Effect of DEM sources on quality indicators of predictive maps of soil cover
DOI:
https://doi.org/10.31073/acss90-04Keywords:
cartogram of agro-production soil groups; DEM; digital elevation model; modelling; morphometric parameters; predicative algorithms; soil mapAbstract
The aim of the study was to identify the impact of digital elevation models of different origins on the qualitative characteristics of forecast maps of soil cover or cartograms of agro-production soil groups using predictive modeling technologies. The current situation with large-scale soil cartographic data in Ukraine is analyzed and it is shown that the fastest and most cost-effective way to fill gaps in creating a continuous cartographic coverage for unexplored areas, which make up 33% of Ukraine, is mathematical simulation. The latter is based on morphometric analysis of digital elevation models, which distinguishes a number of predictors, which are further analyzed for links with existing cartographic soil materials by creating a mathematical predictive model using landscape reference points and associated soil type. The identified difference in the quality of predictive materials using the Cohen's kappa coefficient allows us to recommend individual sources of DEM as a basis for such tasks. A demonstration of a closed production cycle of creating predicative soil cartographic materials based on free software (GRASS and Quantum geographic information systems, language and environment for statistical computing and graphics R and shareware - Easy Trace vectorizer) was conducted.
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