Abstract
The application of quantitative methods to digital soil and geomorphological mapping is becoming an increasing trend. One of these methods, Geomorphons, was developed to identify the ten most common landforms based on digital elevation models. This study aimed to make a quantitative assessment of the relationships between Geomorphons units, determined at three spatial resolutions and nine radii, and soil types and properties of two watersheds with different soil-landscape relationships in Brazil to help soil surveying and mapping under tropical conditions. The study was conducted at Lavrinha Creek (LCW) and Marcela Creek (MCW) watersheds, located in the state of Minas Gerais, Brazil. Spatial resolutions of 10, 20 and 30 m were the basis for generating Geomorphons at 9 radii of calculation for the watersheds. They were overlapped to detailed soil maps of the watersheds and a chi-square test was carried out to assess their relationship with soil types. Observation points were compared with the most highly correlated Geomorphons to also assess relationships with soil properties. Geomorphons with resolution of 30-m and radii of 20 and 50 cells, respectively for LCW and MCW, were more highly correlated with the variability of soil types, in accordance with the terrain features of these watersheds. The majority of observation points for each soil type was located in the same Geomorphon unit that was dominant when analyzing soil maps. There was less variability in soil properties between Geomorphon units, which was probably due to the highly weathered-leached stage of soils. Geomorphons can help to improve soil maps in tropical conditions when assessing soil variability due to its high correlation with tropical soil types variability.
Highlights
In soil surveys, the understanding of existing relationships between soil types and/or properties and landscape features are fundamental to defining the most representative places for soil morphological description and sampling
Geomorphons, was developed to identify the ten most common landforms based on digital elevation models
It was observed that the pixel size alone had great influence on chi-square values and, the correspondence between soil types and Geomorphon unit (GU)
Summary
The understanding of existing relationships between soil types and/or properties and landscape features are fundamental to defining the most representative places for soil morphological description and sampling This understanding is needed for digital soil and geomorphological mapping (Bishop et al, 2012). The advent of digital soil mapping tools has promoted a rise in global interest in more detailed soil maps (Vaysse and Lagacherie, 2015) and a transition from qualitative to more quantitative soil mapping methods (McBratney et al, 2003) This has been proposed as an approach to exposing the soil scientist's mental (qualitative) model (Bui, 2004) of soil distribution in the landscape through the mapping process. Applying it to more quantitative methods, this knowledge can be made explicit on maps, resulting in improvements in existing maps, and these relationships can be understood by other soil scientists
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