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Xi-DissertationApril2017.pdf (8.61 MB)

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Use of LiDAR in Object-based Classification to Characterize Brownfields for Green Space Conversion in Toledo

Li, Xi
http://rave.ohiolink.edu/etdc/view?acc_num=toledo1493417634359152

Abstract Details

2017, Doctor of Philosophy, University of Toledo, Spatially Integrated Social Science.
One of the fundamental but critical barriers of brownfields redevelopment (BR) is the lack of information on the brownfield locations. Planners, policy-makers and developers need to know this information before they can create effective policies and legislation for redevelopment. However, relatively few studies have been conducted on creating effective methods to identify brownfield sites and to provide decision support for BR. Brownfileds' information is still collected with traditional methods using a combination of tax record information, site visits, and other records, which is typically a time and labor consuming process. This study used the City of Toledo as a case study to explore an efficient method to identify brownfields automatically as a part of the brownfields inventory and then determine the best use for that parcel. Based on object-based classification, this study made a map of potential brownfields using LiDAR imagery and Color-Infrared (CIR) imagery using the eCognition software. Then, a GIS-based land use suitability analysis model (LSAM) for green space was created using the brownfield layer in addition to proximity to residences, air/noise pollution, high land surface temperature to explore which brownfields could be converted into green spaces in Toledo.
Kevin Czajkowski, Ph.D (Committee Chair)
Wentworth B. Clapham, Ph.D (Committee Member)
Daniel J. Hammel, Ph.D (Committee Member)
Sujata Shetty, Ph.D (Committee Member)
Sumei Zhang, Ph.D (Committee Member)
125 p.
Environmental Management; Geographic Information Science; Remote Sensing; Urban Planning
Object-based Classification, LiDAR, Urban Land Use Cover Classification, GIS-based Land Use Suitability Model, eCognition, Brownfields, Green Spaces

Recommended Citations

Citations

  • Li, X. (2017). Use of LiDAR in Object-based Classification to Characterize Brownfields for Green Space Conversion in Toledo [Doctoral dissertation, University of Toledo]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1493417634359152

    APA Style (7th edition)

  • Li, Xi. Use of LiDAR in Object-based Classification to Characterize Brownfields for Green Space Conversion in Toledo . 2017. University of Toledo, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=toledo1493417634359152.

    MLA Style (8th edition)

  • Li, Xi. "Use of LiDAR in Object-based Classification to Characterize Brownfields for Green Space Conversion in Toledo ." Doctoral dissertation, University of Toledo, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1493417634359152

    Chicago Manual of Style (17th edition)

toledo1493417634359152
587
© 2017, all rights reserved.
This open access ETD is published by University of Toledo and OhioLINK.