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Evaluation of CAI Method of Crop Residue Assessment as a Tool for Soil and Water Conservation Management in the Dryland Agriculture of the Northern Great Plains

机译:评价北大平原旱地农业土壤和水资源管理工具的作物残留评价的评价

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The USDA Agricultural Research Station-Hydrology and Remote Sensing Laboratory (ARS-HRSL) had developed a remote sensing method capable of measuring crop residue cover. This method utilized the cellulose absorption index (CAI) at the short wave infrared region of the spectrum to differentiate soil from plant residues. The method worked well in humid areas in Iowa, where it was calibrated and tested, but it had not been tested in the ecologically fragile, semi-arid conditions of the Northern Great Plains (NGP) region. The effectiveness of CAI in differentiating crop residue from soil was affected by different soil and residue moisture levels and soil spectral properties, and needed to be evaluated in the NGP agricultural setting. This study aimed toassess the applicability of the CAI method in the NGP region across various dryland crops and soil types. Dryland crops, such as malting barley, spring wheat, durum, peas and fallow under conventional and ecological tillage systems were evaluated using amultispectral camera. CAI values were compared to visual measurements of crop residue cover. Initial results showed that the CAI method can effectively differentiate a bare soil from the various crop residues. Further analyses are being conducted to evaluate and relate CAI values with percent area of crop residue cover with respect to primary tillage systems. The results of this study could improve rapid assessment of soil and water conservation practices in the NGP, as well as other regions, especially if used with aerial and satellite multispectral imagery.
机译:USDA农业研究站 - 水文和遥感实验室(ARS-HRSL)开发了一种能够测量庄稼残留盖的遥感方法。该方法利用在光谱的短波红外区域的纤维素吸收指数(CAI),以区分来自植物残留物的土壤。该方法在爱荷华州潮湿地区工作得很好,在那里校准并测试,但它尚未在北大平原(NGP)区的生态脆弱,半干旱条件下进行测试。 CAI在从土壤中区分作物残留物的有效性受到不同土壤和残留水分水平和土壤光谱特性的影响,并且需要在NGP农业环境中进行评估。本研究旨在挖掘各种旱地作物和土壤类型的NGP地区CAI方法的适用性。使用AmultIspectral相机评估旱地作物,例如麦芽大麦,春小麦,杜兰姆,豌豆和休耕,以及常规和生态耕作系统。将CAI值与作物残留盖的视觉测量进行比较。初始结果表明,CAI方法可以有效地区分各种作物残留物的裸土。正在进行进一步分析以评估和将CAI值与作物残留物覆盖的百分比相对于初级耕种系统进行评价。本研究的结果可以提高NGP的土壤和水资源保护实践的快速评估,以及其他地区,特别是如果与空中和卫星多光谱图像一起使用。

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