Remote sensing of soil properties in precision agriculture: A review

Abstract

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 laboratoryanalysis 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.

Digital Mapping of Soil Properties Using Multivariate Statistical Analysis and ASTER Data in an Arid Region

“…Remotely-sensed imagery in combination with field measurements has been used intensively for the last two decades in modeling and mapping of soil properties in a cost-effective manner at various scales [7,8]. Satellite sensors, such as the Landsat Thematic Mapper (TM) Enhanced Thematic Mapper Plus (ETM+), Operational Land Imager (OLI) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), have been used to map soil properties [9].…”

Effects of soil compaction on cereal yield

“…Nowadays, remote sensing is widespread and a recent trend is the use of the hyperspectral method (Ge et al 2011) which also provides an opportunity to record the large database of soil parameters and to adapt and validate the decision support models. We emphasize that the EC a measurements could contribute to the increase in accuracy of decision support models (Nagy et al 2013).…”

Organic Matter Modeling at the Landscape Scale Based on Multitemporal Soil Pattern Analysis Using RapidEye Data

“…Owing to the demand for qualitative and quantitative soil information at multiple scales in precision agriculture (PA) [1][2][3][4][5][6], accurate functional soil maps are needed for the concept of site-specific management (SSM) to balance a profitable and cost-effective crop production with environmental concerns and sustainability [7][8][9][10]. To evaluate site-specific spatiotemporal variable soil properties at the field-scale, many functional soil mapping models and approaches based on digital elevation models (DEM), proximal and/or remote sensing (RS) data have been designed.…”

“…Compared with geostatistical and spatial interpolation methods (e.g., Kriging procedures, fuzzy clustering algorithms) based on comprehensive, time-consuming, and costly field surveys and soil sampling, non-invasive remote and proximal sensors, combined with empirical-or physical-based data analysis, offer potentially more effective, quick, and cost-efficient continuous direct or indirect data on physiochemical soil characteristics, which are determined by spatial, temporal or spectral sensor resolutions [1,6,[11][12][13][14][15][16][17][18]. Due to the advantages of existing, easily accessible data archives, relatively low-cost and high-temporal, high-spatial resolution multispectral imagery and time series are available for qualitative and partly-quantitative soil information extraction, deduction of soil patterns, and mapping of SSM zones and soil surface units [7,15].…”

“…For the latest state-of-the-art science, Ge et al (2011) [7], Mulla (2013) [8], Mulder et al (2011) [15], and Panda et al (2010) [19] provide research summaries of remote sensing systems and applications in PA and soil science (e.g., crop yield, biomass, soil organic content, and soil texture). Numerous studies have investigated the relation between soil reflectance characteristics (e.g., soil color and soil brightness) and soil properties, particularly organic matter (OM), soil moisture, and texture [1,[20][21][22][23][24].…”