Patrick Sogno

Patrick Sogno
German Aerospace Center (DLR) | DLR · German Remote Sensing Data Center (DFD)

Master of Science


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Interested in Earth Observation, especially for the research of non-communicable diseases. Mostly focused on satellite remote sensing and GIS. R enthusiast.
October 2018 - March 2021
University of Wuerzburg
Field of study
  • Applied Earth Observation and Geoanalysis of the Living Environment
October 2014 - August 2018
Universität Heidelberg
Field of study
  • Geography & South Asian Studies


Publications (4)
Conference Paper
The goal of this research was to explore whether ecological niche modelling (ENM) and a habitat suitability index (HSI) model can be combined to refine results for actual breeding areas of three different locust pests. With the application of ENM as part of HSI, the information value based on climatic and soil preference components defining locust...
Full-text available
Inland surface water is often the most accessible freshwater source. As opposed to groundwater, surface water is replenished in a comparatively quick cycle, which makes this vital resource—if not overexploited—sustainable. From a global perspective, freshwater is plentiful. Still, depending on the region, surface water availability is severely limi...
Non-communicable diseases – NCDs – (asthma, cancer, or diabetes, for example) are a major concern for modern medicine. According to the World Health Organization, NCDs are responsible for over 70% of global premature deaths. Apart from the mortality directly related to these chronic diseases, they constantly strain the individual’s immune system, i...
Full-text available
A disease is non-communicable when it is not transferred from one person to another. Typical examples include all types of cancer, diabetes, stroke, or allergies, as well as mental diseases. Non-communicable diseases have at least two things in common—environmental impact and chronicity. These diseases are often associated with reduced quality of l...


Cited By


Project (1)
The primary goals are: (1) develop a multi-observation ensemble-based calibration and data assimilation (C/DA) methodology to combine observational data of model output variables (time series of gauge-based streamflow, GRACE/GRACE-FO total water storage variations, remotely-sensed extent and level of surface water bodies, snow cover, glacier mass change and streamflow) with hydrological models in an optimal manner. (2) exploit this methodology with the global hydrological model WaterGAP to provide an improved quantitative assessment of freshwater fluxes and storages including their uncertainties in response to climate and anthropogenic forcing. To reach these goals, nine partners work together, collaborating with two Mercator fellows. The Goethe University Frankfurt and the University of Bonn coordinate the project.