  We propose a framework stitching of vector representations of large scale
raster mosaic images in distributed computing model. In this way, the negative
effect of the lack of resources of the central system and scalability problem
can be eliminated. The product obtained by this study can be used in
applications requiring spatial and temporal analysis on big satellite map
images. This study also shows that big data frameworks are not only used in
applications of text-based data mining and machine learning algorithms, but
also used in applications of algorithms in image processing. The effectiveness
of the product realized with this project is also going to be proven by
scalability and performance tests performed on real world LandSat-8 satellite
images.
