2026-09-22T08:54:00Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/88213 2023-07-11 col_2142_5131 col_2142_14770 com_2142_5130 com_2142_3518 com_2142_234

Peschel, Joshua Rutherford, Cassandra Depwe, Elizabeth E. 2015-09-29T20:50:18Z 2015-09-29T20:50:18Z 2017-09-30T09:15:32Z 2015-08 2015-07-17 2015-8 This thesis presents a machine vision procedure to identify and extract storm drain locations from natural images along surface street curbsides. Existing storm drain infrastructure information is commonly reposed by managing agencies in either paper or digital format. Access to these data for urban hydrologic and hydraulic modeling purposes may be limited by security protocols and/or the format in which the data may be available. The procedure described in this work uses a novel vision algorithm with Google Street View imagery to identify and extract the locations of curbside storm drains. Results are converted into a tabular format that can be converted into geometric input files for modeling purposes. This fast, approximation approach to assembling storm drain data could be of interest to public works managers, urban hydrology and hydraulics practitioners and researchers, and citizen scientists, to improve general understanding of the civil and environmental infrastructure. Submission published under a 24 month embargo labeled 'U of I only', the embargo will last until 2017-08-01 The student, Elizabeth Depwe, accepted the attached license on 2015-07-17 at 11:39. The student, Elizabeth Depwe, submitted this Thesis for approval on 2015-07-17 at 11:58. This Thesis was approved for publication on 2015-07-17 at 13:24. DSpace SAF Submission Ingestion Package generated from Vireo submission #8528 on 2015-09-29 at 15:00:42 Made available in DSpace on 2015-09-29T20:50:18Z (GMT). No. of bitstreams: 3 DEPWE-THESIS-2015.pdf: 2144726 bytes, checksum: 1e5edc5211f4222c3da43bbbeebdd47f (MD5) DEPWE_Thesis_Code.zip: 15698488 bytes, checksum: c3f9bde5871153f0fc47d55ded01f601 (MD5) LICENSE.txt: 4212 bytes, checksum: 2e014d8a133dd72c76ffca9794934680 (MD5) Previous issue date: 2015-07-17 Embargo set by: Seth Robbins for item 89493 Lift date: 2017-09-29T20:50:34Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system U of I Only Restriction Lifted for Item 89493 on 2017-09-30T09:15:32Z. application/pdf http://hdl.handle.net/2142/88213 en Copyright 2015 Elizabeth E. Depwe infrastructure assessment computer vision Google Street View data mining stormwater management image detection image processing Extracting curbside storm drain locations from street-level images text text Civil & Environmental Engineering Civil Engineering University of Illinois at Urbana-Champaign Thesis M.S.