Abstract

Abstract: The objective of this work was to disaggregate the polygons of physiographic map units in order to individualize the soil classes in each one, representing them as simple soil map units and generating a more detailed soil map than the original one, making these data more useful for future reference. A physiographic map, on a 1:25,000 scale, of the Tarumãzinho watershed, located in the municipality of Águas Frias, in the state of Santa Catarina, Brazil, was used. For disaggregation, three geomorphometric parameters were applied: slope and landforms, both derived from the digital terrain model; and an elevation map. The boundaries of the physiographic units and the elevation, slope, and landform maps were subjected to cross tabulation to identify the existing combinations between the soil classes of each physiographic unit. Based on these combinations, rules were established to select typical areas of occurrence of each soil type in order to train a decision tree model to predict the occurrence of soil classes. The model was trained using the Weka software and was validated with a set of georeferenced soil profiles. Disaggregation enables the individualization and spatialization of soil classes and is useful in producing detailed soil maps.

Highlights

  • Detailed knowledge regarding the spatial distribution of soil is vital for soil management programs aimed at monitoring the environment and managing agricultural production

  • An example is the technical report of Empresa de Pesquisa Agropecuária e Extensão Rural de Santa Catarina (Epagri, 2004), which describes the spatial distribution of the soils in the landscape, but does not represent graphically the soil classes on the produced map

  • Through photo interpretation and a field survey of the study area conducted by Empresa de Pesquisa Agropecuária e Extensão Rural de Santa Catarina (Epagri, 2004), six physiographic units were identified (Figure 1), taking into account their depositional or erosional origin: erosional summit (ES), erosional slope (ESL), erosional colluvial slope (ECS), colluvial erosional slope (CES), plateau slope (PS), alluvial colluvial valley bottom (ACVB)

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Summary

Introduction

Detailed knowledge regarding the spatial distribution of soil is vital for soil management programs aimed at monitoring the environment and managing agricultural production. Information on soil is often scarce or only available on a small scale, limiting its usefulness Factors such as reduced investments in soil surveys and in the time spent on soil research have contributed to this scenario (Arruda et al, 2016; Regmi & Rasmussen, 2018; Vincent et al, 2018). In this context, it is important to take advantage of existing information that explains the occurrence of soil in the landscape. A possible approach is the spatial disaggregation of the polygons of the combined PUs to better represent the spatial distribution of soils by individualizing and locating soil types in the landscape (Häring et al, 2012; Li et al, 2012; Odgers et al, 2014; Sarmento et al, 2017; Machado et al, 2018; Vincent et al, 2018)

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