Monitoring Pasture Aboveground Biomass and Canopy Height in an Integrated Crop-Livestock System Using Textural Information from PlanetScope Imagery
Monitoring Pasture Aboveground Biomass and Canopy Height in an Integrated Crop-Livestock System Using Textural Information from PlanetScope Imagery
复制标题
使用 PlanetScope 图像的纹理信息监测农作物-牲畜综合系统中的牧场地上生物量和冠层高度
作者：
A. A. D. Reis;J. P. Werner;B. C. Silva;G. Figueiredo;J. Antunes;J. Esquerdo;A. Coutinho;R. Lamparelli;J. Rocha;P. G. Magalhães
快速、准确地量化现有牧草生物量对于支持集约化管理领域的放牧管理决策至关重要。Planet CubeSat卫星等新一代轨道平台提供的时间和空间分辨率不断提高，提高了利用遥感数据监测牧场生物量的能力。在这里，我们评估了使用来自PlanetScope图像的光谱和纹理信息估计牧场地上生物量（AGB）和冠层高度（CH）在集约化管理的领域和潜在的提高精度，通过应用极端梯度提升（XGBoost）算法的可行性。我们的研究结果表明，纹理措施增强AGB和CH估计相比，仅使用光谱波段或植被指数获得的性能。最好的结果是通过采用XGBoost模型的基础上，只对纹理措施。这些模型实现了适度高的精度来预测牧场AGB和CH，解释65%和89%的AGB（均方根误差（RMSE）= 26.52%）和CH（RMSE = 20.94%）的变异，分别。这项研究表明，在集中管理的混合牧场的高时空分辨率PlanetScope数据的基础上，使用纹理措施，以提高预测精度的AGB和CH模型的潜力。
Fast and accurate quantification of the available pasture biomass is essential to support grazing management decisions in intensively managed fields. The increasing temporal and spatial resolutions offered by the new generation of orbital platforms, such as Planet CubeSat satellites, have improved the capability of monitoring pasture biomass using remotely sensed data. Here, we assessed the feasibility of using spectral and textural information derived from PlanetScope imagery for estimating pasture aboveground biomass (AGB) and canopy height (CH) in intensively managed fields and the potential for enhanced accuracy by applying the extreme gradient boosting (XGBoost) algorithm. Our results demonstrated that the texture measures enhanced AGB and CH estimations compared to the performance obtained using only spectral bands or vegetation indices. The best results were found by employing the XGBoost models based only on texture measures. These models achieved moderately high accuracy to predict pasture AGB and CH, explaining 65% and 89% of AGB (root mean square error (RMSE) = 26.52%) and CH (RMSE = 20.94%) variability, respectively. This study demonstrated the potential of using texture measures to improve the prediction accuracy of AGB and CH models based on high spatiotemporal resolution PlanetScope data in intensively managed mixed pastures.
影响因子：
13.5
作者：
S. Punalekar;Anne Verhoef;Tristan Quaife;D. Humphries;Louise Bermingham;C. K. Reynolds
通讯作者：
S. Punalekar;Anne Verhoef;Tristan Quaife;D. Humphries;Louise Bermingham;C. K. Reynolds
影响因子：
5
作者：
Miller, Gwen J.;Morris, James T.;Wang, Cuizhen
通讯作者：
Wang, Cuizhen