At Brockmann Geomatics, I develop reproducible Python-based workflows and machine learning solutions for environmental and water analytics, contributing to international projects such as OASIS and AQUATIME that integrate Earth observation, AI, and scientific computing into decision-ready products.
Stay updated with my latest professional journey, project announcements, and insights from the world of geospatial analytics and remote sensing.
A showcase of workshops and hackathons that amplified my expertise in LiDAR, machine learning, geospatial intelligence, and entrepreneurship—focusing on real-world data challenges and interdisciplinary teamwork in forestry and environmental domains.
A showcase of hackathons that amplified my expertise in Artificial Intelligence, machine learning, geospatial intelligence, LiDAR, and entrepreneurship—focusing on real-world data challenges and interdisciplinary teamwork in forestry and environmental domains.
I’ve applied remote sensing techniques across a wide range of environmental monitoring projects, from assessing urban heat islands and mapping volcanic deformation with InSAR, to modeling forest structures using LiDAR and developing web-based applications on Google Earth Engine. My work integrates multi-sensor datasets, geospatial analytics, and field validation to produce actionable insights for climate, disaster, and land surface studies.
My work with InSAR focuses on detecting and analyzing ground displacement using radar remote sensing techniques such as DInSAR and PSInSAR. I’ve developed and implemented workflows for processing satellite SAR data, enabling accurate monitoring of subsidence, tectonic motion, and anthropogenic changes. These efforts have supported environmental and geophysical studies across varied terrains using Sentinel-1 and TerraSAR-X datasets.