Deep-Learning-analysis-of-satellite-images

Studienprojekt Satellitenbilder

Participants:

• Professor Dr. Sebastian Fischer
• Oskar Thaute
• Minh Hai Nguyen (s_nguyenmi21@stud.hwr-berlin.de) -> Bei Fragen
• Laurin Pausch

Protocolling: Laurin Pausch, 13.01.23 12.00 pm - 12.50 pm

Initial meeting

Topics introduced and discussed:

• the goal of this project
• context of the projects part in a bigger research project
• what tools to use
• Workflow and meeting schedule

Goal of this Project:

We are developing a satellite imagery analysis application that allows users to specify a region of interest and receive an analysis of the percentage of privately-owned yards within that region. This prototype will demonstrate the feasibility of the concept and the potential of the technology.

Context of the Project:

The motivation behind our project is to support detecting potential for optimization of privately-owned yards in Germany as a means of combating climate change. We will try to identify areas where there is potential to make privately-owned yards more sustainable. By creating a data basis for choice modeling and utilizing deep learning techniques, we hope to support a research project that will potentially inform and shape political decision-making and sustainability policies in the future.

Which Tools will be used:

There is no limitation or specification for which Tools should be used. The only specification at this time is the computer language of python.

https://www.python.org

Workflow and meeting schedule

The next meeting is set at the 23.01.23, 1 pm via Teamsmeeting The following meetings and updates to the project will be set on demand. Follow us on our Git-Hub Repository https://github.com/LaurinX/Deep-Learning-analysis-of-satellite-images for our latest updates