Review of Spatial Interpolation Methods for Environmental Data

A 2026 review from Geoscience Australia compares 62 spatial interpolation methods across 51 comparative studies. The work quantifies the impact of factors like sample density and data variation using 77 cases and classifies 26 methods based on their features. It provides a decision tree for method selection and lists available 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.
• Quantifying the impact of sampling design and data quality on interpolation accuracy using the summarized assessment measures.
• Identifying software packages suitable for implementing specific spatial interpolation methods in marine or terrestrial studies.

Strengths

• Compares 62 methods and sub-methods based on 51 comparative studies.
• Quantifies impacts of sample density and variation using data from 77 cases.
• Provides a structured decision tree for selecting from 26 classified methods.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The primary content is a review document (PDF/HTML), not a structured dataset of environmental measurements.

Provenance

Source

Geoscience Australia Data

Collection Method

Literature review and comparative analysis of existing studies.

Freshness

Last updated 2026-04-20 01:57:58.195241; freshness should be verified.