A MapReduce-Based Big Spatial Data Framework for Solving the Problem of Covering a Polygon with Orthogonal Rectangles

Abstract: The polygon covering problem is an important class of problems in the area of computational geometry. There are slightly different versions of this problem depending on the types of polygons to be addressed. In this paper, we focus on finding an answer to a question of whether an orthogonal rectangle, or spatial query window, … Read more

Kd-tree and quad-tree decompositions for declustering of 2D range queries over uncertain space

Abstract: We present a study to show the possibility of using two well-known space partitioning and indexing techniques, kd trees and quad trees, in declustering applications to increase input/output (I/O) parallelization and reduce spatial data processing times. This parallelization enables time-consuming computational geometry algorithms to be applied efficiently to big spatial data rendering and querying. … Read more