Fire is used extensively in prairie grassland management in the Flint Hills region of the midwestern United States, particularly at the end of the dormant season (March–April). A model is used to manage grassland fires in the region to avoid deterioration of air quality beyond acceptable standards. Dormant season dry biomass is an important parameter in the model. The commonly used method for producing high-quality biomass estimates relies on clipping, drying and weighing small biomass samples, which is tedious, expensive and does not scale efficiently to larger areas to provide regional estimates. Small unmanned aircraft systems (sUAS) were used to develop a reliable and more efficient method of biomass estimation based on the correlation between biomass and vegetation canopy height derived from digital surface models (DSMs). A linear regression model was developed from data collected at 11 representative sites in the Kansas Flint Hills region, and the model was validated at two sites. Biomass and canopy heights derived from DSMs were correlated, with a Pearson product moment correlation value of 0.881 (P-value <0.001). Biomass estimated from clipped vegetation at two validation sites positively correlated with model-derived biomass estimates, resulting in linear regression R2-values of 0.90 and 0.74 and Pearson moment correlation coefficients of 0.99 (P < 0.001) and 0.86 (P = 0.003). The described sUAS method has the potential to increase the efficiency and reliability of dormant season grassland biomass estimates.

中文翻译：

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利用小型无人机系统产生的超高空间分辨率航空成像估算高草草原休眠季节草生物量的有效方法

美国中西部弗林特希尔斯地区的草原草原管理中广泛使用火，特别是在休眠季节结束时（3 月至 4 月）。模型用于管理该地区的草原火灾，以避免空气质量恶化超出可接受的标准。休眠期干生物量是模型中的一个重要参数。生成高质量生物量估计值的常用方法依赖于对小生物量样本进行剪裁、干燥和称重，这既乏味又昂贵，并且不能有效地扩展到更大的区域以提供区域估计值。小型无人机系统 (sUAS) 被用于开发一种可靠且更有效的生物量估算方法，该方法基于生物量与从数字表面模型 (DSM) 得出的植被冠层高度之间的相关性。线性回归模型是根据在堪萨斯州弗林特希尔斯地区 11 个代表性地点收集的数据开发的，并在两个地点验证了该模型。来自 DSM 的生物量和冠层高度相关，Pearson 积矩相关值为 0.881（P 值 <0.001）。从两个验证点的修剪植被估计的生物量与模型得出的生物量估计值呈正相关，导致线性回归 R2 值为 0.90 和 0.74，皮尔逊矩相关系数为 0.99 (P < 0.001) 和 0.86 (P = 0.003)。所描述的 sUAS 方法有可能提高休眠季节草地生物量估计的效率和可靠性。来自 DSM 的生物量和冠层高度相关，Pearson 积矩相关值为 0.881（P 值 <0.001）。从两个验证点的修剪植被估计的生物量与模型得出的生物量估计值呈正相关，导致线性回归 R2 值为 0.90 和 0.74，皮尔逊矩相关系数为 0.99 (P < 0.001) 和 0.86 (P = 0.003)。所描述的 sUAS 方法有可能提高休眠季节草地生物量估计的效率和可靠性。来自 DSM 的生物量和冠层高度相关，Pearson 积矩相关值为 0.881（P 值 <0.001）。从两个验证点的修剪植被估计的生物量与模型得出的生物量估计值呈正相关，导致线性回归 R2 值为 0.90 和 0.74，皮尔逊矩相关系数为 0.99 (P < 0.001) 和 0.86 (P = 0.003)。所描述的 sUAS 方法有可能提高休眠季节草地生物量估计的效率和可靠性。74 和皮尔逊矩相关系数分别为 0.99 (P < 0.001) 和 0.86 (P = 0.003)。所描述的 sUAS 方法有可能提高休眠季节草地生物量估计的效率和可靠性。74 和皮尔逊矩相关系数分别为 0.99 (P < 0.001) 和 0.86 (P = 0.003)。所描述的 sUAS 方法有可能提高休眠季节草地生物量估计的效率和可靠性。