Autonomous engineering: a multi-scale GIS-based approach to green infrastructure design

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dc.contributor Cohen, Sagy
dc.contributor Elliott, Mark
dc.contributor Kumar, Mukesh
dc.contributor Nnaji, Chukwuma
dc.contributor.advisor Graettinger, Andrew
dc.contributor.author Greer, Ashton Danielle
dc.date.accessioned 2020-01-16T15:04:29Z
dc.date.available 2020-01-16T15:04:29Z
dc.date.issued 2019
dc.identifier.other u0015_0000001_0003479
dc.identifier.other Greer_alatus_0004D_13887
dc.identifier.uri http://ir.ua.edu/handle/123456789/6536
dc.description Electronic Thesis or Dissertation
dc.description.abstract This dissertation presents a new method called “Autonomous Engineering” that incorporates geographic information systems (GIS) to automatically design green stormwater infrastructure. The Autonomous Engineering framework aims to increase the efficiency at which green infrastructure is designed, thus promoting increased implementation. Green infrastructure design is a unique challenge in that it is multi-scale; planning and design considerations must be made at both the site-level and the watershed level by analyzing various types of spatial data. This framework presents a methodology for designing green infrastructure based on a combination of remotely sensed watershed-scale data and ultra-high resolution site-level Light Detection and Ranging (LiDAR) data. First, watershed level data is analyzed to generate site recommendations and quantify runoff characteristics. Second, LiDAR data is processed using both deep learning and machine learning frameworks so that site-level spatial features can automatically be recognized and extracted and so that an ultra high resolution digital elevation model (DEM) is generated. Next, linear referencing techniques are used to analyze terrain and identify geometric design recommendations. The results are finalized in the form of custom design drawings and reports. This work has outcomes for improved green infrastructure design workflows as well as the spatial analysis of robust site-level data for other applications. Future work includes the extension of these methodologies to applications beyond green infrastructure.
dc.format.extent 196 p.
dc.format.medium electronic
dc.format.mimetype application/pdf
dc.language English
dc.language.iso en_US
dc.publisher University of Alabama Libraries
dc.relation.ispartof The University of Alabama Electronic Theses and Dissertations
dc.relation.ispartof The University of Alabama Libraries Digital Collections
dc.relation.hasversion born digital
dc.rights All rights reserved by the author unless otherwise indicated.
dc.subject.other Civil engineering
dc.title Autonomous engineering: a multi-scale GIS-based approach to green infrastructure design
dc.type thesis
dc.type text
etdms.degree.department University of Alabama. Department of Civil, Construction, and Environmental Engineering
etdms.degree.discipline Civil, Construction and Environmental Engineering
etdms.degree.grantor The University of Alabama
etdms.degree.level doctoral
etdms.degree.name Ph.D.


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