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Title Remote sensing & GIS applications for drainage detection and modeling in agricultural watersheds
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Publication Date
University/Publisher IUPUI
Abstract

Indiana University-Purdue University Indianapolis (IUPUI)

The primary objective of this research involves mapping out and validating the existence of sub surface drainage tiles in a given cropland using Remote Sensing and GIS methodologies. The process is dependent on soil edge differentiation found in lighter versus darker IR reflectance values from tiled vs. untiled soils patches. Data is collected from various sources and a primary classifier is created using secondary field variables such as soil type, topography and land Use and land cover (LULC). The classifier mask reduces computational time and allows application of various filtering algorithms for detection of edges. The filtered image allows an efficient feature recognition platform allowing the tile drains to be better identified. User defined methods and natural vision based methodologies are also developed or adopted as novel techniques for edge detection. The generated results are validated with field data sets which were established using Ground Penetration Radar (GPR) studies. Overlay efficiency is calculated for each methodology along with omission and commission errors. This comparison yields adaptable and efficient edge detection techniques which can be used for similar areas allowing further development of the tile detection process.

Subjects/Keywords Remote Sensing, GIS; Geographic information systems  – Remote sensing; Hydrology  – Indiana  – Hancock County  – Remote sensing; Hydrology  – Data processing; Drainage  – Research  – Analysis; Water resources development  – Indiana  – Hancock County  – Remote sensing; Watershed management  – Indiana  – Hancock County  – Remote sensing; Ground penetrating radar; Artificial satellites in geographical research; Ecohydrology; Orthophotography  – Indiana  – Hancock County  – Remote sensing; Orthophotomaps; Landforms  – Measurement; Land use  – Indiana  – Hancock County  – Maps; Vector analysis; Spatial analysis (Statistics); Remote sensing  – Data processing; Image processing  – Maps
Contributors Li, Lin; Bayless, E. Randall (Edward Randall), 1961-; Jacinthe, Pierre-André
Language en
Country of Publication us
Record ID handle:1805/4086
Repository iupui
Date Retrieved
Date Indexed 2018-09-07

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…Fig 4. 30m Resolution NASS LULC and Confidence imagery and 1m CIR and classified LULC product ........................................................................18 Fig 5. Overview of data Analysis and processing

…severely limited by the time frame of the data collected. Among image processing and edge detection methods mentioned above, none of the methodologies used are truly automatic when it comes to detection and vectorization. When dealing with regular tile…

…Both raster and vector data sets were georeferenced to maintain consistency in the analyzed data and the processing which would follows. Table 7. Vector Layer with attribute Data for secondary feature analysis Source HANCOCK Co. Office USGS Vector…

…15 Table 5. NAIP Color Infrared Imagery characteristics and resolution ..............................16 Table 6. DOQQ Imagery characteristics and resolution (Source: USGS) .........................16 Table 7. Vector layer with attribute data

…the focus of the current study. The location information of these tile drain systems are limited and the tile drain placement layouts are complex, making detection of subsurface systems a valuable tool in assessment of field hydrology and in…

…Converted Partially Converted Total Acres % 25,023.05 79.20% 7,895.24 57.12% 32,918.29 72.48% However, there are concerns about the watershed hydrology and water quality (Naz and Bowling, 2008). The interactions between groundwater…

…resolution of about 1m. This CIR based study suggested that the image used by Verma et al. (1996) had uniformly light gray tone and indicated drainage stresses more efficiently. Varner (2003) used RDACSII multispectral sensor data, and the…

…RDACSH3 hyperspectral data with 120 bands from 471 to 828nm which was used to simulate IKONOS data. The multispectral and simulated data at a spatial resolution of 1m was suitable for discerning these drainage features, but limited in temporal scale owing…

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