首页> 外文会议>Annual Conference of the New Zealand Grassland Association >Validating satellite monitoring of dairy pastures in Canterbury with Lincoln University Dairy Farm and commercial farm data
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Validating satellite monitoring of dairy pastures in Canterbury with Lincoln University Dairy Farm and commercial farm data

机译:用林肯大学乳业农场和商业农场数据验证坎特伯雷乳制品卫星监测

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Validation of satellite-based prediction of pasture cover for dairy farms in Canterbury (New Zealand) during the 2008 and 2009 milking seasons is reported. Satellite-based predictions made using the new Canterbury model were validated against estimates from a rising plate meter for the Lincoln University Dairy Farm (LUDF) weekly farm walks and from nine commercial farms, across 15 images. Validation against LUDF data showed high coefficients of determination (mean R2 = 0.85, range 0.69 to 0.97 kg DM/ha) and low residual standard errors (mean RSE =138 kg, range 53 to 244 kg DM/ha). Validation against commercial data showed a higher level of variability between farms and images than the LUDF data. The Canterbury model accounted for a large proportionof the observed variability in pasture cover of dairy pastures when matched to high quality data, and showed seasonal trends in the model coefficients. Higher variability associated with commercial data may be attributed to geographic distribution, timing and method of data collection as well as varying levels of competency in monitoring skills.
机译:报道了2008年和2009年挤奶赛季坎特伯雷(新西兰)奶牛场牧场牧场牧场牧场覆盖的验证。使用新的坎特伯雷模型进行的基于卫星的预测验证了林肯大学奶牛场(LUDF)每周农场和九个商业农场的升高仪表的估计数,横跨15张图片。针对LUDF数据的验证显示了高系数的测定系数(平均R2 = 0.85,范围为0.69至0.97kg DM / HA)和低残留标准误差(平均RSE = 138千克,范围为53至244kg DM / HA)。针对商业数据的验证显示了比LUDF数据在农场和图像之间更高的可变性。坎特伯雷模型在匹配高质量数据时,乳制品牧场的牧场覆盖范围内观察到的变异性,并在模型系数中显示了季节性趋势。与商业数据相关的更高可变性可能归因于数据收集的地理分布,时序和方法以及监测技能的竞争力水平。

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