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Unsupervised clustering of soil spectral curves to obtain their stronger correlation with soil properties

机译:未经监督的土壤光谱曲线聚类以获得与土壤性质的更强相关性

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The laboratory measurements of the diffuse spectral reflectance of 212 soil samples, representing many various taxonomic units, collected throughout the area of arable lands in Poland, were conducted to investigate the relationship between the soil reflectance and their selected properties. It was found that among various tested transformations the first derivative of the soil reflectance was the one most strongly correlated with the content of textural fractions, soil organic carbon, Fe and CaCO3, The use of unsupervised Ward's Euclidian distance based on clustering algorithm to split the total dataset into subsets, according to the shape and the level of the soil spectra, improved the correlation between soil properties and the transformed spectral data. The highest values of the coefficient of determination R2 for clay and Fe contents on the total dataset reached only 0.64 and 0.56, respectively. Using the ED Ward's algorithm, six subsets were formed and their R2 increased up to 0.87 and 0.80, respectively.
机译:进行了212种土壤样品的弥漫谱反射率的实验室测量,代表了在波兰耕地面积的整个地区收集的许多各种分类单位,以研究土壤反射率及其所选性质之间的关系。结果发现,各种经过测试的转化中,土壤反射率的第一个衍生物是与纹理分数,土壤有机碳,Fe和Caco 3 的最高值分别仅达到0.64和0.56。使用ED Ward的算法,形成了六个亚群,其R 2 分别增加到0.87和0.80。

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