Delineation of tile-drain networks using thermal and multispectral imagery—Implications for water quantity and quality differences from paired edge-of-field sites

Abstract

As part of the Great Lakes Restoration Initiative, paired edge-of-field sites were established in high priority subwatersheds to assess the effectiveness of agricultural management practices. One pairing was in Black Creek, a tributary to the Maumee River and Lake Erie. These fields were paired because of similarity in soils, topography, and agricultural management. Following two years of baseline data collection from these fields, consistent differences in water quantity and quality were observed for tile networks draining the fields, despite these fields being adjacent and managed together. Consequently, it was hypothesized that differences in subsurface water movement, specifically tile-drain density and connectivity, were the source of the observed differences. Our objective was to map the tile-drain network using remote sensing methodology in order to improve the understanding of nutrient and water transport as well as management on these fields. A combination of multispectral and thermal imagery, collected in spring of 2017, was incorporated to delineate the tile-drain network within each field. This imagery led to locating a cracked tile, which provided a direct path for overland flow to enter the tile-drain system and suggested that a tile-drain segment under the road connected the two fields. A ground-penetrating radar survey verified multiple tile locations, including the tile segment under the road. The distribution of these tiles helps explain the difference in water quantity and quality in the two fields.

Improved Accuracy of High-Throughput Phenotyping From Unmanned Aerial Systems by Extracting Traits Directly From Orthorectified Images

“…where Thermal IR is the pixel value within the thermal infrared band of the GeoTiff image, T is the absolute temperature measurement in Celsius degrees, and K and T 0 are constant parameters. In this study, K and T 0 were set as 0.04 and −273.15 (Flir Systems Inc., 2017; Williamson et al, 2019;Song and Park, 2020).…”

Mapping of Agricultural Subsurface Drainage Systems Using Unmanned Aerial Vehicle Imagery and Ground Penetrating Radar

“…Recent technological advancements in remote sensing enabled unmanned aerial vehicles (UAVs) and their compatible cameras—visible-color (VIS-C), multispectral (MS), and thermal infrared (TIR)—to become affordable. A few recent studies [ 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 ] explored the potential of UAV imagery for subsurface drainage mapping. However, more work is warranted in this direction as the research is still in a beginning stage, with ideal conditions based on soil type, crop residue, tillage practice, ground wetness level, and prior rainfall event for carrying out the UAV surveys for subsurface drainage mapping not yet fully understood.…”

“…Consequently, given bare ground conditions, lighter shaded dry soil surface features (i.e., increased reflected radiation) that are linear may be representative of drain lines as the dry soil surfaces reflect more visible (VIS) and near-infrared (NIR) EM radiation than wet soil surfaces [ 56 , 57 ]. This makes VIS-C and MS (green, red, red edge, and NIR wavelength bands) cameras a suitable choice for subsurface drainage mapping [ 40 , 42 , 44 , 57 ]. In addition, soil water content variation can result in emitted TIR radiation differences explained by the difference in thermal inertia between dry and wet soils due to the high specific heat capacity and low thermal conductivity of water resulting in a temperature difference [ 58 , 59 , 60 ].…”

Locating drainage tiles at a wetland restoration site within the Oak Openings region of Ohio, United States using UAV and land based geophysical techniques

“…In the absence of such maps, locating these drainage tiles by traditional probing using exible metal rod and excavations are tedious and destructive (Ruark et al, 2009). The use of non-invasive techniques including vegetation analysis (Tlapáková et al, 2015), aerial photographs, remote sensing (Williamson et al, 2019) and geophysical methods such as ground penetrating radar (Allred et al, 2004;Chow and Rees, 1989;Koganti et al, 2020) if applicable, provide a more e cient approach for locating the tiles. This study further evaluates the use of both unmanned aerial vehicle (UAV)-based visible and thermal infrared imaging and land-based ground penetrating radar for locating drainage tiles and mapping their network at a large eld scale within the Oak Openings Region of Northwestern Ohio.…”