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: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=683922
• 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 EMIGPR 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 ac. The integrated EMIGPRsoil 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. *****

土壤物理性质，即土壤水文，在不同的景观中有所不同，并随着土地利用的变化和不同的农业实践而改变。精准农业已成为提高农业生产力和保持农业可持续发展的关键。探地雷达（GPR）和电磁感应（EMI）方法可用于评估直接或间接影响土壤水文的土壤性质的时空变异性。为了实现这一目标，土壤的视电导率（ECa）和雷达波速度（RWv）将通过集成EMI？探地雷达。***然而，使用传统方法估算土壤性质成本高、劳动强度大、耗时长，而且只能提供点信息，阻碍了任何快速响应管理活动。在现场尺度上获取信息的一种潜在方法是通过对易于记录和可重复的物理变量进行无创测绘，例如使用EMI的ECa和使用与相关土壤特性相关的探地雷达的RWv。应用综合的土壤时空变异性估算方法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，促进土地和水资源的可持续管理。在本研究中，多线圈多频电磁干扰传感器与探地雷达结合使用不同频率，将与土壤的基本性质相关联。***拟议的研究将解决在理解不同土地利用和农业实践对支持精准农业的影响方面的关键研究空白。制定使用与探地雷达结合的电磁干扰传感器进行非洲经委会调查的协议和准则将有助于迅速监测不同景观土壤性质的空间变异性。因此，正确的土壤、水和养分管理决策可以支持精准农业。研究的目标是：(a)将ECa数据分配给稳定土壤相对稳定的土壤特性，并使用测量数据生成回归模型；(b)利用延时电磁干扰获得可变土壤参数，以揭示诸如持水能力、拒水能力和渗透能力等水文过程；(c)评价两种不同的电磁干扰传感器及其探测深度的准确性，通过结合探地雷达测量和地面真实数据来预测近地表土壤特性；(d)根据ac的结果评估不同土地利用和农艺做法对土壤性质的影响。综合的EMIGPRsoil样本信息将为不同的管理方案和概念建立基线。长期目标是生成关键物理和水力特性的高分辨率地图，以便评估不同土地利用和农艺做法对土壤水文的影响，从而对精准农业的影响。＊＊＊＊＊