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首页> 外文期刊>Animal Production Science >Using MODIS imagery, climate and soil data to estimate pasture growth rates on farms in the south-west of Western Australia.
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Using MODIS imagery, climate and soil data to estimate pasture growth rates on farms in the south-west of Western Australia.

机译:使用MODIS影像,气候和土壤数据估算西澳大利亚州西南部农场的牧场增长率。

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Remote sensing of vegetation and its monitoring using the normalised difference vegetation index (NDVI) offers the opportunity to provide a coverage of agricultural land at a large scale. The availability of MODIS NDVI at a resolution of 250 m provided the opportunity to evaluate the hypothesis that pasture growth rate (PGR) of individual paddocks can be accurately predicted using a model based on MODIS NDVI in combination with climate and soil data and a light-use efficiency model. Model estimates of PGR were compared with field measurements of PGR recorded in grazing enclosure cages collected over 3 years from six farms located across the south-west region of Western Australia. The estimates attained from the model explained 70% of the variation in PGR for individual paddocks on farms over the 3 years of the study, with an average error at the paddock scale of 10.4 kg DM/ha.day over all growing seasons and years. Across all farms studied, there was generally good agreement between satellite-derived PGR and ground-based measurements, although estimates of PGR varied between years and farms. The model explained 47% of the variation in pasture growth early in the season (from break of season to end of July), compared with 62% late in the season (from August to pasture senescence). The present study demonstrated that PGR for individual paddocks can be predicted at weekly intervals from MODIS imagery, climate and soil data and a light-use efficiency model at an accuracy sufficient to facilitate on-farm pasture and livestock management.
机译:植被的遥感及其使用归一化植被指数(NDVI)的监视提供了机会,可以大规模覆盖农业用地。分辨率为250 m的MODIS NDVI的可用性提供了评估以下假设的机会:使用基于MODIS NDVI的模型,结合气候和土壤数据以及光照,可以准确预测单个牧场的草场生长率(PGR)。使用效率模型。将PGR的模型估算值与在3年中从西澳大利亚州西南地区的六个农场收集的放牧围网中记录的PGR实地测量值进行了比较。通过模型获得的估算值解释了研究3年中农场个体牧场的PGR变化的70%,在所有生长季节和年份中,牧场规模的平均误差为10.4 kg DM / ha.day。在所有研究的农场中,尽管年份和农场之间的植物遗传资源估计值各不相同,但卫星衍生的植物遗传资源和地面测量值之间通常有很好的一致性。该模型解释了季节初期(从季节休息到七月底)牧场生长变化的47%,而季节后期(从八月到牧场衰老)则为62%。本研究表明,可以根据MODIS图像,气候和土壤数据以及光利用效率模型,每周精确地预测单个牧场的PGR,其精确度足以促进农场牧场和牲畜的管理。

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