Phillip Lanza, Stacia Davis Conger, Jeffrey Beasley, Thanos Gentimis and Don La Bonte
Changing agroclimatic conditions and the increasing world population present various challenges to maintaining long-term food security. As such, improvements to agricultural production efficiencies achieved through technological advancements have become valuable. Studies have shown precision agriculture techniques reduce pesticide applications by 8%-10%, improve nitrogen use efficiency by 51%-97%, increase yields by 10% and improve farm profitability for various commodity crops.
Spatial analysis of field topography is an area showing tremendous potential for agricultural applications under Louisiana’s agroclimatic conditions. Even minimal changes in field elevations have been found to affect both soil hydrology and nutrient mobility and availability, both of which strongly influence crop yields. Better hydrological and fertility perspectives can lead to improved management decisions that decrease production costs. Continued advancements in spatial measurement and data integration are expected to lead to further increases in resource use efficiency.
Field elevations were traditionally measured manually using surveying equipment or ground-based technologies, such as vehicle-mounted global navigation satellite system receivers. More recently, remote sensing technologies, such as Laser Imaging Detection and Ranging (LIDAR) have become more readily available. Aerially collected LIDAR shows tremendous potential for surface elevation measurement compared to other technologies because of its ability to provide accurate, high precision and high-resolution data. It also eliminates the need to navigate terrestrial obstacles, such as vegetation and bodies of water, while collecting data.
Statewide elevation data is collected by LIDAR-equipped airplanes as part of Louisiana’s frequent natural disaster response needs; however, this is cost-prohibitive for farmers needing field level accuracy. Data resolution is also limited by high aircraft speeds.
The combination of LIDAR sensor miniaturization and improvements to unmanned aerial vehicle (UAV) technology have allowed UAVs, which are commonly known as drones, to collect high resolution LIDAR elevation data. UAVs are less expensive to operate and maintain than airplanes and are capable of producing data with increased resolution because they can operate at much lower speeds and elevations. This has greatly reduced operation costs and provided increased data collection flexibility. Greater use of this technology is expected to occur over time, empowering more stakeholders to obtain high-resolution elevation maps for their areas of interest.
The power of high-resolution LIDAR elevation data becomes clear in relatively flat areas subject to variable rainfall, irrigation or intermittent flooding issues. Small changes in elevation affect how water flows across agricultural fields, making gravity-fed irrigation methods less efficient due to poor uniformity. Employing UAV-mounted LIDAR sensors to collect elevation data within and adjacent to fields provides a more complete picture of topographical feature effects and helps to maximize water use management. This information can allow more efficient selection and placement of best management practices (BMP). For example, buffer strips that filter surface runoff to improve water quality and minimize erosion can be installed in key locations where drainage naturally occurs rather than surrounding the entire field.
LSU AgCenter scientists conducted a study in 2021 to determine the optimum UAV flight altitudes for mapping specialty crop fields in northeastern Louisiana. Data were collected over two fields using UAV-mounted LIDAR sensors at 40-, 50- and 60-meter altitudes, with lower altitudes producing higher resolution LIDAR datasets. A higher altitude is advantageous given a faster flight time and lower computing and labor expenses if resolution is nearly the same.
Elevation data were spatially analyzed to determine statistical significance between digital elevation models (DEMS) generated from data collected at each altitude. It was determined that no significant differences existed between digital elevation models. Therefore, flying at an altitude of 60 meters provides greater efficiency with lower operational costs for UAV LIDAR data collection. The figures complementing this article show color enhanced side-by-side digital elevation models of two specialty crop fields collected at each elevation.
The two site maps clearly identify low lying areas within the fields and where each field drains to the natural environment. Figure 1 indicates westward movement of water due to the leveed bayou on the eastern field border. There are four to five areas of dark color on the western border where drainage is already being channeled; the implementation of best management practices should be focused in those areas. Similarly, Figure 2 indicates that most drainage occurs in the southeast portion of the field where a naturally occurring bayou exists. Implementation of best management practices should be focused on the two southeastern corners where drainage naturally occurs.
The elevation maps provide valuable information to stakeholders when making decisions involving irrigation and drainage and when strategizing implementation designs of various best management practices. Use of this technology will likely increase as sensor and UAV costs decrease and greater education occurs regarding applicability. Determining optimized flight characteristics during data collection, which was done in this study, will further reduce associated costs. This will likely lead to more continuous, more complete high-resolution elevation data coverage as more people use this technology.
Phillip Lanza is a doctoral student at Cornell University. He completed a Master of Science degree in precision agriculture in 2021. Stacia Davis Conger is an assistant professor and irrigation specialist at the AgCenter Red River Research Station. Jeffrey Beasley is a professor in the AgCenter School of Plant, Environmental and Soil Sciences. Thanos Gentimis is an assistant professor in the AgCenter Experimental Statistics Department and Don La Bonte is a professor in and director of the School of Plant, Environmental and Soil Sciences.
This article appeared in the summer 2022 issue of Louisiana Agriculture.
Figure 1. Digital elevation maps of a specialty crop field were created from LIDAR point cloud data collected at 40 meters, 50 meters and 60 meters. Darker colors are lower elevations. Because no significant differences exist between digital elevation models, flying at an altitude of 60 meters provides greater efficiency with lower operational costs for UAV LIDAR data collection. Figure by Phillip Lanza
Figure 2. Digital Elevation Maps of a specialty crop field created from LIDAR point cloud data collected at 40m, 50m, and 60m. Darker colors are lower elevations. Figure by Phillip Lanza