture 6 If time allows DBMS. Joins primary key, foreign key…. Spatial Reference Systems (CRS)
Practicals:
Practical GIS Divided in 3 sessions. Input data, Working with CRS,
Querying by attribute and by location (Geospatial). Data Visualizations and treating different data types. Creating layers. Summarizing data from Att Table. Creating maps.
GPS own data creation. Digitize of maps
Practical Remote Sensing:
Download satellite imagery
Creating composite images (Indices)
Python → As classification toolchain?
Image classification
Accuracy assessment (how to use cancilliary data)
Change detection
Flood risk mapping.
Interpolation and suitability analysis