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首页> 外文会议>World Engineers' Convention 2004 vol F-A: Resources and Energy; 20041102-06; Shanghai(CN) >Estimating Rangeland Cover and Yield Using Digital Data in the Arid and Semi-arid Areas
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Estimating Rangeland Cover and Yield Using Digital Data in the Arid and Semi-arid Areas

机译：在干旱和半干旱地区使用数字数据估算牧场的覆盖率和产量

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摘要

Remote sensing is considered as a tool for monitoring rangelands. Landsat TM data was used to examine biomass and cover levels at Manuka, Conservation, and Sandstone sites. Four 300 m transects were laid out at each site and measurements were made either in quadrats randomly located along the transects or in nearby exclosures. Two sets of cover and yield data obtained during the drought and good conditions. The data at each site was combined and compared with relative single pixel data. Correlations between cover and yield, and vegetation indices were calculated for selecting suitable indices being sensitive, to both green and brown vegetation cover and insensitive to soil background. Equations generated using ground truth data and satellite data for suitable indices were validated. The VNIR1 and VNIR2 indices and the MSI ratio at Manuka and the PD312 index at Fowlers Gap performed well. Equations obtained from these indices gave a high coefficient of determinations (R~2 = 0. 70 to 0. 98) and low standard errors. At Manuka there were no differences between values estimated from satellite images and those measured in the field (P < 0. 01). At Fowlers Gap, favourable estimates of yield from satellite images were derived at Sandstone paddock with low standard errors ( SE < 5 % ). However, standard errors of estimates at Conservation paddock during drought were relatively high (SE = 60%). The results indicated that Landsat TM data has potential to assess cover and yield of groups of species.
机译：遥感被视为监测牧场的工具。 Landsat TM数据用于检查麦卢卡，保护区和砂岩站点的生物量和覆盖水平。在每个站点上布置了四个300 m样带，并在沿样带随机分布的四边形中或附近的邻近区域进行了测量。在干旱和良好条件下获得了两组覆盖和产量数据。合并每个站点的数据，并将其与相对的单个像素数据进行比较。计算植被和产量之间的相关性，以及植被指数，以选择对绿色和棕色植被都敏感并且对土壤背景不敏感的合适指数。验证了使用地面真实数据和卫星数据生成的方程作为合适指标的方程。 VNIR1和VNIR2指数以及Manuka的MSI比和Fowlers Gap的PD312指数表现良好。从这些指数获得的方程式具有较高的测定系数（R〜2 = 0. 70至0. 98）和较低的标准误差。在麦卢卡，根据卫星图像估算的值与现场测量的值之间没有差异（P <0. 01）。在福勒斯峡（Fowlers Gap），以低标准误差（SE <5％）在沙石围场获得了卫星图像的有利估计。但是，干旱期间保育场的估算标准误差相对较高（SE = 60％）。结果表明，Landsat TM数据具有评估一组物种的覆盖率和产量的潜力。

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