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Previous reports demonstrated that data from air- and spaceborne sensors are appropriate for delineation of soil patterns.
The raster method characterizes soil profiles in two dimensions and can be used to quantify lateral variation and improve field delineation of soil horizons.
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We evaluated a hybrid approach for disaggregating reconnaissance scale soil maps: rapid and inexpensive delineation of representative soil-landscape units in the field using expert knowledge, followed by the use of inductive, empirical, and correlative modeling techniques to map these landscape units.
The delineation of land mapping units will be based in part on land characteristics most readily mapped, frequently landforms, soils and vegetation.
This study proposes an object-based methodology, for detailed delineation and classification of soil types, using digital maps of topography and vegetation as soil covariates, based on Random forests classifier.
Soil moisture at each LU shows significantly different variance characteristics when compared with other units, and the delineation procedure reduces the spatial variation of soil moisture within each LU.
In this situation, quantification of soil loss and delineation of degraded areas is necessary for effective conservation planning (Yadav and Sidhu 2010).
These results suggest that despite morphological constraints and subjective factors in the delineation of eroded phases, these soils should be viewed as unique pedological entities that hold lasting value for understanding the effects of accelerated erosion on soil morphology, crop production, and ecosystem services.
Furthermore, vegetation would best proxy the delineation of single attribute of urban soils.
Legacy soil maps typically consist of a tessellation of polygon soil map unit delineations where the map units consist of a defined assemblage of soil classes assumed to exist in more-or-less fixed proportions.
Delineation of STUs within SMUs, i.e. spatial disaggregation of SMU, should improve the precision of soil information derived from legacy and ancillary data.
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