Abstract
Detailed and accurate information on the spatial variation of soil types and soil properties are critical components of environmental research and hydrological modeling. Early studies introduced a soil feedback pattern as a promising environmental covariate to predict spatial variation over low-relief areas. However, in practice, local evaporation can have a significant influence on these patterns, making them incomparable at different locations. This study aims to solve this problem by examining the concept of transforming the dynamic patterns of soil feedback from the original time-related space to a new evaporation-related space. A study area in northeastern Illinois with large low-relief farmland was selected to examine the effectiveness of this idea. Images from MODIS in Terra for every April–May period over 12 years (2000–2011) were used to extract the soil feedback patterns. Compared to the original time-related space, the results indicate that the patterns in the new evaporation-related space tend to be more stable and more easily captured from multiple rain events regardless of local evaporation conditions. Random samples selected for soil subgroups from the SSURGO soil map show that patterns in the new space reveal a difference between different soil types. And these differences in patterns are closely related to the difference in the soil structure of the surface layer.
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More From: International Journal of Applied Earth Observation and Geoinformation
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