Abstract

In this study, we conducted a simulation experiment to identify robust spatial interpolation methods using samples of seabed mud content in the Geoscience Australian Marine Samples database. Due to data noise associated with the samples, criteria are developed and applied for data quality control. Five factors that affect the accuracy of spatial interpolation were considered: 1) regions; 2) statistical methods; 3) sample densities; 4) searching neighbourhoods; and 5) sample stratification. Bathymetry, distance-to-coast and slope were used as secondary variables. Ten-fold cross-validation was used to assess the prediction accuracy measured using mean absolute error, root mean square error, relative mean absolute error (RMAE) and relative root mean square error. The effects of these factors on the prediction accuracy were analysed using generalised linear models. The prediction accuracy depends on the methods, sample density, sample stratification, search window size, data variation and the study region. No single method performed always superior in all scenarios. Three sub-methods were more accurate than the control (inverse distance squared) in the north and northeast regions respectively; and 12 sub-methods in the southwest region. A combined method, random forest and ordinary kriging (RKrf), is the most robust method based on the accuracy and the visual examination of prediction maps. This method is novel, with a relative mean absolute error (RMAE) up to 17% less than that of the control. The RMAE of the best method is 15% lower in two regions and 30% lower in the remaining region than that of the best methods in the previously published studies, further highlighting the robustness of the methods developed. The outcomes of this study can be applied to the modelling of a wide range of physical properties for improved marine biodiversity prediction. The limitations of this study are discussed. A number of suggestions are provided for further studies.
Google map showing geographic bounding box with values North bound -8.0 East bound 165.0 West bound 105.0 South bound -50.0
Related Links

Product Type/Sub Type

nonGeographicDataset

Constraints

Creative Commons Attribution 4.0 International Licence

IP Owner

Commonwealth of Australia (Geoscience Australia)

Author(s)

Date (publication)

2010-01-01T00:00:00

Product Type

nonGeographicDataset

Topic Category

geoscientificInformation

GA Catalogue Number

70150 Product http://www.ga.gov.au/metadata-gateway/metadata/record/70150/

Keywords

GA Publication
Record
GIS
numerical modelling
environmental
geoscience
model
marine
AU-EEZ
Earth Sciences

Resource Language

English

Resource Character Set

utf8

Resource Security Classification

unclassified

Geographic Extent

North bound
-8.0
East bound
165.0
West bound
105.0
South bound
-50.0

Lineage

Unknown

Digital Transfer Options

onLine

Distributor

Role
distributor
Organisation Name
Commonwealth of Australia (Geoscience Australia)
City
Canberra
Administrative Area
ACT
Postal Code
2601
Country
Australia
Email Address

Source Description

Source data not available.

Metadata File Identifier

a05f7892-f002-7506-e044-00144fdd4fa6

Metadata Standard Name

ANZLIC Metadata Profile: An Australian/New Zealand Profile of AS/NZS ISO 19115:2005, Geographic information - Metadata

Metadata Standard Version

1.1

METADATA SECURITY CLASSIFICATION

unclassified

Metadata Contact

Role
pointOfContact
Organisation Name
Commonwealth of Australia (Geoscience Australia)
City
Canberra
Administrative Area
ACT
Postal Code
2601
Country
Australia
Email Address
Related Links