Review of Spatial Interpolation Methods for Environmental Data

A review paper from Geoscience Australia compares 62 spatial interpolation methods across 51 comparative studies in environmental sciences. It quantifies the impact of factors like sample density and data variation using 77 cases and classifies 26 methods based on their features. The document, last updated in 2026, includes a decision tree for method selection and a list of software packages.

Use Cases

• Selecting an appropriate interpolation method based on data availability and nature using the provided decision tree.
• Comparing the performance of non-geostatistical, geostatistical, and combined interpolation methods for environmental variables.
• Assessing the impact of sampling design, data quality, and sample density on interpolation accuracy using quantified results from 77 cases.
• Conducting cluster analysis to understand similarities among 26 classified spatial interpolation methods.

Strengths

• Summarizes findings from 51 comparative studies on interpolation method performance.
• Compares the performance of 62 distinct methods and sub-methods.
• Quantifies impacts of key factors using data from 77 separate cases.
• Provides a structured classification and decision tree for 26 methods.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

Geoscience Australia Data

Collection Method

Literature review and comparative analysis of existing studies.

Freshness

Last updated 2026-04-30 13:03:01.318820; freshness should be verified.