远程和近距离传感器数据融合:灌管理区分的数字双胞胎
Hugo Rodrigues1, Marcos B Ceddia2, Wagner Tassinari3
1Institute of Food and Agricultural Sciences, University of Florida, McCarty Hall, 1604 McCarty Dr 1008, Gainesville, FL 32603, USA.
Sensors (Basel, Switzerland)
|September 14, 2024
概括
使用稀疏土壤采样进行精准农业绘制是可行的. 外部漂移 (KED) 的Kriging有效地使用辅助数据来创建管理区准确的表面电导率 (aEC) 地图.
科学领域:
- 农业科学 农业科学
- 土壤科学 土壤科学
- 地理空间分析是什么
背景情况:
- 精准农业需要详细的土壤数据,但广泛的采样资源密集.
- 在土壤采样中,数据密度,成本和地图准确性之间存在权衡.
- 优化投入使用和减少农业对环境的影响需要有效的数据采集策略.
研究的目的:
- 通过稀疏的土壤采样来评估表面电导率 (aEC) 的映射方法.
- 为了比较使用外部漂移 (KED) 和地理加权回归 (GWR) 的 kriging 的性能,与从详尽采样中得出的参考地图进行比较.
- 评估这些方法在定义灌管理区 (MZs) 的有效性.
主要方法:
- 使用EM38-MK2传感器收集了详尽的表面电导率 (aEC) 数据集 (3906点).
- 从详尽的数据中模拟了一个稀疏的数据集 (162点).
- 在参考地图中使用了普通 kriging (OK);KED和GWR被应用于稀疏的数据集,包括遥感和地形共变量.
主要成果:
- 参考aEC地图 (详尽的数据,OK) 实现了高精度 (R2 = 0.97,RMSE = 0.56).
- 使用稀疏数据的外部漂移 (KED) 的Kriging显示出良好的性能 (R2 = 0.78,MAE = 1.26,RMSE = 1.62),表现优于GWR (R2 = 0.57,MAE = 1.78,RMSE = 2.30).
- 来自KED的管理区与参考地图密切匹配,验证了其灌管理潜力.
结论:
- 稀疏的土壤采样与KED和辅助变量相结合,为aEC绘制提供了一个可行的替代方案,而不是详尽的采样.
- 在使用有限的数据创建准确的土壤属性地图方面,KED表现出高于GWR的卓越性能.
- KED方法为定义管理区提供了可靠的指导,优化了精密农业的灌策略.
相关概念视频
02:35Key Elements for Plant Nutrition
18.7K
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...
18.7K
01:21Manipulation and Analysis
22
GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
22
01:25Selected Data About Geographic Locations
26
Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
26
01:29Applications of GIS: Disaster Management and Emergency Response
63
Geographic Information System (GIS) technology is essential for risk identification, action prioritization, and resource optimization in critical situations like flooding and earthquakes. By integrating spatial and demographic data, GIS provides a comprehensive framework for emergency response.GIS integrates data layers, like rainfall intensity, topography, elevation profiles, and river levels, to model high-risk flood zones. These layers assess areas susceptible to flooding based on their...
63
01:29Levels of Use of a GIS
46
Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
46