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Quantitative monitoring of grazing intensity in the temperate meadow steppe based on remote sensing data

机译:基于遥感数据的温带草原草原放牧强度定量监测

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摘要

Grazing intensity (GI) is difficult to measure accurately because of the diversity of grazing livestock, their mobility in the grazing space and the uncertainty of grazing times. Thus, GI monitoring is often only qualitative, while quantitative monitoring is scarce. In this study, models correlating GI, the normalized difference vegetation index (NDVI) and aboveground biomass (AGB) were established based on a controlled GI experiment. The GI derived from NDVI was evaluated using the GI derived from AGB samples, under the principle that AGB is similar for the same GI in the same grassland type. The results showed that the appropriate time to build the model in the study area was from July to August, when there was a negative correlation between GI and NDVI. The simulated GI derived from NDVI was similar to GI derived from AGB, and the R-2 (coefficient of determination) values for fresh weight and dry weight were 0.3770 and 0.4292, respectively; the root mean square error (RMSE) were 0.2302 and 0.1953 animal units (AU) ha(-1) (1AU=500kg of adult cattle); and the relative error from -20% to 20% accounted for 62.07% and 72.41% of the total samples. Most of the study area was under heavy grazing according to monitoring results from 2010 to 2016, except for a few pastures with rational utilization (0.23AU ha(-1) - 0.46AU ha(-1)), and continuous heavy grazing often occurred for many years without rest grazing.
机译:由于放牧牲畜的多样性,它们在放牧空间中的流动性以及放牧时间的不确定性,放牧强度(GI)难以准确测量。因此,GI监测通常只是定性的,而定量监测却很少。在这项研究中,基于受控的GI实验,建立了与GI,归一化差异植被指数(NDVI)和地上生物量(AGB)相关的模型。使用AGB样本的GI评估NDVI的GI,其原则是在相同草地类型中,相同GI的AGB相似。结果表明,在研究区域建立模型的合适时间是从七月到八月,那时GI和NDVI之间存在负相关。来自NDVI的模拟GI与来自AGB的GI相似,鲜重和干重的R-2(测定系数)值分别为0.3770和0.4292;均方根误差(RMSE)为0.2302和0.1953动物单位(AU)ha(-1)(1AU = 500kg成年牛);相对误差从-20%到20%分别占样本总数的62.07%和72.41%。根据2010年至2016年的监测结果,除少数合理利用的牧场(0.23AU ha(-1)-0.46AU ha(-1))外,大部分研究区域处于重度放牧状态,并且经常发生连续的重度放牧多年没有放牧

著录项

  • 来源
    《International journal of remote sensing》 |2019年第6期|2227-2242|共16页
  • 作者单位

    Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Hulunber Grassland Ecosyst Observat & Res Stn, Beijing, Peoples R China;

    Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Hulunber Grassland Ecosyst Observat & Res Stn, Beijing, Peoples R China;

    Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Hulunber Grassland Ecosyst Observat & Res Stn, Beijing, Peoples R China;

    Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Hulunber Grassland Ecosyst Observat & Res Stn, Beijing, Peoples R China;

    Agr Univ Hebei, Key Lab Crop Growth Regulat Hebei Prov, Baoding, Peoples R China;

    Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Hulunber Grassland Ecosyst Observat & Res Stn, Beijing, Peoples R China;

    Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Hulunber Grassland Ecosyst Observat & Res Stn, Beijing, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
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