Cloud based Machine learning algorithms on archived satellite/raster Imagery datasets

The proposed research work will be a breakthrough in the emerging data engineering field, especially in satellite data management, Machine learning algorithms, quality and quantitative analytics. The machine learning platform quickly scans vast archives of satellite images and delivers usable insights to decision makers.

Developing a web server system to process Multispectral raster to extract NDVI data

This research is focused on building a web-based system for processing big earth data available in a form of Raw multispectral imagery captured by a UAV or a satellites system. The data gathered will be processed to obtain the end results in a vegetation indices (Vis), or NDVI form, which could be used for crop monitoring. The efforts are required in developing a web server, which will allow inexperienced users to classify raster imagery without any supervision.