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Mitigating the effects of soil and residue water contents on remotely sensed estimates of crop residue cover

机译:减轻土壤和残留水含量对遥感估计的农作物残留覆盖率的影响

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Crop residues on the soil surface decrease soil erosion and increase soil organic carbon and the management of crop residues is an integral part of many conservation tillage systems. Current methods of measuring residue cover are inadequate for characterizing the spatial variability of residue cover over large fields. The objectives of this research were to determine the effects of water content on the remotely sensed estimates of crop residue cover and to propose a method to mitigate the effects of water content on remotely sensed estimates of crop residue cover. Reflectance spectra of crop residues and soils were measured in the lab over the 400-2400 nm wavelength region. Reflectance of scenes with various residue cover fractions and water contents was simulated using a linear mixture model. Additional spectra of scenes with mixtures of crop residues and soil were also acquired in corn, soybean, and wheat fields with different tillage treatments and different water content conditions. Crop residue cover was linearly related to the cellulose absorption index (CAI), which was defined as the relative intensity of an absorption feature near 2100 nm. Water in the crop residue significantly attenuated CAI and changed the slope of the residue cover vs. CAI relationship. Without an appropriate correction, crop residue covers were underestimated as scene water content increased. Spectral vegetation water indices were poorly related to changes in the water contents of crop residues and soils. A new reflectance ratio water index that used the two bands located on the shoulders of the cellulose absorption feature to estimate scene water conditions was proposed and tested with data from corn, soybean, and wheat fields. The ratio water index was used to describe the changes in the slope of crop residue cover vs. CAI and improve the predictions of crop residue cover. These results indicate that spatial and temporal adjustments in the spectral estimates of crop residue cover are possible. Current mutispectral imaging systems will not provide reliable estimates of crop residue cover when scene water content varies. Hyperspectral data are not required, because the three narrow bands that are used for both CAI and the scene moisture correction could be incorporated in advanced multispectral sensors. Thus, regional surveys of soil conservation practices that affect soil carbon dynamics may be feasible using either advanced multispectral or hyperspectral imaging systems. (c) 2007 Published by Elsevier Inc.
机译:土壤表面的农作物残留物可减少土壤侵蚀并增加土壤有机碳,而农作物残留物的管理是许多保护性耕作系统不可或缺的一部分。当前测量残留物覆盖率的方法不足以表征大视野范围内残留物覆盖率的空间变异性。这项研究的目的是确定水分含量对作物残留量遥感估算的影响,并提出减轻水分含量对作物残留量遥感估算的影响的方法。在实验室中在400-2400 nm波长范围内测量了农作物残留物和土壤的反射光谱。使用线性混合模型模拟了具有各种残渣覆盖率和水含量的场景的反射率。在不同耕作处理和不同含水量条件下的玉米,大豆和麦田中,还获得了带有农作物残渣和土壤混合物的场景的其他光谱。作物残渣覆盖率与纤维素吸收指数(CAI)呈线性关系,纤维素吸收指数(CAI)定义为2100 nm附近吸收特征的相对强度。作物残渣中的水分显着减弱了CAI,并改变了残渣覆盖率与CAI关系的斜率。如果不进行适当的校正,则由于现场含水量增加,农作物残留覆盖率被低估了。光谱植被水分指数与农作物残渣和土壤中水分含量的变化关系不大。提出了一种新的反射比水指数,该指数使用位于纤维素吸收特征肩膀上的两个谱带来估计现场水况,并用玉米,大豆和小麦田的数据进行了测试。比率水指数用于描述作物残茬覆盖率相对于CAI的斜率变化,并改善了作物残茬覆盖率的预测。这些结果表明,对作物残茬覆盖率的光谱估计进行时空调整是可能的。当场景含水量变化时,当前的多光谱成像系统将无法提供可靠的农作物残留覆盖率估算。不需要高光谱数据,因为用于CAI和场景湿度校正的三个窄带可以合并到高级多光谱传感器中。因此,使用先进的多光谱或高光谱成像系统对影响土壤碳动态的土壤保护措施进行区域调查可能是可行的。 (c)2007年由Elsevier Inc.发布。

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