基于无人机成像的综合数据驱动方法,用于监测灌水下的玉米生物质和水平,基于无人机成像
Farid Feizolahpour1, Sina Besharat2,3, Bakhtiar Feizizadeh4
1Department of Water Engineering, Faculty of Agriculture, Urmia University, Urmia, Iran.
Environmental monitoring and assessment
|August 24, 2023
概括
基于无人驾驶飞行器 (UAV) 的遥感有效监测玉米生物质. 频谱指数,特别是那些使用近红外和红边波段,如MTCI,提供准确的作物产量估计.
科学领域:
- 农业科学 农业科学
- 遥感 遥感 遥感 遥感
- 农业学是一种农业学.
背景情况:
- 基于无人驾驶飞行器 (UAV) 的遥感越来越多地用于现场规模的作物产量估计.
- 优化灌和 (N) 肥料管理对于最大限度地提高作物生物质和产量至关重要.
研究的目的:
- 评估各种光谱指数在不同水和N管理场景下监测和估计玉米生物质的有效性.
- 确定最准确的光谱指数,并开发出可靠的玉米生物质估计模型.
主要方法:
- 农场实验使用随机的完整块设计进行,使用三级灌水和N肥 (60%,80%,100%).
- 在关键生长阶段 (茎延长,开花,丝) 使用配备红杉传感器的固定翼无人机获取空中图像.
- 使用差异分解分析和线性回归模型来评估管理实践的影响以及光谱指数和玉米生物质之间的相关性.
主要成果:
- 使用近红外 (NIR) 和红边波段的光谱指数在估计玉米生物质方面表现出卓越的表现.
- 梅里斯陆地叶绿素指数 (MTCI) 获得了最高的准确性,R2为0.92和RMSE为8.27/ha.
- 贝叶斯式模型平均化 (BMA) 模型整合多个植被指数提高了生物质估计的准确性.
结论:
- 基于无人机的遥感,特别是使用NIR和红边光谱带,是玉米生物质估计的可靠方法.
- MTCI是评估整个生长季节玉米生物质的高效指数.
- 通过BMA模型将各种植被指数结合起来,提高了作物生物质估计的精度,有助于优化农业管理.
相关概念视频
02:16Light Acquisition
8.5K
In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
8.5K
02:35Key Elements for Plant Nutrition
18.8K
Like all living organisms, plants require organic and inorganic nutrients to survive, reproduce, grow and maintain homeostasis. To identify nutrients that are essential for plant functioning, researchers have leveraged a technique called hydroponics. In hydroponic culture systems, plants are grown—without soil—in water-based solutions containing nutrients. At least 17 nutrients have been identified as essential elements required by plants. Plants acquire these elements from the...
18.8K