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Mapping of Tile Drains in Hoagland Watershed for Simulating the Effects of Drainage Water Management

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  2007 ASAE Annual Meeting  072144.(doi:10.13031/2013.23549)
Authors:   Srinivasulu Ale, Bibi S Naz, Laura C Bowling
Keywords:   Tile drains, mapping, decision tree, aerial photograph, edge enhancement, filter

Detailed location maps of tile drains in the Midwestern states of the United States are generally not available as the tile lines in these areas were laid more than 75 years ago. The objective of this study is to map tile drains in the Hoagland watershed in west--central Indiana using image processing tools such as decision tree classification and edge enhancement techniques applied to multiple spatial datasets. A decision tree classifier model that utilizes land cover, soil drainage, and surface slope data sets was used to classify the watershed into 'potential tile drained' and 'potential non--tiled' areas. After masking out the potential non--tiled areas from the aerial photograph, image processing techniques were used to create a detailed tile location map of the watershed. First difference horizontal and vertical filters were applied to enhance the edges that represent tiles and the edge enhanced images were classified in to 'tile' and 'no--tile' areas using density slice classification. Post--classification methods were applied to reclassify erroneous pixels. From the tile line map of the watershed, drain spacings in different parts of the watershed were estimated. The decision tree identified 79% of the watershed as potential tile drained area while the image processing techniques predicted tiles in 73% of the watershed. The average drain spacing in five subwatersheds varied from 41 to 43 m, which is within the recommended drain spacing of 23--45 m for the soils in this area. In general, the techniques used for mapping tile lines gave reasonably good results and hence are useful to detect tile lines from aerial photographs in large areas.

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