• History of soil geography in the context of scale

    Categories of cartographic scale correspond to the selection of environmental soil predictors used to initially create historical soil maps. Paradigm shifts in soil mapping and classification can be best explained by not only their correlation to historical improvements in scientific understanding, but also by differences in purpose for mapping, and due to advancements in geographic technology. Although the hierarchy of phenomena scales observed in this study is generally known in pedology today, it also represents a new view on the evolution of soil science.

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  • Towards mapping soil carbon landscapes: Issues of sampling scale and transferability

    This study examines the spatial patterns and accuracies of predictions made by different spatial modelling methods on sample sets taken at two different scales. These spatial models are then tested on independent validation sets taken at three different scales. Each spatial modelling method produced similar, but unique, maps of soil organic carbon content (SOC%). Kriging approaches excelled at internal spatial prediction with more densely spaced sample points.

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  • Types of Scale

    When you read the phrases “large scale” or “small scale,” do you know what they mean? Sometimes “large scale” is describing a large area and sometimes it is describing a small area, depending on if the author was thinking about process scale or cartographic scale. This is a problem for communication. In this post I describe the different types of scale that geographers recognize, which will hopefully encourage others to be specific when they are discussing scale.

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  • Impact of multi-scale predictor selection for modeling soil properties

    Results suggest that models with limited predictor pools can substitute other predictors to compensate for unavailable variables. However, a better performing model was always found by considering predictor variables at multiple scales. Although the scale effect of the modifiable area unit problem is generally well known, this study suggests digital soil mapping efforts would be enhanced by the greater consideration of predictor variables at multiple analysis scales.

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  • Is It a Scientific Theory or Hypothesis?

    This is a common question addressing a popular misconception about how science classifies the knowledge that it has accumulated. The levels of hypothesis, theory, and law often get interpreted as classes of confidence. However, this is not really right. The missing piece here is spatial scale!

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  • The historical role of base maps in soil geography

    This paper reviews the historical development of base maps used for soil mapping, and evaluates the dependence of soil mapping on base maps. Formerly, as a reference for spatial position, paper base maps controlled the cartographic scale of soil maps. However, this relationship is no longer true in geographic information systems. Today, as parameters for digital soil maps, base maps constitute the library of predictive variables and constrain the supported resolution of the soil map.

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  • Multi-scale Parameter Selection for Predicting Soil Organic Carbon (2014 Digital Soil Mapping Workshop)

    This poster presents work analyzing the impact on model performance from utilizing a wide range of DTA analysis scales together with RS data, some of which have a resolution that could be considered too coarse for fine resolution DSM. Data mining techniques were used to select parameters from large pools of base maps for modelling the variables needed to estimate soil organic carbon (SOC) stocks. The best performing models were then used to produce maps of the SOC stock and estimated prediction error.

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  • Semantic calibration of digital terrain analysis scale

    DTA has not been field tested to the extent that traditional field metrics of topography have been. Human assessment of topography synthesizes multiple parameters at multiple scales to characterize a landscape, based on field experience. In order to capture the analysis scale used by field scientists, this study introduces a method for calibrating the analysis scale of DTA to field assessments.

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