在现场VIS-NIR光谱仪用于基本和快速的土壤调查
Guillaume Debaene1, Piotr Bartmiński2, Marcin Siłuch2
1Department of Soil Science Erosion and Land Protection, Institute of Soil Science and Plant Cultivation, State Research Institute, ul. Czartoryskich 8, 24-100 Puławy, Poland.
Sensors (Basel, Switzerland)
|July 8, 2023
概括
可见和近红外光谱 (VIS-NIR) 可以通过简单的现场测量来预测土壤特性. 这种方法提供了一个快速的,粗略的选在田间规模的土壤成分.
科学领域:
- 土壤科学 土壤科学
- 频谱学是一种光谱学.
- 地理空间分析是什么
背景情况:
- 可见和近红外光谱 (VIS-NIR) 在土壤科学中广泛用于属性预测,主要是在实验室条件下.
- 在现场测量通常需要接触探头和耗时的方法,产生与远程获取数据不同的光谱.
研究的目的:
- 评估直接VIS-NIR光谱测量的有效性,使用光纤或裸露土壤上的4度镜头来预测土壤特性.
- 开发和比较部分最小平方 (PLS) 和支向量机 (SVM) 回归模型,用于土壤碳 (C), (N) 含量和土壤纹理 (沙子,泥土,粘土).
主要方法:
- 使用光纤或4度镜头,直接从裸露的未接触过的土壤中获取反射频谱.
- 使用PLS和SVM回归开发C,N含量和土壤纹理的预测模型.
- 纳入土壤湿度和温度作为辅助数据,以潜在地提高模型性能.
主要成果:
- 在光谱预处理后,对于C含量 (R2 = 0.57) 和N含量 (R2 = 0.53) 实现了令人满意的预测模型.
- 当包括湿度和温度等辅助数据时,模型性能显示有所改善.
- 使用实验室和预测值生成C,N和粘土含量的地图.
结论:
- 使用光纤光学或4度镜头获得的VIS-NIR光谱适合在现场规模上构建预测模型,以获得初步的土壤成分信息.
- 开发的预测地图对于快速的,尽管是近似的,对土壤特性进行现场选是有价值的.
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