TY - JOUR
T1 - Voronoi Natural Neighbours Tessellation
T2 - An interpolation and grid agnostic approach to forensic soil provenancing
AU - Aberle, Michael G.
AU - Robertson, James
AU - Hoogewerff, Jurian A.
N1 - Funding Information:
M. Aberle was generously supported in part by a PhD Research Training Program stipend funded by the Australian Government at the University of Canberra. The funding source had no involvement in the study design, sample/data collection, investigation, formal analysis or writing of this contribution.
Funding Information:
We would like to express our gratitude toward Geoscience Australia (GA) management and inorganic laboratory staff members for allowing MA's visits and use of GA resources to complete sample preparation, XRF and ICP-MS analyses. We are especially grateful to Patrice de Caritat, Stewart Gilmore, Christian Thun (both formerly from GA), Simon Webber, Tara Webster, and Jessica Byass for facilitating the in-kind analytical support, and laboratory training. We gratefully acknowledge and thank all visiting, past and present members of the ACTGUM project for their persistence and determination in fieldwork, and subsequent sample preparation. We thank all private landowners and the ACT Government for granting access to their property, public lands, and nature reserves to the ACTGUM field teams for sampling purposes. The Australian Federal Police Chemical Criminalistic team is acknowledged for their involvement and support, particularly Brenda Woods and Timothy Simpson for facilitating discussions, fieldwork access to restricted land zones, and collection of “blind” topsoil samples.
Publisher Copyright:
© 2023
PY - 2023/9
Y1 - 2023/9
N2 - Recently there has been an increase of work dedicated to developing a more objective soil provenancing capability. Notwithstanding the significant progress made, the presented provenancing techniques have predominately been based upon interpolation grids, generated from often arbitrary decisions of the user (e.g., grid cell size, grid placement, interpolation model, etc.). To address the acknowledged reproducibility issues, this paper introduces a spatial modelling technique based upon Voronoi Tessellations that is free from arbitrary user decisions. Termed herein as Voronoi Natural Neighbours Tessellation (VNNT), the proposed approach segments the survey area into many “honeycomb-like” polygons. Of which, the exact number, shape, location, and orientation of polygons are inherently dependent upon the original density of input sampling points from the survey, not a user's subjective decision. Utilising compositional geochemistry data from a fit-for-purpose topsoil survey and eleven “blind” soil samples from Canberra, Australia, we compare this proposed VNNT approach against a simpler Voronoi Tessellation, and a previously presented 500 m × 500 m grid following a modified and upscaled Natural Neighbour interpolation. Aside from also being computationally less intensive, our results indicated the proposed VNNT approach regularly yielded at least equal, or often more accurate provenance predictions than that of the gridded Natural Neighbour interpolation. Importantly, the delineation of individual polygons is fundamentally dependent upon the survey's real sampling design, and most truthfully reflects the underlying sampling density, and associated uncertainties. Consequently, the VNNT approach is significantly less susceptible to expert bias as a result of subjective decision-making and “fine-tuning” of interpolation parameters.
AB - Recently there has been an increase of work dedicated to developing a more objective soil provenancing capability. Notwithstanding the significant progress made, the presented provenancing techniques have predominately been based upon interpolation grids, generated from often arbitrary decisions of the user (e.g., grid cell size, grid placement, interpolation model, etc.). To address the acknowledged reproducibility issues, this paper introduces a spatial modelling technique based upon Voronoi Tessellations that is free from arbitrary user decisions. Termed herein as Voronoi Natural Neighbours Tessellation (VNNT), the proposed approach segments the survey area into many “honeycomb-like” polygons. Of which, the exact number, shape, location, and orientation of polygons are inherently dependent upon the original density of input sampling points from the survey, not a user's subjective decision. Utilising compositional geochemistry data from a fit-for-purpose topsoil survey and eleven “blind” soil samples from Canberra, Australia, we compare this proposed VNNT approach against a simpler Voronoi Tessellation, and a previously presented 500 m × 500 m grid following a modified and upscaled Natural Neighbour interpolation. Aside from also being computationally less intensive, our results indicated the proposed VNNT approach regularly yielded at least equal, or often more accurate provenance predictions than that of the gridded Natural Neighbour interpolation. Importantly, the delineation of individual polygons is fundamentally dependent upon the survey's real sampling design, and most truthfully reflects the underlying sampling density, and associated uncertainties. Consequently, the VNNT approach is significantly less susceptible to expert bias as a result of subjective decision-making and “fine-tuning” of interpolation parameters.
KW - Bias
KW - Fundamental science
KW - Interpolation
KW - Provenancing
KW - Soil forensics
KW - Voronoi tessellation
UR - http://www.scopus.com/inward/record.url?scp=85170084810&partnerID=8YFLogxK
U2 - 10.1016/j.forc.2023.100522
DO - 10.1016/j.forc.2023.100522
M3 - Article
AN - SCOPUS:85170084810
SN - 2468-1709
VL - 35
SP - 1
EP - 19
JO - Forensic Chemistry
JF - Forensic Chemistry
M1 - 100522
ER -