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Direct contact
  •  michael@jendryke.de (pgp)
  •  michael.jendryke
  •  +86 150 7116 7347
  •  1817149601
About

I am a geospatial data scientist and engineer deriving actionable insights from big spatial data. In my approach, I combine a Discrete Global Grid System to organize, merge, analyze and visualize large spatial datasets at multiple scales and Artificial Neural Networks (ANN) to crunch through the data to make predictions. A data platform such as a DGGS and machine learning algorithms like ANNs help to produce insights from big earth observation data, location-based services (LBS), internet of things (IoT), volunteered geographic information (VGI) from citizens, and other sensors. 

I studied Geography and Geomatics at Ruhr-University Bochum in Germany and joined the UN Operational Satellite Applications Program (UNOSAT) of the United Nations Institute for Training and Research (UNITAR) in Geneva, Switzerland in 2009. I worked there for about 1.5 years before moving to the State Key Laboratory for Information Engineering in Surveying Mapping and Remote Sensing (LIESMARS) at Wuhan University, China, to pursue my doctoral degree in engineering in photogrammetry and remote sensing, where I currently work as a Postdoc. In 2013/2014 I did a contract engagement at the Global Polio Eradication Initiative at the World Health Organization in Geneva, which set the frame for my future research interests.

Research

My goal is to create an intelligent earth that knows what is where, what was there before, and what might be there in the future.  In a holistic approach I combine multiple data sources in a Discrete Global Grid System (DGGS). This structures and harmonizes data from various sources such as satellite imagery, social media, census, or any data that has a spatial reference into hexagonal cells of almost equal size. As different phenomena have different effects at different scales multi-scale capabilities are needed. 

Each cell in the grid has a unique ID. Stored in a relational database system RDBMS such as PostgreSQL + PostGIS, Accumolo + GeoMESA this framework quickly becomes a powerful tool for big geospatial data managment and analysis. 

Figure 1: Discrete Global Grid System, resolution 9 (196,832 cells) showing NASA's Blue Marble image.

Curriculum Vitae

Download my CV  here