Session 2B: Inaugural Lectures by Fellows/Associates

N Sathyamurthy, Bengaluru

Mathematical Morphology in Geosciences and Geospatial Data Sciences

Mathematical Morphology – a robust mathematical theory that needs more attention by geoscience, remote sensing, and geospatial data science communities – is an area of geoscience that most people don’t realize will change how they look at Earth and Earth-like planets! Data available at multiple spatial/spectral/temporal scales pose numerous challenges to data scientists. Of late, researchers paid wide attention to handling such data acquired through various sensing mechanisms to address intertwined topics like patternretrieval, pattern-analysis, quantitative reasoning, and simulation and modelling to better understand spatiotemporal behaviours of several terrestrial phenomena and processes. Various spatial algorithms that are mainly based on mathematical morphology have been developed and demonstrated. This lecture that presents fundamentals of mathematical morphology and their applications in geosciences, processing and analysis of remotely sensed satellite data and Digital Elevation Models, as well as geoinformatics, would be helpful for those with research interests in geosciences and remote sensing, geographical information sciences, spatial statistics, and mapping of earth-like planetary surfaces.