| Kurzkommentar |
The aim of this module is to learn and apply new concepts and methods of Applied Geoinformation Science. Basic knowledge in GIS and statistics is expected (e.g. similar to M5 in MA Human Geography or M1 in MSc Global Change Geography). In this course, methods of data assessment (survey, walking interviews), analysis (statistical, spatial, scenario-development), and visualization (web-based, critical cartography) are introduced first, then applied using hands-on examples and critically reflected. We will mainly use QGIS and Python(including an introduction to Python) in this course. We will apply research-focused teaching in this course and will closely aline the content of the course with ongoing research in the lab (e.g. invite external speakers, use research data). All students who want to explore the benefits and challenges of Applied Geoinformation Science techniques are very welcome. |
| Kommentar |
The growing global population together with climate change puts pressure on food systems and affects food security. Earth Observation can provide essential information that can help different stakeholders (e.g., farmers, decision makers) to maximize productivity and food security.
In this module students will acquire theoretical and practical knowledge on state of the art Earth Observation data and tools for agricultural monitoring. The seminar will cover several topics varying from crop mapping to crop condition and management assessment in areas with different agro climatic conditions (e.g., Germany, Sub-Saharan Africa, USA). For this purpose, data from different sources will be tested, such as MODIS, Landsat, Sentinel-1, Sentinel-2. Appropriate theoretical knowledge on suitable methods and relevant datasets will be developed in the seminar and then implemented during practical sessions. During the practical sessions, students will gain firsthand experience in the R programming language and Google Earth Engine (using Javascript) for solving different real life issues with the use of multisource data.
The topics will include (but not limited to):
- Global agricultural monitoring: data, tools, information needs and current status
- Monitoring of crop growth with Sentinel -1 and Sentinel-2
- Crop Evapotranspiration, Water Use, and Irrigation assessment
- Drought impact assessment
- Remote Sensing and crop yield assessment
This module will successfully finish with a term paper and a presentation prepared in a group with a focus on one particular method or application related to the case studies.
Knowledge of the basic concepts of remote sensing, as well as basic programming experience are prerequisites for participating in this module. |
| Literatur |
Delince, J., Lemoine, G., Defourny, P., Gallego, J., Davidson, A., Ray, S., ... & Achard, F. (2017). Handbook on remote sensing for agricultural statistics. GSARS: Rome, Italy.
https://www.fao.org/3/ca6394en/ca6394en.pdf
Paganini et al. (2018): Satellite earth observations in support of the Sustainable Development Goals. http://eohandbook.com/sdg/
Weiss, M., Jacob, F., & Duveiller, G. (2020). Remote sensing for agricultural applications: A meta-review. Remote Sensing of Environment, 236, 111402.
Special Issue „Remote Sensing in Food Production and Food Security“ in Remote Sensing (http://www.mdpi.com/journal/remotesensing/special_issues/rs_food_production_security) |
