Analysis of Crop Spectral Reflectance at the Croplands in Eastern Kazakhstan Using Satellite Imagery

Q4 Social Sciences
K. Samarkhanov, M. Sadenova, N. Beisekenov
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引用次数: 0

Abstract

Using satellite imagery, this study investigates the spectral reflectance characteristics of crops at the OHMK farm in Eastern Kazakhstan, focusing on wheat and barley. The analysis reveals significant differences in spectral reflectance, particularly in the visible and near-infrared regions, and tracks change over time during different growth stages. Employing principal component analysis (PCA), strong correlations are observed between specific spectral bands and principal components, providing insights into crop variability. Derived equations enable the estimation of principal component values based on spectral information. These findings have implications for crop monitoring, management, and precision agriculture, offering potential yield optimization and resource allocation improvements. The study highlights the potential use of spectral reflectance analysis for crop health assessment and yield prediction, with implications for agricultural decision-making and enhanced productivity. Further research is needed to expand the application of this approach to other crops and conditions.
利用卫星图像分析哈萨克斯坦东部农田的作物光谱反射率
本研究利用卫星图像调查了哈萨克斯坦东部 OHMK 农场作物的光谱反射特性,重点是小麦和大麦。分析表明,光谱反射率存在显著差异,尤其是在可见光和近红外区域,并跟踪不同生长阶段随时间发生的变化。利用主成分分析(PCA),可以观察到特定光谱波段与主成分之间的强烈相关性,从而深入了解作物的变异性。根据光谱信息推导出的方程可以估算主成分值。这些发现对作物监测、管理和精准农业具有重要意义,可提供潜在的产量优化和资源分配改进。这项研究强调了光谱反射率分析在作物健康评估和产量预测方面的潜在用途,对农业决策和提高生产力具有重要意义。要将这种方法推广应用到其他作物和条件,还需要进一步的研究。
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来源期刊
International Journal of Geoinformatics
International Journal of Geoinformatics Social Sciences-Geography, Planning and Development
CiteScore
1.00
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