A review summarizing 51 comparative studies on the performance of 62 spatial interpolation methods in environmental sciences. It analyzes 77 cases to quantify the impact of factors like sample density and data variation, and classifies 26 methods based on their features. The resource was published by the Australian Ocean Data Network and 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 variable correlation on interpolation accuracy as discussed in the review.
- Identifying suitable software packages for implementing spatial interpolation techniques from the provided list.
Strengths
- Summarizes a substantial body of research, including 51 comparative studies and 77 analyzed cases.
- Proposes a structured decision tree for selecting among 26 classified interpolation methods.
- Quantifies the impact of key factors like sample density and data variation on method performance.
Limitations
- The resource is a review document (HTML/PDF), not a dataset of raw environmental measurements.
- The specific data used in the 77 analyzed cases is not directly available for download.
- Column-level documentation for any underlying data is absent; field semantics must be inferred from the review text.
Provenance
- Source
- Australian Ocean Data Network
- Collection Method
- Literature review and synthesis of existing comparative studies.
- Freshness
- Last updated 2026-06-16 23:22:10.008078; freshness should be verified.