Applications of Robust Methods in Spatial Analysis

Spatial data analysis provides valuable information to the government as well companies. The rapid improvement of modern technology with a geographic system (GIS) can lead collection and storage more spatial data. We developed algorithms choose optimal locations from those permanently in space for an efficient analysis. Distances between neighboring permanent are not necessary be equispaced distances. Robust sequential methods were used develop design construction. constructed designs robust against misspecified regression responses variance/covariance structures responses. proposed method extended future works image which includes 3 dimensional