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首页> 外文期刊>GIScience & remote sensing >Comparing the spectral settings of the new generation broad and narrow band sensors in estimating biomass of native grasses grown under different management practices
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Comparing the spectral settings of the new generation broad and narrow band sensors in estimating biomass of native grasses grown under different management practices

机译：比较新一代宽带和窄带传感器的光谱设置，以估算在不同管理方式下种植的天然草的生物量

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The challenge of assessing and monitoring the influence of rangeland management practices on grassland productivity has been hampered in southern Africa, due to the lack of cheap earth observation facilities. This study, therefore, sought to evaluate the capability of the newly launched Sentinel 2 multispectral imager (MSI) data, in relation to Hyperspectral infrared imager (HyspIRI) data in estimating grass biomass subjected to different management practices, namely, burning, mowing and fertilizer application. Using sparse partial least squares regression (SPLSR), results showed that HyspIRI data exhibited slightly higher grass biomass estimation accuracies (RMSE=6.65g/m(2), R-2=0.69) than Sentinel 2 MSI (RMSE=6.79g/m(2), R-2=0.58) across all rangeland management practices. Student t-test results then showed that Sentinel 2 MSI exhibited a comparable performance to HyspIRI in estimating the biomass of grasslands under burning, mowing and fertilizer application. In comparing the RMSEs derived using wave bands and vegetation indices of HyspIRI and Sentinel, no statistically significant differences were exhibited (=0.05). Sentinel (Bands 5, 6 and 7) and HyspIRI (Bands 730nm, 740nm, 750nm, 710nm), as well as their derived vegetation indices, yielded the highest predictive accuracies. These findings illustrate that the accuracy of Sentinel 2 MSI data in estimating grass biomass is acceptable when compared with HyspIRI. The findings of this work provide an insight into the prospects of large-scale grass biomass modeling and prediction, using cheap and readily available multispectral data.
机译：由于缺乏廉价的地球观测设施，评估和监测牧场管理做法对草地生产力的影响的挑战在南部非洲受到了阻碍。因此，本研究试图评估新发布的Sentinel 2多光谱成像仪（MSI）数据与高光谱红外成像仪（HyspIRI）数据相关的能力，以评估经受不同管理方式（即燃烧，割草和肥料）的草生物量应用。使用稀疏偏最小二乘回归（SPLSR），结果显示HyspIRI数据显示的草木生物量估计准确性（RMSE = 6.65g / m（2），R-2 = 0.69）比Sentinel 2 MSI（RMSE = 6.79g / m）高（2），R-2 = 0.58）。学生t检验的结果表明，在估计燃烧，割草和施肥情况下的草地生物量方面，Sentinel 2 MSI表现出与HyspIRI相当的性能。在比较使用HyspIRI和Sentinel的波段和植被指数得出的RMSE时，没有显示出统计学上的显着差异（= 0.05）。前哨（波段5、6和7）和HyspIRI（波段730nm，740nm，750nm，710nm）及其派生的植被指数产生了最高的预测精度。这些发现表明，与HyspIRI相比，Sentinel 2 MSI数据在估计草的生物量方面的准确性是可以接受的。这项工作的发现使用便宜且容易获得的多光谱数据，为大规模草类生物量建模和预测的前景提供了见识。

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