HASM-AD algorithm based on the sequential least squares

Abstract

The HASM (high accuracy surface modeling) technique is based on the fundamental theory of surfaces, which has been proved to improve the interpolation accuracy in surface fitting. However, the integral iterative solution in previous studies resulted in high temporal complexity in computation and huge memory usage so that it became difficult to put the technique into application, especially for large-scale datasets. In the study, an innovative model (HASM-AD) is developed according to the sequential least squares on the basis of data adjustment theory. Sequential division is adopted in the technique, so that linear equations can be divided into groups to be processed in sequence with the temporal complexity reduced greatly in computation. The experiment indicates that the HASM-AD technique surpasses the traditional spatial interpolation methods in accuracy. Also, the cross-validation result proves the same conclusion for the spatial interpolation of soil PH property with the data sampled in Jiangxi province. Moreover, it is demonstrated in the study that the HASM-AD technique significantly reduces the computational complexity and lessens memory usage in computation. © 2010 Wuhan University and Springer-Verlag Berlin Heidelberg.