Methodology

APbase uses standard geostatistical methods in its automatic mapping pipeline. You can generate maps without reading this section. Use it when you want to understand the mathematics, tune an advanced workflow, or see why one method won over another.

The default pipeline compares IDW and ordinary kriging using validation error, then uses the method that performs better on the current data. In Python, apbase.create_map is the functional shortcut for the same pipeline. Co-kriging is covered here as an advanced method for workflows with screened secondary variables.

References

The bibliography entries include DOI, publisher, or stable catalog links when available.

  1. Shepard, Donald (1968). A two-dimensional interpolation function for irregularly-spaced data. Proceedings of the 1968 23rd ACM National Conference, 517–524, ACM. doi:10.1145/800186.810616
  2. Matheron, Georges (1971). The Theory of Regionalized Variables and Its Applications. École des Mines de Paris. https://books.google.com/books/about/The_Theory_of_Regionalized_Variables_and.html?id=TGhGAAAAYAAJ
  3. Cressie, Noel A. C. (1993). Statistics for Spatial Data. Wiley. doi:10.1002/9781119115151
  4. Isaaks, Edward H.; Srivastava, R. Mohan (1989). An Introduction to Applied Geostatistics. Oxford University Press. https://global.oup.com/academic/product/an-introduction-to-applied-geostatistics-9780195050134
  5. Maldaner, Leonardo Felipe; Corrêdo, Lucas Pontara; Tavares, Tiago Rodrigues; Mendez, Luiz Guilherme; Duarte, Cassio; Molin, José Paulo (2018). Identifying and filtering out outliers in spatial datasets. Proceedings of the 14th International Conference on Precision Agriculture. https://www.researchgate.net/publication/326557441_Identifying_and_filtering_out_outliers_in_spatial_datasets
  6. Maldaner, Leonardo Felipe; Molin, José Paulo (2020). Data processing within rows for sugarcane yield mapping. Scientia Agricola, 77(5), e20200101. doi:10.1590/1678-992X-2018-0391
  7. Journel, A. G.; Huijbregts, C. J. (1978). Mining Geostatistics. Academic Press. https://books.google.com/books/about/Mining_Geostatistics.html?id=w5UZAQAAIAAJ
  8. Myers, Donald E. (1982). Matrix formulation of co-kriging. Mathematical Geology, 14(3), 249–257. doi:10.1007/BF01032887
  9. Goovaerts, Pierre (1997). Geostatistics for Natural Resources Evaluation. Oxford University Press. https://global.oup.com/academic/product/geostatistics-for-natural-resources-evaluation-9780195115383
  10. Wackernagel, Hans (2003). Multivariate Geostatistics. Springer. doi:10.1007/978-3-662-05294-5
  11. Goulard, Michel; Voltz, Marc (1992). Linear coregionalization model: tools for estimation and choice of cross-variogram matrix. Mathematical Geology, 24(3), 269–286. doi:10.1007/BF00893750
  12. Xu, Weiliang; Tran, Thanh T.; Srivastava, R. Mohan; Journel, André G. (1992). Integrating seismic data in reservoir modeling: the collocated cokriging alternative. SPE Annual Technical Conference and Exhibition. doi:10.2118/24742-MS
  13. Journel, André G. (1999). Markov models for cross-covariances. Mathematical Geology, 31(8), 955–964. doi:10.1023/A:1007553013388
  14. Chilès, Jean-Paul; Delfiner, Pierre (2012). Geostatistics: Modeling Spatial Uncertainty. Wiley. doi:10.1002/9781118136188
  15. Fisher, Ronald A. (1921). On the probable error of a coefficient of correlation deduced from a small sample. Metron, 1, 3–32. https://hdl.handle.net/2440/15169