Mapping Soil Organic Carbon Using Local Terrain Attributes: A Comparison of Different Polynomial Models
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Application of a combinatorial approach for soil organic carbon mapping in hills
2021, Journal of Environmental ManagementCitation Excerpt :Second, the hilly area was divided into different terrain zones according to the different connections between the LS residuals and local factors (topographic and vegetation factors). This makes it feasible to accurately determine the varying relationships between SOC and local factors (Li et al., 2013; Wiaux et al., 2014; Song et al., 2017) and is also an important reason for the higher performance of LS_RBF_HASM compared to LS_HASM. Third, the RBF model has excellent capability to capture the complex relationships between SOC and LS residuals within different local terrain than MLR, and this led LS_RBF_HASM performance better than LS_MLR_HASM although they incorporated the same auxiliary environmental variables.
Effects of neighborhood analysis window forms and derivative algorithms on the soil aggregate stability – Landscape modeling
2021, CatenaCitation Excerpt :In this regard, A-Xing et al. (2008) demonstrated that the accuracy of DSM is strongly related to the neighborhood size applied to calculate terrain attributes. Xiaodong et al. (2017) also showed that appropriate terrain attribute algorithms could improve the digital mapping accuracy of soil organic carbon. The results of this study showed that the curvature attributes were more sensitive to the type of calculation patterns than the slope attributes.
Combining geomorphometry, feature extraction techniques and Earth-surface processes research: The way forward
2020, GeomorphologyCitation Excerpt :The lower resolution DEM (Fig. 9j) presents vagueness in the valley. Comparative studies in various discipline, ranging from hydrology (Buchanan et al., 2014; Sørensen et al., 2006), natural hazard (Barbarella et al., 2017; Favalli and Fornaciai, 2017; Mahalingam and Olsen, 2016), geomorphometry (Purinton and Bookhagen, 2017; Sofia et al., 2014a), watershed analysis (Liffner et al., 2018), soil science (Song et al., 2017; Song et al., 2016) proves that a calculation method that performs best for all measured variables does not exist; rather the best methods is generally variable, site-specific and specific to each field-of-study. We can think of geomorphometry as a research that is bridging two very different timescales: that of much longer landform evolution, and that based upon measurement using specially designed instrumentation.
Digital soil mapping algorithms and covariates for soil organic carbon mapping and their implications: A review
2019, GeodermaCitation Excerpt :Parameters that can be derived from DEM have also been widely used in DSM. Song et al. (2017a) compared the predictive performance of first-order terrain derivatives such as slope and aspect with second-order derivatives including various measures of terrain curvature. In comparison to lower order terrain parameters, higher order terrain parameters derived from the DEM were found to yield moderately smaller prediction errors, which may be due to the local de-noising in comparison to lower order terrain parameters.
Multinomial logistic regression with soil diagnostic features and land surface parameters for soil mapping of Latium (Central Italy)
2019, GeodermaCitation Excerpt :The appropriate resolution of a DEM will depend on the scale of the processes controlling soil formation and this will be strongly landscape dependent (McKenzie and Ryan, 1999). More recently, Ließ et al. (2012) produced digital soil maps of thickness and occurrence probability of a soil diagnostic horizon using classification and regression trees; Vågen et al. (2016) developed prediction models for mapping soil functional properties relying on the spectral properties of individual MODIS pixels; Song et al. (2017) combined prediction methods with local terrain attributes to improve their prediction performance for DSM of soil organic carbon. Land components (LCs, also called landform elements, terrain units or land surface segments) are often used as land units, mainly because their boundaries frequently coincide with transitions in environmental land properties (MacMillan et al., 2004).