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Identification of Sewage Sludge Injection Application on Harvested Agricultural Fields Using Landsat TM Data

Jiang, Yitong
http://rave.ohiolink.edu/etdc/view?acc_num=toledo1290201856

Abstract Details

2010, Master of Arts, University of Toledo, Geography.
Application of sewage sludge to agriculture fields is used by farmers to improve the soil conditions, physically, chemically and organically. However, it has potential risk to public health and the environment because of the heavy metals, nutrients and pathogens that may be included in biosolids. The location of all applications of sewage sludge is not known because some records of application are missing. Remote sensing technology has been shown to be an effective way to detect surface application of sewage sludge on agricultural fields for different times of year over large areas. The main objective of this study is to determine if Landsat TM data can be used to identify harvested agricultural fields that have had sewage sludge applied through injection. The spectral characteristics were compared between sewage sludge injection applied fields and control fields, including the following spectral ratios: R(7,5), R(5,4) and R(3,2). Landsat TM images from path 20, row 31 from 2003 to 2007 were selected in this study, and the sewage sludge injection application data in Oregon, Ohio were mapped with the images. The results show that there are spectral differences between fields that had sewage sludge injected and control fields that have not received sewage sludge. Band 4, band5 and band 7 show more differences than other bands. The differences are detectable up to 10 to 18 days after sewage sludge injection. The ratio combinations of R(7,5), R(5,4) and R(3,2), respectively, in blue, green and red can be used to identify sample sewage sludge application fields through injection. The fields with sewage sludge injected appear gray, and the control fields appear yellow. A pixel from a ratio combination image is representing a spot in sewage sludge injected fields, when it meets all the three conditions: R(3,2) value is in the confidence interval of 1.651 to 1.665, R(5,4) value is in the confidence interval of 1.941 to 1.981, and R(7,5) value is in the confidence interval of 0.561 to 0.569, at 95% confidence level.
Kevin Czajkowski, PhD (Committee Chair)
Patrick Lawrence, PhD (Committee Member)
David Nemeth, PhD (Committee Member)
Bhuiyan Alam, PhD (Committee Member)
114 p.
Agriculture; Environmental Studies; Geography; Public Health
Landsat TM; remote sensing; sewage sludge; biosolids

Recommended Citations

Citations

  • Jiang, Y. (2010). Identification of Sewage Sludge Injection Application on Harvested Agricultural Fields Using Landsat TM Data [Master's thesis, University of Toledo]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1290201856

    APA Style (7th edition)

  • Jiang, Yitong. Identification of Sewage Sludge Injection Application on Harvested Agricultural Fields Using Landsat TM Data. 2010. University of Toledo, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=toledo1290201856.

    MLA Style (8th edition)

  • Jiang, Yitong. "Identification of Sewage Sludge Injection Application on Harvested Agricultural Fields Using Landsat TM Data." Master's thesis, University of Toledo, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1290201856

    Chicago Manual of Style (17th edition)

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© 2010, all rights reserved.
This open access ETD is published by University of Toledo and OhioLINK.
Release 3.2.12