Joint internship The Netherlands Red Cross 510 & VanderSat
Testing high resolution satellite data in real Forecast Based Financing flood pilots
Within this internship you will work for two inspiring organizations that wish to improve the impact of satellite based water data within real development projects
VanderSat is a commercial satellite data company that is specialized in high resolution surface soil moisture based on a patented microwave technology. We deliver water and temperature data, every day, for the entire world – without disturbance of clouds. Our aim is to maximize the positive impact of this data by joining forces with NGOs such as Red Cross.
510 is an initiative of the Netherlands Red Cross. We aim to positively impact faster & more (cost) effective humanitarian aid by smart use of (big) data. We wish to shape the future of humanitarian aid by converting data into understanding, and put it in the hands of humanitarian relief workers, decision makers and people affected, so that they can better prepare for and cope with disasters and crises.
Within this project you will be working as a Remote Sensing analyst in order to test VanderSat Soil Moisture (SM) within a flood pilot for the Red Cross Forecast Based Financing (FbF) flood program. Your project will be the essential first step towards setting up a global flood alert system for NGOs – based on VanderSat SM and historical runoff data. It can significantly contribute to the decision making process of Red Cross within the FbF program.
The test will be executed by two internship tracks:
- Internship 1: Inundation mapping historical floods from passive microwave and optical data.
- Internship 2: Investigate relationship soil moisture and runoff. Generate long time series of runoff.
Requirements & skills:
- strong communication skills
- able to work independently
- interested in activities of development organizations
- wish to be part of solving water problems
- good programming skills, experience with Python
- experience with remote sensing data
- basic statistics knowledge, expertise on statistical machine learning is a plus
- willing to work for two organisations on two locations
Shift & primary locations:
- VanderSat Haarlem
- Red Cross 510 Den Haag
- Full time
For more information please contact Celine Nobel or submit your application letter and resume to email@example.com