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Mapping a Profile Wall of a Typic Udipsamments from the Central Sands in Wisconsin, USA

机译:从美国威斯康星州的中央沙子映射典型的udipsamments的轮廓墙

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We measured and mapped the spatial distribution of Al; Si, Fe, Mn, Ca, pH, soil moisture content (6), and color of a soil profile wall of a Typic Udipsamments. A 10 x 10 cm grid was laid on the soil profile wall, and 70 soil samples were collected from the grid centers. The spatial distribution of these properties was mapped with block kriging. The kriged values of the elements and red color were used in fc-means clustering to identify soil horizons. Variation in the profile was considerable, but weobserved that Fe, Mn, Ca, pH, and 0 decreased with soil depth, while red color increased. The concentration of Al and Si increased at depth between 30 and 60 cm from the soil surface. The fc-means clustering was able to locate three soil horizons in theprofile, which was comparable to the standard soil profile description. We found that pXRF and soil color index coupled with clustering could be useful in digital soil morphometries for the identification of soil horizons.
机译:我们测量并映射了Al的空间分布; Si,Fe,Mn,Ca,pH,土壤水分含量(6),以及典型UdiSam的土壤剖面墙的颜色。在土壤轮廓壁上铺设了10×10cm的网格,并从网格中心收集了70种土壤样品。这些属性的空间分布用块kriging映射。在FC-MEAREL聚类中使用元素和红色的克里格特值以识别土壤视野。轮廓的变化相当可观,但我们使用土壤深度减少了Fe,Mn,Ca,pH和0,而红颜色增加。 Al和Si的浓度在距离土壤表面30至60厘米之间的深度增加。 FC-Means聚类能够定位在助长的三种土壤视野中,该润滑性与标准土壤轮廓描述相当。我们发现,与聚类相结合的PXRF和土壤颜色指数可用于数字土壤形态量,以识别土壤视野。

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