In this study we determine the areal footprint of parking lots in the  Great Lakes Basinand outline policies to provide smart growth of  parking lots. Our poster addresses the question: “what is the areal  footprint and the ensuing economic and ecological consequences of  parking lots?”. Our research addresses whether land use in the in the  Great Lakes is efficient and sustainable. To that end, we use high  resolution aerial photography and GIS to estimate the areal footprint of  parking lots in relationship to: (1) the total urban area; (2) the number  of parking spaces versus the population of the county; and (3) the  distribution of parking spaces by land use category for a high density  urban cover portion of the study area. Finally, we develop a set of  metrics useful to relate our findings to urban planners and county  regulators and 4) we outline the necessary steps to extrapolate our  findings to the United States scale and from that draw conclusions as  to a possible sustainable path to controlled growth

Davis, Amélie Y

Kidwell, Paul B

Pijanowski, Bryan C

Robinson, Kimberly D

English

In this study we determine the areal footprint of parking lots in the Great Lakes Basinand outline policies to provide smart growth of parking lots. Our poster addresses the question: “what is the areal footprint and the ensuing economic and ecological consequences of parking lots?”. Our research addresses whether land use in the in the Great Lakes is efficient and sustainable. To that end, we use high resolution aerial photography and GIS to estimate the areal footprint of parking lots in relationship to: (1) the total urban area; (2) the number of parking spaces versus the population of the county; and (3) the distribution of parking spaces by land use category for a high density urban cover portion of the study area. Finally, we develop a set of metrics useful to relate our findings to urban planners and county regulators and 4) we outline the necessary steps to extrapolate our findings to the United States scale and from that draw conclusions as to a possible sustainable path to controlled growth

Pijanowski, Brian C.

Robinson, Kimberly D.

Kidwell, Paul B.

Purdue E-Pubs

Purdue UniversityPurdue e-PubsGIS Day GIS, Geoinformatics, and Remote Sensing atPurdue11-14-2007Estimating the parking lot footprint across theGreat Lakes regionAmélie Y. DavisPurdue University, amelie@purdue.eduBryan C. PijanowskiPurdue UniversityKimberly D. RobinsonPurdue UniversityPaul B. KidwellPurdue UniversityFollow this and additional works at: http://docs.lib.purdue.edu/gisdayThis document has been made available through Purdue e-Pubs, a service of the Purdue University Libraries. Please contact epubs@purdue.edu foradditional information.Davis, Amélie Y.; Pijanowski, Bryan C.; Robinson, Kimberly D.; and Kidwell, Paul B., "Estimating the parking lot footprint across theGreat Lakes region" (2007). GIS Day. Paper 3.http://docs.lib.purdue.edu/gisday/3IntroductionResultsMethodsDiscussion and ConclusionsEstimating the parking lot footprint across the Great Lakes regionAmélie Y. Davis1, Bryan C. Pijanowski1, Kimberly D. Robinson1, Paul B. Kidwell21Department of Forestry and Natural Resources, 2Department of Statistics, 1,2Purdue University, West Lafayette IN, 47907For further information contact bpijanow@purdue.edu or visit http://www.human-environment.orgBrief Literature Review234 56Abstract1In this study we determine the areal footprint of parking lots in the Great Lakes Basin and outline policies to provide smart growth of parking lots.  Our poster addresses the question: “what is the areal footprint and the ensuing economic and ecological consequences of parking lots?”. Our research addresses whether land use in the in the Great Lakes is efficient and sustainable.  To that end, we use high resolution aerial photography and GIS to estimate the areal footprint of parking lots in relationship to: (1) the total urban area; (2) the number of parking spaces versus the population of the county; and (3) the distribution of parking spaces by land use category for a high density urban cover portion of the study area .  Finally, we develop a set of metrics useful to relate our findings to urban planners and county regulators and 4) we outline the necessary steps to extrapolate our findings to the United States scale and from that draw conclusions as to a possible sustainable path to controlled growth.   The primary objective is to quantify the arealfootprint of parking lots (PL) on a national scale which would create the basis for proper parking lot regulation.  Develop an appropriate methodology for applying our very detailed knowledge of the landscape at a small scale to the large scale. Determine the PL footprint of Tippecanoe Co, then scale up. Propose sound policy measures for future parking lot construction and current PL modifications.• Asphalt and concrete both contribute to lower-atmosphere warming both during the day and at night (Eliasson, 1996)• Planning for PL size is for the busiest day of the year such as the day after Thanksgiving for shops, Easter or Christmas service for churches. (Shoup 1997)• Runoff off of PL is very toxic (Greenstein et al. 2004)• “Expanses of open asphalt impact hydrology and climate across city space.” Such hydrological impacts could include increased flooding of downstream locations, increased water flow which could lead to increased sedimentation in streams and rivers, and larger non-point pollution loads (Jackle & Sculle 2005). Future work includes comparing urban zip codes to suburban and rural zip codes.We will compare our estimation of parking lots to urban sprawl indices.Next steps include applying our methodology to the conterminous United States. In order to have uniform data we plan to use the DMSP/OLS Nighttime lights data to locate urban clusters(Elvidge et al, 1997)Randomly pick 30 zip codes from 3804 in the Great Lakes regionDigitize them using orthophotos (aerial photography) Digitization for the highly urban centers which consisted mostly of West Lafayette and Lafayette was done at the 1:1000 scale, In the rural areas of the county we combed through the aerial photography at 1:3500 scale.Assemble following data to use as predictors in multiple regression_ NAICS data  number of employees and establishments _ U.S. Census data  population and number of houses_ National Land Cover Data (NLCD)  for 2001 urban land useUnfortunately most of the variables were significantly autocorrelated.  The variable which had the highest correlation with the dependent variable was urban land use (Urb) as defined by the NLCD as low intensity to high intensity development intensity to high intensity development i.e. 20 to 100% off total land cover being impervious surface (Lowry, 2005).  Least Squares Model for multiple linear regression (N = 30)Model: (Parking lot area)1/3 = B1(Urb) + B2(Urb) + constantPL = (9.61x10-6 Urb – 1.08x10-9 Urb2/3 + 14.98) 3    F = 83.3p values (.014) (.000) (.003) (.000)Used Box Cox transformation to find best transformation of the dependent variable which stabilized the varianceWe had to fit data beyond sample data (about 1.84% of all our zip codes)Box Cox transformation Plot (left)Normal P-P Plot of Regression Standardized Residual (right)Detail of aerial photographyDigitized Parking lots on Purdue campus (purple outline)Note: Total area of parking lots at Purdue University slightly exceeds that of buildings (0.61sq km of buildings versus 0.67sq km of PL)Total Area Metrics (M.) – what is the total area of parking lots in case study area and as expressed as % of urban useEfficiency M. – how many parking spaces do we have per person, family, registered vehicle, etc. in the case study areaPerspective Size M. – relate the size of parking spaces to units general public understands (e.g., size of a football field)Replacement M. – what the current parking lot area could produce if it were used for another ecosystem serviceMETRICS Tippecanoe County Great Lakes RegionTotal Area of PL 5.6 sq km 1,260 sq km% total land use 0.44 0.00% urban land use 6.79 4.97# of football fields 1,075 239,531Bushels of Corn 237,490 52,936,433Gallons of Ethanol 641,223 142,928,368Spaces per car 1.9 1.9Spaces per family 5.6 4.6Spaces per capita 1.5 1.6The greatest PL concentration occurs around large urban centers like Chicago, IL and Indianapolis, IN (B) The zip codes which have the greatest areal coverage of PL are seemingly scattered (A).  Is this a measure of the sprawling nature of that zip code?  Need to investigate further.  Validation: We compare our estimation of PL areal coverage using the regression to our digitized PL for Tippecanoe County which we had done as a pilot study.  The agreement between the two is 93.4%.  We underestimate parking lots slightly using the regression (C).  There is 1,260 sq km of Parking Lots in the Great Lakes region.  The values are similar between Tippecanoe County and the Great Lakes.ADCB

Estimating the Parking Lot Footprint Across the Great Lakes Region

Estimating the parking lot footprint across the Great Lakes region

https://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1003&context=gisday

Estimating the parking lot footprint across the Great Lakes region

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