Integrated EMI-GPR surveys can support precision agriculture by monitoring and evaluating the effects of land uses and agricultural management

综合 EMI-GPR 调查可以通过监测和评估土地利用和农业管理的影响来支持精准农业

• 批准号: RGPIN-2019-04614
• 负责人: Galagedara, Lakshman
• 金额: $ 2.26万
• 依托单位: Memorial University of Newfoundland
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=755179
• 关键词: Integrated; EMI; GPR; surveys; support

Soil physical properties, thus soil hydrology, varies across the landscape and is altered following land use changes and different agricultural practices. Precision agriculture has become the key to increase the productivity and maintaining the sustainability of agriculture. Ground penetrating radar (GPR) and electromagnetic induction (EMI) methods can be used to assess the spatiotemporal variability of soil properties that will directly or indirectly effect on soil hydrology. For achieving this, soil's apparent electrical conductivity (ECa) and radar wave velocity (RWv) will be used through integrated EMI?GPR. However, estimating soil properties using traditional methods is expensive, labor-intensive, and time-consuming and provides point information only, which hinder any rapid response management activities. A potential way to acquire information at field-scale is by noninvasive mapping of easily recordable and reproducible physical variables such as ECa using the EMI and RWv using the GPR that correlate with relevant soil properties. The application of the integrated EMI-GPR methods for estimating the spatiotemporal variability soil properties are unique in boreal ecosystems and will aid in the development of new scientific knowledge for sustainable management of land and water resources. In this research, combined multi-coil and multi-frequency EMI sensors integrated with GPR using different frequencies will be correlated with fundamental soil properties. The proposed research will address key research gaps regarding the understanding of the effects of different land uses and agronomic practices for supporting precision agriculture. Development of protocols and guidelines for conducting ECa surveys using combined EMI sensors integrated with GPR will help to monitor the spatial variability of soil properties across different landscapes rapidly. Thus, correct soil, water and nutrient management decisions can be decided in supporting precision agriculture. Objectives of the research are to: (a) allocate ECa data to stable soil relatively stable soil properties and generate regression models using measured data; (b) obtain variable soil parameters to reveal hydrological processes such as water holding capacity, water repellency and infiltration capacity by means of time-lapse EMI; (c) evaluate the accuracy of two different EMI sensors and their exploration depths for predicting near-surface soil properties by integrating with GPR measurements and ground truth data; and (d) assess the effects of different land use and agronomic practices on soil properties based on the results from a-c. The integrated EMI-GPR-soil sample information will build the baseline for different management scenarios and concepts. The long-term goal is to generate high-resolution maps of key physical and hydraulic properties in order to assess the effects of different land uses and agronomic practices on soil hydrology, and thus on precision agriculture.

土壤物理特性（因此土壤水文学）在整个景观中都有所不同，并且在土地使用变化和不同的农业实践后会改变。精确农业已成为提高生产力并维持农业可持续性的关键。地面穿透性雷达（GPR）和电磁诱导（EMI）方法可用于评估土壤特性的时空变异性，这些变化将直接或间接对土壤水文产生直接或间接影响。为了实现这一目标，将通过集成的EMI？gpr使用土壤的明显电导率（ECA）和雷达波速度（RWV）。 但是，使用传统方法估算土壤特性是昂贵，劳动密集型且耗时的，并且仅提供点信息，这阻碍了任何快速的响应管理活动。使用与相关土壤特性相关的GPR，使用EMI和RWV对易于记录和可重复的物理变量（例如ECA）进行非侵入性映射（例如ECA）来获取信息的潜在方法。综合EMI-GPR方法在估算时空变异性土壤特性中的应用在北方生态系统中是独一无二的，将有助于开发新的科学知识，以实现土地和水资源的可持续管理。在这项研究中，使用不同频率集成的多型型和多频EMI传感器将与基本土壤特性相关。拟议的研究将解决有关理解不同土地用途的影响以及支持精确农业的影响的关键研究差距。使用与GPR集成的组合的EMI传感器进行ECA调查的方案和指南将有助于监测不同景观跨不同景观的土壤特性的空间变异性。因此，可以在支持精确农业方面做出正确的土壤，水和养分管理决策。研究的目标是：（a）将ECA数据分配给稳定的土壤相对稳定的土壤特性，并使用测量的数据生成回归模型； （b）获取可变的土壤参数以揭示水文过程，例如通过延时EMI进行水的能力，排水和渗透能力； （c）评估两个不同的EMI传感器的准确性及其探索深度，以通过与GPR测量和地面真实数据集成来预测近地表土壤特性； （d）根据A-C的结果，评估不同土地使用和农艺实践对土壤特性的影响。集成的EMI-GPR-ail样本信息将为不同的管理场景和概念建立基线。长期的目标是生成关键物理和液压特性的高分辨率图，以评估不同土地用途和农艺实践对土壤水文的影响，从而评估对精确农业的影响。