Soil erosion has significant and serious consequences for both humanity and the environment (Adhikari & Nadella, 2011). Poor agricultural practices are a major contributor to soil erosion, and tillage is considered the greatest “on-site force” to soil erosion (Ritter, 2012; Montgomery, 2007). Tillage operations consist of using plows, cultivators and other methods that physically disturb the soil in order to prepare it for planting or seeding (Hofmann, 2015). As noted by Aletto et al. (2010), humans have been tilling land for millennia, but only in the last two centuries have the advancements in tilling efficiency and effectiveness begun to cause economic and ecological stress, which humanity is only beginning to address. With the intensification of agricultural activity globally, agricultural productivity is being impeded by increased soil erosion due to poor tilling practices (Alletto et al. 2010). Poor tilling practices are also ecologically damaging as pesticides, fertilizers, and fine sediment can be transported into local waterways by surface runoff (Potter et al. 2015). Actively tilling redistributes the top soil, causing soil organic content to be lost and soil structure to be destroyed (Ritter, 2012).
In Ontario, the Ontario Ministry of Agriculture, Food and Rural Affairs (OMAFRA) has estimated that soil erosion rates have increased ten to twenty percent in the last decade (OMAFRA, 2016a). As a consequence of increased soil erosion, efforts to monitor and educate farmers to have better soil management practices are needed (OMAFRA, 2016a). In response to increasing soil erosion, farmers have transitioned to no-till practices that ensure that no crop residue is turned over, which increases the soil organic content (Hofmann, 2015). Both types of tillage practices can be compared in Figure 2 below which shows that the no-till field has not been shaped into furrows, therefore reducing soil loss and improving soil stability (Buffett, 2012). Government organizations such as OMAFRA seek to identify the tilling practices used by landowners and farmers in order to develop erosion assessment tools (OMAFRA, 2016a). If these data are gathered in the long-term, the consequences of standard tilling practices can be better understood (OMAFRA, 2016a).
Figure 1 - Conventional tillage field (left) vs. no-till field (right) (Ritter, 2012)
The first step of this process would be to identify which farms in Ontario use till or no-till practices. This information could be difficult to gather if done through conventional surveying practices, as the time and resources required to complete the survey would be impractical. Utilizing remote sensing technologies would be a more efficient way to gather this information. OMAFRA has proposed using remote sensing to collect information concerning soil and its characteristics in order to combat soil erosion within Ontario (OMAFRA, 2016a). A potential obstacle to utilizing remote sensing technology is that the data must be at a very fine spatial resolution in order to reveal landscape features such as furrows and ridges caused by active tillage (OMAFRA, 2016a).
Light Detection and Ranging (LiDAR) is one remote sensing technology that has the potential of imaging furrows and ridges within a landscape due to its very fine spatial resolution (NOAA, 2012). Airborne LiDAR works by emitting a laser pulse towards the earth from an airborne platform (such as a helicopter or small plane). The time the pulse takes to return to the sensor is measured and is converted into a spatial datapoint with fields concerning its X, Y, and Z coordinates as well as the intensity of its return to the scanner. A single pulse from a LiDAR scanner can have multiple returns as the emitted pulse can reflect off of multiple surfaces. This emission-return sequence occurs at a very high frequency, which in turn creates a very fine resolution spatial dataset (NOAA, 2012). The Ontario Ministry of Natural Resources and Forestry (OMNRF) and OMAFRA are in the process of releasing a large LiDAR dataset for the areas of Cochrane, Peterborough, and Soutwestern Ontario with a precision of +/- 5cm (OMNRF, 2017). These datasets have many applications within earth sciences and engineering (NOAA, 2012). This project develops a model to identify furrows and ridges using a LiDAR dataset in order to determine whether till or no-till practices are in use. Organizations such as OMAFRA could use this information and model for the purpose of addressing agricultural soil erosion and the subsequent issues that can arise from frequent tillage practices.
Purpose of Research
This study designs and implements a remote sensing-based framework to identify furrows in Northumberland County using digital elevation models derived from LiDAR data.