NS43B-1971
Detecting Subsurface Agricultural Tile Drainage using GIS and Remote Sensing Technique

Thursday, 17 December 2015
Poster Hall (Moscone South)
Milan Budhathoki1, Kemal Gokkaya1, Jennifer L. Tank1, Sheila F Christopher2 and Brittany Hanrahan1, (1)University of Notre Dame, Notre Dame, IN, United States, (2)Notre Dame, South Bend, IN, United States
Abstract:
Subsurface tile drainage is a common practice in many of the row crop dominated agricultural lands in the Upper Midwest, which increases yield by making the soil more productive. It is reported that nearly half of all cropland in Indiana benefits from some sort of artificial drainage. However, subsurface tile has a significant negative impact on surface water quality by providing a fast means of transport for nutrients from fertilizers. Therefore, generating spatial data of tile drainage in the field is important and useful for agricultural landscape and hydrological studies. Subsurface tile drains in Indiana’s croplands are not widely mapped. In this study, we will delineate subsurface tile drainage in agricultural land in Shatto Ditch watershed, located in Kosciusko County, Indiana. We will use geo-spatial methodology, which was purposed by earlier researchers to detect tile drainage. We will use aerial color-infrared and satellite imagery along with Light Detection and Ranging (LiDAR) data. In order to map tile lines with possible accuracy, we will use GIS-based analysis in combination with remotely sensed data. This research will be comprised of three stages: 1) masking out the potential drainage area using a decision tree rule based on land cover information, soil drainage category, surface slope, and satellite image differencing technique, 2) delineate tile lines using image processing techniques, and 3) check the accuracy of mapped tile lines with ground control points. To our knowledge, this study will be the first to check the accuracy of mapping with ground truth data. Based on the accuracy of results, we will extend the methodology to greater spatial scales. The results are expected to contribute to better characterizing and controlling water pollution sources in Indiana, which is a major environmental problem.