Anita Chandrasekharan

I’m a Remote Sensing and GIS Engineer with over eight years of experience in Earth Observation, satellite image processing, spatial analytics, and environmental modelling. I translate complex spatial data into actionable insights, with a strong focus on building repeatable geospatial workflows that stand up to real-world project timelines.

Across my work, I develop geospatial workflows using Python, Google Earth Engine, ArcGIS Pro, QGIS, ENVI, and multi-source satellite datasets including Sentinel, Landsat, ASTER, and MODIS. My technical strengths span spatial data processing, land use and land cover analysis, change detection, terrain analysis, and geospatial decision support—built on both rigorous analysis and clean documentation.

Now, I’m advancing expertise in GeoAI, machine learning, and AI-assisted Earth Observation through practical projects involving satellite image classification, time-series analysis, environmental monitoring, and predictive geospatial analytics. I’ve worked with model validation and spatial prediction approaches such as Random Forest classification and Artificial Neural Networks.

Before consulting, I also supported learning and applied geospatial workflows as a Teaching Assistant for GIS, Remote Sensing, Photogrammetry, and Surveying, and I’ve contributed to research through my Ph.D. in Remote Sensing and GIS. I bring a multidisciplinary, collaboration-first approach—partnering with researchers, engineers, and teams to deliver high-quality analytical outputs.