一个多角度反射数据集的小麦和桃树与无人机飞行器图像
Yuhan Guo1,2, Xihan Mu1,2, Xiang Lyu1,2
1State Key Laboratory of Remote Sensing and Digital Earth, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China.
Data in brief
|February 5, 2026
概括
无人机收集了小麦和桃树的多角度光谱数据,揭示了双向反射分布函数 (BRDF) 效应. 这一数据集有助于理解树冠的光谱动态,并提高植被遥感的准确性.
科学领域:
- 遥感 遥感 遥感 遥感
- 农业科学 农业科学
- 地理空间分析的研究.
背景情况:
- 卫星遥感,包括Sentinel-2和Landsat-8,已经推进了植被监测.
- 双向反射分布函数 (BRDF) 效应在植被现象学和参数检索中带来不确定性.
- 了解树冠反射功率的角效应对于准确的植被分析至关重要.
研究的目的:
- 开发使用无人机 (UAV) 的多角度反射数据集.
- 为了研究不同生长阶段在作物树冠上的角效应.
- 为BRDF分析和遥感模型验证提供高质量的数据.
主要方法:
- 使用无人机在小麦和桃树地块上获得的多角度光谱测量.
- 采用DJI Matrice 350 RTK与小麦的高光谱成像仪以及桃树的成长多光谱成像仪.
- 利用球状螺旋飞行轨迹进行全面的太阳视图几何覆盖,收集了1800多个观测.
主要成果:
- 在关键生长阶段生成了小麦和桃树在关键生长阶段高质量,多角度光谱测量的数据集.
- 数据捕捉了不同视角和照明角度的BRDF效应影响的光谱变化.
- 该数据集可以对BRDF特征和光谱指标的角度灵敏度进行详细分析.
结论:
- 来自无人机的多角度反射数据集对于研究植被遥感中的BRDF效应非常有价值.
- 这些数据支持对植被参数逆转和表态监测的物理和机器学习模型的验证.
- 这些发现有助于提高农业遥感应用的准确性和可靠性.
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