The Rapid Method of Soil Identification Based on Remote Sensing and Geographic Information Systems (Case Study of Moramo Watershed)
Abstract
The field-tested samples are done by stratified random sampling. Soil classification was obtained through observation of field profile morphology and soil analysis in the laboratory followed by supporting data such as temperature and rainfall. The Moramo River Basin (DAS) was used as the location of the case study in this experiment by observing 13 soil profiles. Soil properties and characteristics were observed for soil texture, clay mineral, soil pH (H2O and KCl), soil cation, saturation bases, and C-organic. The soil naming was done to subgroup category based on Soil Taxonomy System in 2010 and paired with the land classification system of Soil Research Center in 1983, and WRB-FAO in 2006. The result showed that the accuracy of landform interpretation 89.6%, rocks 92.19%, accuracy of land use interpretation 90.63%, and accuracy of soil mapping 90.00%, so that the image ALOS AVNIR-2 can be utilized well to obtain parameter of the land unit for land mapping. The result of image data processing through RGB 341 composite image showed a high unidirectional frequency filter, histogram equalization, and analyzed with Geographic Information System, 15 units of landform, five-rock units. nine land-use units and 11 sub-soil sub-groups were obtained. The results of the soil classification in the Moramo Watershed (DAS) region in the subgroup category obtained 11 subgroups of land consisting of Lithic Udorthents, Typic Udifluvents, Aeric Endoaquents, Typic Fluvaquents, Typic Dystrudepts, Typic Eutrudepts, Ruptic-Alfic Eutrudepts, Lithic Dystrudepts, Oxyaquic Eutrudepts, Fluvaquentic Epiaquepts, Typic Endoaquepts.
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