Integrated Proximal Sensing of Soil and Crop

土壤和作物的集成近端传感

• 批准号: 402298-2012
• 负责人: Adamchuk, Viacheslav
• 金额: $ 1.53万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=573233
• 关键词: Integrated; Proximal; Sensing; Soil; Crop

Proximal sensing of soils and crops is a growing area of science and technology that uses sensing systems to obtain information either close to, or in direct contact with, the target. When deployed properly, proximal sensing systems provide high-density data on the physical, chemical and biological attributes of soil and crops. These attributes help us to better understand the changes in soil conditions influencing crop growth. Accounting for this variability over space and time reduces the negative environmental impact and increases profitability. In recent years, proximal sensing technology has been used to increase efficiency in the use of fertilizers, water, and other production inputs as well as to assess the environment. The main problem is that most sensors respond to more than one agronomic property, which frequently complicates the decision-making process. Sensor fusion is an emerging concept that relies on combining data from alternative sources to increase the certainty of the information obtained. Although appealing, the concept is poorly understood and requires substantial development in both theory and potential applications. In this proposal, a unique methodology to integrate the most promising and cost-effective sensing technologies is discussed. Conceptually different, commercially available, proximal soil/crop sensors will be used simultaneously as well as integrated with our recently developed sensor prototypes. Also, proximal sensing data that includes ground elevation will be integrated with remotely sensed data (satellite or airborne imagery). The interdisciplinary and multipurpose nature of this approach promises an endless array of potential uses. While demonstrating and analyzing certain applications, the ultimate goal of this program is to develop a strong and reliable dataflow structure that can be adopted easily across many disciplines in agriculture and in the management of natural resources.

土壤和作物的近距离传感是一个不断发展的科学和技术领域，它使用传感系统来获得接近或直接接触目标的信息。如果部署得当，近距离传感系统可提供关于土壤和作物的物理、化学和生物属性的高密度数据。这些属性有助于我们更好地了解影响作物生长的土壤条件变化。考虑到这种空间和时间上的可变性，减少了对环境的负面影响，提高了盈利能力。近年来，近端传感技术已被用于提高肥料、水和其他生产投入的使用效率以及评估环境。主要的问题是，大多数传感器响应不止一个农艺性状，这往往使决策过程复杂化。传感器融合是一个新兴的概念，它依赖于将来自其他来源的数据结合起来，以增加所获得信息的确定性。虽然很吸引人，但这一概念却鲜为人知，需要在理论和潜在应用方面进行实质性的发展。在这项提案中，一个独特的方法来整合最有前途的和成本效益的传感技术进行了讨论。概念上不同的，商业上可用的，近端土壤/作物传感器将同时使用，以及与我们最近开发的传感器原型集成。此外，包括地面高程在内的近距离传感数据将与遥感数据（卫星或机载图像）相结合。这种方法的跨学科和多用途性质保证了无限的潜在用途。在演示和分析某些应用程序的同时，该计划的最终目标是开发一种强大可靠的可编程逻辑结构，可以在农业和自然资源管理的许多学科中轻松采用。