Automatic Estimation of Soil Biochar Quantity via Hyperspectral Imaging

IF 1.3 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Lei Tong, Jun Zhou, S. Bai, Chengyuan Xu, Y. Qian, Yongsheng Gao, Zhihong Xu
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引用次数: 1

Abstract

Biochar soil amendment is globally recognized as an emerging approach to mitigate CO2 emissions and increase crop yield. Because the durability and changes of biochar may affect its long term functions, it is important to quantify biochar in soil after application. In this chapter, an automatic soil biochar estimation method is proposed by analysis of hyperspectral images captured by cameras that cover both visible and infrared light wavelengths. The soil image is considered as a mixture of soil and biochar signals, and then hyperspectral unmixing methods are applied to estimate the biochar proportion at each pixel. The final percentage of biochar can be calculated by taking the mean of the proportion of hyperspectral pixels. Three different models of unmixing are described in this chapter. Their experimental results are evaluated by polynomial regression and root mean square errors against the ground truth data collected in the environmental labs. The results show that hyperspectral unmixing is a promising method to measure the percentage of biochar in the soil.
利用高光谱成像技术自动估算土壤生物炭的数量
生物炭土壤改良剂是全球公认的一种减少二氧化碳排放和提高作物产量的新兴方法。由于生物炭的耐久性和变化会影响其长期功能,因此对施用后土壤中生物炭的定量研究非常重要。在本章中,提出了一种土壤生物炭自动估算方法,该方法通过对相机拍摄的可见光和红外光波长的高光谱图像进行分析。将土壤图像视为土壤和生物炭信号的混合,然后采用高光谱解调方法估计每个像元上的生物炭比例。最终的生物炭百分比可以通过取高光谱像元比例的平均值来计算。本章描述了三种不同的分解模型。他们的实验结果通过多项式回归和均方根误差对环境实验室收集的真实数据进行评估。结果表明,高光谱解调是一种很有前途的测量土壤中生物炭百分比的方法。
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来源期刊
International Journal of Agricultural and Environmental Information Systems
International Journal of Agricultural and Environmental Information Systems COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
6.70
自引率
0.00%
发文量
10
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