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首页> 外文期刊>International journal of applied earth observation and geoinformation >Evaluating the relationship between biomass, percent groundcover and remote sensing indices across six winter cover crop fields in Maryland, United States
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Evaluating the relationship between biomass, percent groundcover and remote sensing indices across six winter cover crop fields in Maryland, United States

机译:在美国马里兰州的六个冬季覆盖作物田中评估生物量,地被植物百分比和遥感指数之间的关系

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Winter cover crops are an essential part of managing nutrient and sediment losses from agricultural lands. Cover crops lessen sedimentation by reducing erosion, and the accumulation of nitrogen in aboveground biomass results in reduced nutrient runoff. Winter cover crops are planted in the fall and are usually terminated in early spring, making them susceptible to senescence, frost burn, and leaf yellowing due to wintertime conditions. This study sought to determine to what extent remote sensing indices are capable of accurately estimating the percent groundcover and biomass of winter cover crops, and to analyze under what critical ranges these relationships are strong and under which conditions they break down. Cover crop growth on six fields planted to barley, rye, ryegrass, triticale or wheat was measured over the 2012-2013 winter growing season. Data collection included spectral reflectance measurements, aboveground biomass, and percent groundcover. Ten vegetation indices were evaluated using surface reflectance data from a 16-band CROPSCAN sensor. Restricting analysis to sampling dates before the onset of prolonged freezing temperatures and leaf yellowing resulted in increased estimation accuracy. There was a strong relationship between the normalized difference vegetation index (NDVI) and percent groundcover (r(2) = 0.93) suggesting that date restrictions effectively eliminate yellowing vegetation from analysis. The triangular vegetation index (TVI) was most accurate in estimating high ranges of biomass (r(2) = 0.86), while NDVI did not experience a clustering of values in the low and medium biomass ranges but saturated in the higher range (>1500 kg/ha). The results of this study show that accounting for index saturation, senescence, and frost burn on leaves can greatly increase the accuracy of estimates of percent groundcover and biomass for winter cover crops. Published by Elsevier B.V.
机译:冬季覆盖作物是管理农田中养分和沉积物流失的重要组成部分。覆盖作物通过减少侵蚀来减少沉积,地上生物量中氮的积累导致养分径流减少。冬季覆盖作物在秋季种植,通常在早春终止,由于冬季条件,它们容易衰老,霜冻和叶片变黄。这项研究试图确定遥感指数能够在多大程度上准确估算冬季覆盖作物的地被植物和生物量百分比,并分析这些关系在什么临界范围内很强,以及在何种条件下会破裂。在2012-2013年冬季生长季节,对六个大麦,黑麦,黑麦草,黑小麦或小麦的田地覆盖作物的生长情况进行了测量。数据收集包括光谱反射率测量,地上生物量和地表覆盖率。使用来自16波段CROPSCAN传感器的表面反射率数据评估了十个植被指数。将分析时间限制在开始采样日期之前,即延长的冷冻温度和叶黄变会提高估计的准确性。归一化植被指数(NDVI)与地被植物百分比之间存在很强的关系(r(2)= 0.93),表明日期限制有效地消除了分析过程中的泛黄植被。三角植被指数(TVI)在估算高生物量范围内最准确(r(2)= 0.86),而NDVI在中低生物量范围内没有出现值聚类,但在较高范围内(> 1500)处于饱和状态公斤/公顷)。这项研究的结果表明,考虑到指数饱和,衰老和树叶上的霜冻灼伤,可以大大提高冬季覆盖作物的地被植物和生物量百分比估算的准确性。由Elsevier B.V.发布

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