Accurate information on the amount of aboveground grass biomass (AGBg) stored in savannah rangelands remains unknown. Therefore, in this study we assessed the capability of a new multispectral sensor (Landsat-8 OLI) in estimating aboveground grass biomass stored within two different land use management units in savannah rangelands using the stepwise multiple linear regression methods. Specifically, we evaluated the performance of different Landsat-8 OLI derivatives (i.e. (a) spectral bands, (b) derived vegetation indices and (c) a combination of spectral bands and vegetation indices) to quantify aboveground grass biomass. The results highlighted that the use of spectral bands as stand-alone model variables yielded considerably high accuracies in terms of the coefficient of determination (r²) and the root mean square error (RMSE). An r² of 0.73 (72.81%) and RMSE of 37.88% for the protected area and an r² of 0.75 (75.18%) and with a RMSE of 33.16% for the nonprotected area were attained. The use of vegetation indices, however, demonstrated a very weak model performance yielding an r² of 0.31 (30.68%) and a RMSE of 51.51%, for the protected area and an r² of 0.50 (50.43%) and RMSE of 40% for the nonprotected areas. Comparatively, combining Landsat-8 OLI derived spectral bands and vegetation indices demonstrated improved model performance, yielding an r² of 0.92 (91.90%), and RMSE of 41.3% for the protected area and an r² of 0.94 (93.82%) with a RMSE of 33.14% for the nonprotected area. Therefore based on the observed results, AGBg in savannah rangelands can be satisfactorily estimated using broadband multispectral derivatives.

中文翻译：

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热带草原保护区和非保护区之间地上草生物量的遥感

关于存储在大草原牧场的地上草生物量 (AGBg) 数量的准确信息仍然未知。因此，在本研究中，我们使用逐步多元线性回归方法评估了一种新的多光谱传感器 (Landsat-8 OLI) 在估计热带草原牧场两个不同土地利用管理单元中存储的地上草生物量的能力。具体而言，我们评估了不同 Landsat-8 OLI 衍生物（即（a）光谱带，（b）衍生植被指数和（c）光谱带和植被指数的组合）以量化地上草生物量的性能。结果强调，使用光谱带作为独立的模型变量在决定系数方面产生了相当高的准确度 ( r ²) 和均方根误差 (RMSE)。保护区的r ²为 0.73 (72.81%)，RMSE 为 37.88%，非保护区的r ²为 0.75 (75.18%)，RMSE 为 33.16%。然而，植被指数的使用表明模型性能非常弱，保护区的r ²为 0.31 (30.68%) 和 RMSE 为 51.51%，r ²为 0.50 (50.43%) 和 RMSE 为 40%对于非保护区。相比之下，结合 Landsat-8 OLI 派生的光​​谱带和植被指数显示出改进的模型性能，保护区的r ²为 0.92 (91.90%)，RMSE 为 41.3%，r² of 0.94 (93.82%) 非保护区的 RMSE 为 33.14%。因此，根据观测结果，可以使用宽带多光谱导数来令人满意地估计大草原牧场的 AGBg。