Using Sentinel 2A spectral-zone images for qualitative assessment of soils in the Northern Forest-Steppe of Ukraine

P. Trofymenko, T. Myslyva, D. Stepanenko, Mykola Mohylko, V. Zatserkovnyi, N. Trofimenko
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Abstract

The research described in this paper is aimed at developing a methodology for remote determination of arable soil quality in the form of a bonita score using high-resolution spectral images. To achieve this goal, the dependencies between the values of the soil bonitet score and the spectral characteristics of satellite images of land cover areas were established. The geospatial models of soil cover scoring were verified, the results of which show a fairly high degree of correlation between the results of traditional soil scoring and remote sensing (NDSI, r = 0.91), the error value of the soil cover score for individual agricultural production groups of soils ranges from 1 to 12 points. It is found that despite the traditionally established use of vegetation indices to determine the state of crops, their use to determine the level of soil fertility is no less informative. It has been shown that the paired use of NDVI and NDSI values allows for the construction of relevant equations for remote determination of soil fertility, where the first of them acts as an auxiliary (clarifying) index, and the second as an effective working index.
使用哨兵2A光谱区图像对乌克兰北部森林草原土壤进行定性评估
本文所描述的研究旨在开发一种利用高分辨率光谱图像以bonita评分的形式远程测定耕地土壤质量的方法。为了实现这一目标,建立了土壤bonitet分值与土地覆盖区域卫星影像光谱特征之间的依赖关系。对土壤覆盖评分的地理空间模型进行了验证,结果显示传统土壤评分结果与遥感结果具有较高的相关性(NDSI, r = 0.91),土壤覆盖评分对单个农业生产组的误差值在1 ~ 12分之间。研究发现,尽管传统上使用植被指数来确定作物的状态,但使用它们来确定土壤肥力水平的信息量并不少。研究表明,配对使用NDVI和NDSI值可以构建相关方程,用于远程确定土壤肥力,其中前者作为辅助(澄清)指标,后者作为有效的工作指标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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