Robert S. Freeland

Mapping agricultural fields with GPR and EMI to identify offsite movement of agrochemicals

Offsite movement of waterborne agrochemicals is increasingly targeted as a non-point source of water quality degradation. Our research has indicated that subsurface water movement is variable and site-specific, and that a small soil volume frequently conducts a large volume of flow. This concentrated flow is usually caused by soil morphology, and it often results in water moving rapidly offsite from certain areas of fields; little or no lateral subsurface flow may occur in other areas. Identifying these subsurface regions is difficult using conventional soil survey and vadose zone sampling techniques. In this study, traditional surveying is combined with electromagnetic induction (EMI) and ground-penetrating radar (GPR) mapping to identify areas with high potential for subsurface offsite movement of agrochemicals, optimizing these identification techniques, and expanding the mapping procedures to make them useful at the field-scale for agricultural production practices. Conclusions from this research are: (1) EMI mapping provides rapid identification of areas of soil with a high electrical conductivity and presumably high potential for offsite movement of subsurface water, (2) GPR mapping of areas identified by EMI mapping provides a means to identify features that are known to conduct concentrated lateral flow of water, and (3) combining the capabilities of EMI and GPR instrumentation makes possible the surveys of large areas that would otherwise be impossible or unfeasible to characterize.

Mapping shallow underground features that influence site-specific agricultural production

Modern agricultural production practices are rapidly evolving in the United States of America (USA). These new production practices present significant applications for nonintrusive subsurface imaging. One such imaging technology is GPR, and it is now being incorporated within site-specific agriculture in the detection of soil horizons, perched water (episaturation), fragipans, hydrological preferential flow paths, and soil compaction. These features traditionally have been mapped by soil scientists using intrusive measurements (e.g., soil augers, soil pits, coring tools). Rather than developing a tool for soil mapping, our studies are targeting the identification, dimensioning, and position of subsurface features that directly influence agricultural productivity. It is foreseen that this information will allow for an increase in agricultural efficiency through infield machinery automation, and it will also greatly enhance development of highly efficient crop production strategies. The field sensing methodologies that we have developed using existing geophysical technologies are highly dependent upon both the soil and site characteristics due to seasonal variations. The GPR applications presented herein were conducted primarily in a region of loess soil that extends east of the Mississippi River into western Tennessee. GPR studies were also conducted in central Tennessee on the Cumberland Plateau within a region of shallow, sandy loam soils. Additional studies were conducted on the karst area of central Kentucky. Although targeting site-specific agriculture, our results and procedures may benefit the traditional users of GPR technology. We suggest that large-scale agricultural applications of the technology would be enhanced by integrating global positioning (GPS) technology in future hardware and software products.

Forensic Application of FM-CW and Pulse Radar

Ground-penetrating radar (GPR) technology has supplied vital assistance in criminal investigations. However, law enforcement personnel desire further developments such that the technology is rapidly deployable, and that it provides both a simple user interface and sophisticated target identification. To assist in the development of target identification algorithms, our efforts involve gathering background GPR data for the various site conditions and circumstances that often typify clandestine burials. For this study, forensic anthropologists established shallow-grave plots at The University of Tennessee Anthropological Research Facility (ARF) that are specific to GPR research. These plots contain donated human cadavers lying in various configurations and depths, surrounded by assorted construction material and backfill debris. We scanned the plots using two GPR technologies: (1) a multi-frequency synthetic-aperture FM-CW radar (200–700 MHz) (GPR-X) developed by the U.S. Department of Energy’s Special Tech...

Comparison of Tractor Ground Speed Measurement Techniques

ABSTRACT PERFORMANCES of fifth wheel, front wheel, and single-beam radar vehicle ground speed sensors were evaluated on an agricultural tractor at operating speeds of 4, 7 and 10 km/h. Surface conditions included a smooth, non-deformable surface, soils subjected to various levels of tillage, and a range of vegetative covers. Based upon calibration values obtained for each sensor during tractor operation over the smooth, non-deformable surface, radar generally produced more accurate indications of true ground speeds than sensors with ground-contacting wheels. Coefficients of variation in indicated ground speed over time were also generally less for the radar unit than for either fifth wheel or front wheel units. The magnitude of the slip between the ground-contacting wheels and the tractive surface varied inversely with surface firmness. Thus, speed sensors having ground-contacting wheels should be calibrated for the specific surface conditions over which vehicle velocity measurement is to be obtained.

Mobilized Surveying of Soil Conductivity Using Electromagnetic Induction

Established and emerging geophysical technologies offer many promising applications for precise near–surface surveying. Scientists are investigating these non–invasive surveying techniques to enhance soil mapping and research. A non–invasive soil surveying system was developed to rapidly map soil characteristics. This system employs an all–terrain utility vehicle towing a nonmetallic carriage that cradles a commercially available ground conductivity meter. Autonomous data streams of time–stamped soil conductivity data and global positioning system (GPS) data are immediately downloaded to a computer after a survey. Both data sets are automatically merged using the time stamp data as an index. Using geographical information software (GIS), conductivity maps of increased data density are produced on–site. The mobile surveying system increased total conductivity sampling rate by a factor of >100, and increased data density by a factor of >10 over a conventional manual survey method when operating over a 1–ha open test site. For open fields that can be easily traversed with a utility vehicle, the mobile surveying system was found to greatly enhance data quality by increasing data density, and to dramatically increase both data acquisition efficiency and data post–processing speeds.

EVALUATING GPR AND EMI FOR MORPHOLOGICAL STUDIES OF LOESSIAL SOILS

Development of a rapid and nonintrusive method for obtaining accurate soil morphological information is critical for pinpointing areas that are prone to leaching. The purpose of this study was to evaluate the suitability of using ground-penetrating radar (GPR) and electromagnetic induction (EMI) techniques in combination to gather soil morphological information on loessial soils. A survey of apparent electrical conductivity (ECa) was conducted in southwestern Tennessee at 10-m increments throughout a 1-ha field. Based on variation in the EMI data, a 36-m transect was selected for further investigation by GPR using a 200-MHz antenna. A hydraulic excavator was used to trench the site to a depth of 3 m, and a complete soil morphological investigation was performed along the trench face at 6-m increments. Readings from the EMI showed a moderate correlation with percent fragic properties (r = 0.40). Average depth to the loess/alluvium interface interpreted from the GPR was 1.20 m, and to the alluvium/Tertiary sand interface, 1.88 m. The loess/alluvium and alluvium/Tertiary sand interfaces interpreted from the GPR data had strong relationships to the measured depths, R2 = 0.90 and 0.88, respectively. Results from this study show that using precursory EMI data to pinpoint GPR surveys is a precise, accurate, and rapid means of acquiring field-scale soil morphological information.

Investigation of a Fuzzy-Neural Network Application in Classification of Soils Using Ground-Penetrating Radar Imagery

Errors associated with visual inspection and interpretations of radargrams often inhibit the intensive surveying of widespread areas using ground-penetrating radar (GPR). To automate the interpretive process, this article presents an application of a fuzzy-neural network (F-NN) classifier for unsupervised clustering and classification of soil profiles using GPR imagery. The classifier clusters and classifies soil profile strips along a traverse based on common pattern similarities that can relate to physical features of the soil (e.g., number of horizons; depth, texture, and structure of the horizons; and relative arrangement of the horizons, etc.). This article illustrates this classification procedure by its application on GPR data, both simulated and actual. Results show that the procedure is able to classify the profile into zones that corresponded with the classifications obtained by visual inspection and interpretation of radar grams. Application of F-NN to a study site in southwest Tennessee gave soil groupings that are in close correspondence with the groupings obtained in a previous study, which used the traditional methods of complete soil morphological, chemical, and physical characterization. At a crossover value of 3.0, the F-NN soil grouping boundary locations fall within a range of 2.7 m from the soil groupings determined by the traditional methods. These results indicate that F-NN can supply accurate real-time soil profile clustering and classification during field surveys.

Searching for concealed human remains using GPR imaging of decomposition

Locating clandestine burials of human remains has long-challenged law-enforcement officials investigating criminal activity, and continues to confront scientific disciplines in finding well-defined procedures. Forensic specialists and law enforcement agencies have noted that multidisciplinary search efforts are becoming more of a necessity in searching for buried remains. Collaborative research at The University of Tennessees Anthropological Research Facility (ARF) in Knoxville supports this concept. We are correlating ground-penetrating radar (GPR) imaging with postmortem processes. Decompositional stages and rate imagery are presented that utilize sweep-frequency radar and time-elapsed imaging. Greater accuracy in predicting clandestine burials using dynamic GPR anomaly detection will reduce widespread excavations and may better assist law-enforcement personnel in obtaining site-specific search warrants.

Application of Fuzzy-Neural Network in Classification of Soils using Ground-penetrating Radar Imagery

Errors associated with visual inspection and interpretations of radargrams often inhibit the intensive surveying of widespread areas using ground-penetrating radar (GPR). To automate the interpretive process, this paper presents an application of a fuzzy-neural network (F-NN) classifier for unsupervised clustering and classification of soil profiles using GPR imagery. The classifier clusters and classifies soil profile strips along a traverse based on common pattern similarities that can relate to physical features of the soil (e.g., number of horizons; depth, texture and structure of the horizons; and relative arrangement of the horizons, etc). This paper illustrates this classification procedure by its application on GPR data, both simulated and actual real-world data. Results show that the procedure is able to classify the profile into zones that corresponded with those obtained by visual inspection and interpretation of radargrams. Results indicate that an F-NN model can supply real-time soil profile clustering and classification during field surveys.

Using Ground-Penetrating Radar to Evaluate Soil Compaction of Athletic Turfgrass Fields

Repairing a compacted turfgrass athletic field is a laborious activity, requiring significant expense. The objective of this project is to develop a rapid survey method for mapping soil compaction that occurs from player trafficking. Once mapped, field managers can target compacted regions of their fields for site-specific remediation; thereby, reducing their labor and expenses.