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Remote sensing of soil properties in precision agriculture: A review

机译:精准农业中的土壤特性遥感研究综述

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The success of precision agriculture (PA) depends strongly upon an efficient and accurate method for in-field soil property determination. This information is critical for farmers to calculate the proper amount of inputs for best crop performance and least environmental effect. Grid sampling, as a traditional way to explore in-field soil variation, is no longer considered appropriate since it is labor intensive, time consuming and lacks spatial exhaustiveness. Remote sensing (RS) provides a new tool for PA information gathering and has advantages of low cost, rapidity, and relatively high spatial resolution. Great progress has been made in utilizing RS for in-field soil property determination. In this article, recent publications on the subject of RS of soil properties in PA are reviewed. It was found that a large array of agriculturally-important soil properties (including textures, organic and inorganic carbon content, macro- and micro-nutrients, moisture content, cation exchange capacity, electrical conductivity, pH, and iron) were quantified with RS successfully to the various extents. The applications varied from laboratory-analysis of soil samples with a bench-top spectrometer to field-scale soil mapping with satellite hyper-spectral imagery. The visible and near-infrared regions are most commonly used to infer soil properties, with the ultraviolet, mid-infrared, and thermal-infrared regions have been used occasionally. In terms of data analysis, MLR, PCR, and PLSR are three techniques most widely used. Limitations and possibilities of using RS for agricultural soil property characterization were also identified in this article.
机译:精确农业(PA)的成功在很大程度上取决于一种有效,准确的田间土壤特性测定方法。这些信息对于农民计算出适当的投入量,以实现最佳的作物生长性能和最小的环境影响至关重要。网格采样作为探索野外土壤变化的一种传统方法,由于劳动强度大,耗时且缺乏空间穷尽性,因此不再被认为是合适的方法。遥感(RS)提供了一种新的PA信息收集工具,具有成本低,速度快,空间分辨率高的优点。在利用RS进行田间土壤性质测定方面已取得了巨大进展。在本文中,回顾了有关PA土壤特性的RS的最新出版物。研究发现,利用RS成功定量了许多农业上重要的土壤特性(包括质地,有机和无机碳含量,大量和微量营养元素,水分含量,阳离子交换容量,电导率,pH和铁)。在不同程度上。应用范围从使用台式光谱仪对土壤样品进行实验室分析到使用卫星高光谱图像进行现场规模的土壤制图都有所不同。可见区和近红外区最常用于推断土壤性质,偶尔会使用紫外区,中红外区和热红外区。在数据分析方面,MLR,PCR和PLSR是最广泛使用的三种技术。本文还确定了使用RS进行农业土壤性质表征的局限性和可能性。

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