Job title: Water Resources Analysis
Work Location: Germany/Online
Department: Remote sensing, Computer Science, Earth Sciences
Work load: 20 Hours / Week
Job Type: Bachelor Thesis / Internship
Water Storage changes derived from mass anomalies (GRACE) in the period between 2016 and 2019 data example (in Egypt)
General Description:
In the frame of prototyping a Remote sensing solution that can process, analyze and interpret satellite data using different statistical methods (see images). In order to understand, monitor and predict changes in water resources, data from different satellite missions and also the NASA Land Data Assimilation System (LDAS) needs to be assessed, analyzed, and combined. The analysis of water resources and the long-term trend in all regions of the Earth is important to understand the impact of climate change. Private households, agriculture but also other industries are strongly dependent on a stable supply of water.
That’s why we are motivated to use remote sensing data to analyze the change of deepwater storage (GRACE mission) and also effects on soil moisture (SMOS) and develop regional water resource models. On one hand, based on these data predictions for the future can be made to support agricultural planning. On the other hand, effects projects like Sahara Green Wall can be monitored in order to consult and lead such projects to success.
The two libraries ggtools and pytesmo have different options for analysis of remote sensed data and are part of the Nabta Playa Environment. Functionalities shall be applicable on remote sensed data provided by up42 and eo_learn databases depending on user defined requests. The derived analysis data shall be provided incomprehensible graphs and netCDF format. In a second step, season filtering and linear regression can be used to predict trends.
Essential Duties and Responsibilities:
Implement different functions of pytesmo and ggtools libraries into the Nabta Playa workflow
Automatization of analyzing, formatting and presenting data
Education and/or Work Experience Requirements:
Bachelor in computer science, remote sensing or related disciplines
Very good knowledge of Python
Very good knowledge of Image Processing
Very good knowledge of Linux
Good knowledge of Cloud Technology
Very good verbal and written communication skills in English
Ability to work independently and to carry out assignments to completion within parameters of instructions given, prescribed routines, and standard accepted practices
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