基于无人驾驶飞行器超光谱成像的土壤纹理含量的估计和绘制地图
Qi Song1,2,3, Xiaohong Gao4,5,6,7, Yuting Song1,2,3
1School of Geographical Sciences, Qinghai Normal University, Xining, 810008, China.
Scientific reports
|August 29, 2023
概括
无人机 (UAV) 的高光谱成像为土壤质地监测提供了一种快速的方法. 这项研究证明了它在西藏高原农业土地规划方面的有效性.
科学领域:
- 土壤科学 土壤科学
- 遥感 遥感 遥感 遥感
- 地质物理学 地质物理学
背景情况:
- 土壤质地是影响农业生产力的关键土壤属性.
- 目前的土壤质地监测严重依赖于地质谱仪,使用超光谱数据有限.
- 无人机 (UAV) 超光谱成像为高分辨率,快速的土壤调查提供了机会.
研究的目的:
- 调查使用无人机超光谱数据用于土壤质地监测的可行性.
- 校准实验室和现场光谱数据,以便直接应用于现场条件.
- 开发和验证用于无人机在土壤纹理分析中的高光谱图像的处理方法.
主要方法:
- 采集了296个土壤样本,这些样本来自青海黄盆地的三个农田.
- 获取无人机的高光谱图像和光谱数据.
- 无人机光谱与实验室和实地场景光谱的校准.
- 机器学习算法的应用用于土壤质地估计和绘制地图.
主要成果:
- 无人机高光谱图像与机器学习相结合,提供了有效的土壤纹理估计.
- 在光谱数据的预处理中,在土壤纹理估计和绘制地图方面取得了高准确性.
- 已建立的处理方法适用于无人机超光谱数据用于土壤质地监测.
结论:
- 无人机的高光谱数据与机器学习相结合,为快速的土壤质地调查提供了可行的解决方案.
- 开发的方法为西藏高原的农业土地规划提供了技术支持.
- 这项研究为在农田使用空中超光谱数据有效监测土壤质地奠定了基础.
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