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Hyperspatial mapping of water, energy and carbon fluxes with Unmanned Aerial Vehicles

机译:用无人驾驶飞行器对水,能量和碳通量进行超空间映射

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摘要

Having spatially distributed estimates of energy, water and carbon fluxes between the land and the atmosphere is of critical importance for improving water resource management, agricultural production, weather forecasting, and climate prediction. Traditionally, satellite based remote sensing data of vegetation or temperature has been used as inputs into land surface models (LSMs). However, the coarse resolution of satellite based remote sensing (3-90 km) data could not accurately capture spatial heterogeneity in fluxes due to changes in topography, soil types, and vegetation. With significant advances in navigation, flight control, miniaturized platforms and sensors, Unmanned Aerial Vehicles (UAVs) can provide ultra-high spatial resolution imagery (1 cm to 1 m). This presents a good opportunity to improve land surface modeling. From this perspective, our study explores the possibility to incorporate UAV-based remote sensing into LSMs. A site growing an energy crop with field sensors (eddy covariance, radiation or soil moisture) at DTU-Risø is chosen for the pilot study. A hexacopter (Tarot) equipped with a six band multispectral camera (Visible and near infrared), a thermal camera and a digital camera regularly flew over the flux site. In the near future, a smart UAV platform combining rotary and fixed wing functionality will be used as platform. The imagery acquired by UAVs will be used to retrieve the vegetation indices and land surface temperature. These data used for land surface modeling to estimate biomass, plant diseases or stress, water uptake.
机译:对土地与大气之间的能量,水和碳通量进行空间分布的估计对于改善水资源管理,农业生产,天气预报和气候预测至关重要。传统上,基于卫星的植被或温度遥感数据已用作地表模型(LSM)的输入。然而,由于地形,土壤类型和植被的变化,基于卫星的遥感(3-90 km)数据的粗分辨率无法准确捕获通量的空间异质性。随着导航,飞行控制,小型化平台和传感器方面的重大进步,无人飞行器(UAV)可以提供超高分辨率的图像(1 cm至1 m)。这为改善陆地表面建模提供了一个很好的机会。从这个角度出发,我们的研究探索了将基于无人机的遥感技术整合到LSM中的可能性。选择在DTU-Risø种植带有田间传感器(涡动协方差,辐射或土壤湿度)的能源作物的地点进行试点研究。配备六波段多光谱摄像头(可见光和近红外),热像仪和数码相机的六轴飞行器(Tarot)定期飞越磁通场。在不久的将来,将结合旋转和固定翼功能的智能无人机平台作为平台。无人机获取的图像将用于检索植被指数和地表温度。这些数据用于陆地表面建模,以估计生物量,植物病害或胁迫,水分吸收。

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