Open AccessSPATIAL DATA INTERPOLATION
Author(s) -
Prof.RAE Zh Aliyev
Publication year - 2018
Publication title -
international journal of medical and biomedical studies
Language(s) - English
Resource type - Journals
eISSN - 2589-8698
pISSN - 2589-868X
DOI - 10.32553/ijmbs.v2i4.36
Subject(s) - raster graphics , multivariate interpolation , spatial analysis , raster data , spatial distribution , interpolation (computer graphics) , field (mathematics) , mathematics , scalar (mathematics) , inverse distance weighting , computer science , geometry , bilinear interpolation , statistics , artificial intelligence , motion (physics) , pure mathematics
During the study and adjustment, techniques revealed our analysis of spatial data in vector format. The latter is best suited for the spatial analysis of discrete objects. However, when the spatial variable is represented as a field of scalar or vector greatness (for example, the spatial distribution of concentrations of heavy metal concentrations in soils or groundwater movement speed field). Convenient ways to record data is bitmap format. This approach is most often used for phenomena of processes that are characterized by considerable anisotropy. However, the characteristic feature of the method of inverse distance is the fact that the interpolated value in measured point is equal to the measured value.
Key words: erosion, soil; heavy metals, extremum, spatial data, raster data anti-erosion measures