A new clustering algorithm called DGCA combines grid and density methods to improve efficiency and quality. It divides data space into grids, stores data in grid cells, uses DBSCAN for clustering, merges clusters, removes noise points, and maps local results to global ones. Tests with artificial data show that DGCA is faster and produces better clusters.