Determining Surface Infiltration Rate of Permeable Pavements with Digital Imaging

Simple item page
dc.contributor.authorValeo, Caterina
dc.contributor.authorGupta, Rishi
dc.date.accessioned2018-03-30T15:34:39Z
dc.date.available2018-03-30T15:34:39Z
dc.date.copyright2018en_US
dc.date.issued2018-01
dc.description.abstractCell phone images of pervious pavement surfaces were used to explore relationships between surface infiltration rates (SIR) measured using the ASTM C1701 standard test and using a simple falling head test. A fiber-reinforced porous asphalt surface and a highly permeable material comprised of stone, rubber and a polymer binder (Porous Pave) were tested. Images taken with a high-resolution cellphone camera were acquired as JPEG files and converted to gray scale images in Matlab® for analysis. The distribution of gray levels was compared to the surface infiltration rates obtained for both pavements with attention given to the mean of the distribution. Investigation into the relationships between mean SIR and parameters determined from the gray level distribution produced in the image analysis revealed that mean SIR measured in both pavements were proportional to the inverse of the mean of the distribution. The relationships produced a coefficient of determination over 85% using both the ASTM and the falling head test in the porous asphalt surface. SIR measurements determined with the ASTM method were highly correlated with the inverse mean of the distribution of gray levels in the Porous Pave material as well, producing coefficients of determination of over 90% and Kendall’s tau-b of roughly 70% for nonparametric data.en_US
dc.description.reviewstatusRevieweden_US
dc.description.scholarlevelFacultyen_US
dc.description.sponsorshipThis research was supported by the University of Victoria, the Canadian Foundation for Innovation, and the National Science and Engineering Research Council of Canada. The authors would also like to thank the generous in-kind donation of Porous Pave Incorporated, Island Asphalt, Brico Services, Butler Brothers, The Grounds Department within Facilities Management at the University of Victoria, graduate students Zhiying Xu and Fahad Shazad for assistance in collecting data as well as undergraduate students Mitch Jernslet, Brendan Kumar,Adrian Hou, Erin Janzen, Scott Jensen, and Laura Smandel.en_US
dc.identifier.citationValeo, C. & Gupta, R. (2018). Determining Surface Infiltration Rate of Permeable Pavements with Digital Imaging. Water, 10(2), 133. http://dx.doi.org/10.3390/w10020133en_US
dc.identifier.urihttp://dx.doi.org/10.3390/w10020133
dc.identifier.urihttp://hdl.handle.net/1828/9184
dc.language.isoenen_US
dc.publisherWateren_US
dc.subjectpermeable pavements
dc.subjectporous asphalt
dc.subjectimage analysis
dc.subjectclogging
dc.subjectsurface infiltration rates
dc.subjectASTM C1701 method
dc.subjectfalling head test
dc.subjectimage analysis
dc.subject.departmentDepartment of Mechanical Engineering
dc.subject.departmentDepartment of Civil Engineering
dc.titleDetermining Surface Infiltration Rate of Permeable Pavements with Digital Imagingen_US
dc.typeArticleen_US

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Valeo_Caterina_Water_2018.pdf
Size:
5.24 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Faculty and Staff Publications
 
University of Victoria Libraries

We acknowledge and respect the Lək̓ʷəŋən (Songhees and Esquimalt) Peoples on whose territory the university stands, and the Lək̓ʷəŋən and W̱SÁNEĆ Peoples whose historical relationships with the land continue to this day.