A Real–time Adaptive Sampling Method for Field Mapping in Patchy, Heterogeneous Environments

Many environmental studies require detailed maps describing the spatial distribution of various environmental characteristics. These distributions tend to be ‘patchy’; that is, their structure and their relationships vary from place to place according to the influences of the local setting. We present a simple sampling method that adapts the sample spacing on a point–by–point basis as the data are collected. The resulting sample is denser in areas of higher variability and sparser in more ‘well–behaved’ areas, and is collected in a single traverse of the transect. It uses a combination of simple fuzzy functions representing the concepts ‘too close’ and ‘too far’ that are adaptively parameterized based on current measurements. The adaptive sampler produced better representations for 47% of simulated reference transects than uniform or random samples of the same size under perfect measurement conditions, increasing to best performance for 71% of the transects when measurement error was severe with only minimal increase in sampling density. The rapid calculations can be easily incorporated into real–time data acquisition software, and the method may be extended to achieve some type of compromise when faced with the need to sample multiple simultaneous variables.

[1]  P. Goovaerts.  Geostatistics in soil science: state-of-the-art and perspectives , 1999 .

[2]  J. J. de Gruijter,et al.  A structured approach to designing soil survey schemes with prediction of sampling error from variograms , 1994 .

[3]  Michael Batty,et al.  FRACTAL MEASUREMENT AND LINE GENERALIZATION , 1989 .

[4]  Daniel G. Brown,et al.  Measuring the abruptness of patchy ecotones – A simulation-based comparison of landscape pattern statistics , 2001, Plant Ecology.

[5]  P. Graniero,et al.  The importance of topographic factors on the distribution of bog and heath in a Newfoundland blanket bog complex , 1999 .

[6]  J. Muller,et al.  Fractal and Automated Line Generalization , 1987 .

[7]  Phaedon C. Kyriakidis,et al.  A geostatistical approach for mapping thematic classification accuracy and evaluating the impact of inaccurate spatial data on ecological model predictions , 2001, Environmental and Ecological Statistics.

[8]  Robert G. Cromley.  Principal axis line simplification , 1992 .

[9]  A. Shogenova,et al.  Urban geochemistry: A study of element distributions in the soils of tallinn (Estonia) , 2000 .

[10]  Guangxing Wang,et al.  Spatial prediction and uncertainty analysis of topographic factors for the Revised Universal Soil Loss Equation (RUSLE) , 2000 .

[11]  K. C. Nielsen,et al.  Real time and the virtual outcrop improve geological field mapping , 1999 .

[12]  Robert S. Freeland,et al.  Mapping agricultural fields with GPR and EMI to identify offsite movement of agrochemicals , 2001 .

[13]  David H. Douglas,et al.  ALGORITHMS FOR THE REDUCTION OF THE NUMBER OF POINTS REQUIRED TO REPRESENT A DIGITIZED LINE OR ITS CARICATURE , 1973 .

[14]  Gavin S. P. Miller,et al.  The definition and rendering of terrain maps , 1986, SIGGRAPH.

[15]  Phillip Andrew Graniero,et al.  The effect of spatiotemporal sampling strategies and data acquisition accuracy on the characterization of dynamic ecological systems and their behaviours , 2001 .

[16]  P. A. Graniero,et al.  Investigating the role of fuzzy sets in a spatial modeling framework , 2001, Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569).

[17]  Andrew J. Graettinger,et al.  Directing Exploration with 3D FEM Sensitivity and Data Uncertainty , 1999 .

[18]  Hyungjun Park,et al.  An adaptive method for smooth surface approximation to scattered 3D points , 1995, Comput. Aided Des..

[19]  Alex B. McBratney,et al.  The design of optimal sampling schemes for local estimation and mapping of of regionalized variables—I: Theory and method , 1981 .

[20]  A. Journel.  Nonparametric estimation of spatial distributions , 1983 .

[21]  P. Jeroschewski,et al.  Application of in-situ and on-line measurements to environmental studies in Lake Müritz, northern Germany , 1998 .

[22]  Bernd Hamann,et al.  A data reduction scheme for triangulated surfaces , 1994, Comput. Aided Geom. Des..

[23]  Loukas G. Arvanitis,et al.  Multiresource inventories incorporating GIS, GPS and database management systems: a conceptual model. , 2000 .