探地雷达与电磁感应:农业的挑战与机遇

Remote. Sens. Pub Date : 2023-06-04 DOI:10.3390/rs15112932
Sashini Pathirana, S. Lambot, M. Krishnapillai, M. Cheema, C. Smeaton, L. Galagedara
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引用次数: 3

摘要

农业景观中土壤性质和状态的时空变化信息对于确定支持精准农业的管理区域至关重要。探地雷达(GPR)和电磁感应(EMI)技术已被用于评估土壤的性质、状态、过程及其时空变异性。本文综述了探地雷达和电磁干扰的基本工作原理,它们在土壤研究中的应用,优缺点,以及导致这两种技术在土壤数据研究中相互补充的困难的知识差距。与传统方法相比,GPR和EMI具有非破坏性重复测量的能力、高分辨率、节省人力以及在农业景观中具有更广泛的地理参考数据空间覆盖范围等优势。探地雷达已被广泛用于估算土壤含水量(SWC)和水动力学,而电磁干扰则有更广泛的应用,如估算土壤含水量、土壤盐度、容重等。此外,探地雷达还可以绘制土壤层、地下水位和其他异常情况。探地雷达和电磁干扰在土壤研究中的应用前景需要关注探地雷达和电磁干扰的潜在整合,以克服每种技术的内在局限性,并加强其应用以支持PA。通过同时估算许多土壤性质、状态和水文过程来划定管理区并计算农业景观的最佳投入,可以加强PA的未来进展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ground-Penetrating Radar and Electromagnetic Induction: Challenges and Opportunities in Agriculture
Information on the spatiotemporal variability of soil properties and states within the agricultural landscape is vital to identify management zones supporting precision agriculture (PA). Ground-penetrating radar (GPR) and electromagnetic induction (EMI) techniques have been applied to assess soil properties, states, processes, and their spatiotemporal variability. This paper reviews the fundamental operating principles of GPR and EMI, their applications in soil studies, advantages and disadvantages, and knowledge gaps leading to the identification of the difficulties in integrating these two techniques to complement each other in soil data studies. Compared to the traditional methods, GPR and EMI have advantages, such as the ability to take non-destructive repeated measurements, high resolution, being labor-saving, and having more extensive spatial coverage with geo-referenced data within agricultural landscapes. GPR has been widely used to estimate soil water content (SWC) and water dynamics, while EMI has broader applications such as estimating SWC, soil salinity, bulk density, etc. Additionally, GPR can map soil horizons, the groundwater table, and other anomalies. The prospects of GPR and EMI applications in soil studies need to focus on the potential integration of GPR and EMI to overcome the intrinsic limitations of each technique and enhance their applications to support PA. Future advancements in PA can be strengthened by estimating many soil properties, states, and hydrological processes simultaneously to delineate management zones and calculate optimal inputs in the agricultural landscape.
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