Airports Offer Unrealized Potential for Alternative Energy Production - Environmental Management

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Authors and Affiliations

1. United States Department of Agriculture, Wildlife Services, National Wildlife Research Center, Sandusky, OH, 44846, USA

   Travis L. DeVault, Bradley F. Blackwell & Jason A. Schmidt

2. Department of Wildlife, Fisheries, and Aquaculture, Mississippi State University, Mississippi, MS, 39762, USA

   Jerrold L. Belant, James A. Martin & L. Wes Burger Jr

3. United States Federal Aviation Administration, William J. Hughes Technical Center, Atlantic City, NJ, 08405, USA

   James W. Patterson Jr

Corresponding author

Correspondence to Travis L. DeVault.

Appendix: Methods Used to Estimate Grassland Area at Airports in the Contiguous U.S.

Although there are 15,079 airports in the U.S. (5,174 with paved runways) (Central Intelligence Agency [CIA] 2010), we limited our estimates of grassland area to the 2,915 airports in the contiguous U.S. considered significant to national air transportation and thus included in the National Plan of Integrated Airport Systems (NPIAS). In general there are two types of airports included in NPIAS: “certificated” airports are those approved by the U.S. Federal Aviation Administration (FAA) for regularly scheduled (>9 seats) or unscheduled (>30 seats) passenger traffic; the remaining, smaller airports are categorized as ‘general aviation’ (GA) airports (Blackwell and others 2009). Because certificated and GA airports differ substantially in size, landcover composition, and types of wildlife hazards (Dolbeer and others 2008; Federal Aviation Administration 2010b), we generated separate estimates of grassland area within airport properties for each. Also, for certificated airports we estimated grassland area within 3 km of air operations areas (AOA; runways and taxiways). Sixty-six percent of wildlife strikes that cause substantial damage to aircraft occur within 3 km of the AOA (Dolbeer 2006; Blackwell and others 2009), and the FAA discourages placement of wildlife attractants within that distance at airports servicing turbine-powered aircraft (Federal Aviation Administration 2007).

For certificated airports, we used a Geographic Information System (GIS) to estimate the extent of grasslands at a sample of 49 airports. We randomly selected 10% of certificated airports located within each of eight Omernik Level I ecological regions (Omernik 1987) in the contiguous U.S. Two ecological regions were excluded because of their small size (0.28 and 0.55% of the contiguous U.S.) and scarcity of certificated airports. We used the GIS to extract grassland polygons from 2007–2009 true-color digital orthoimagery with 1-m resolution obtained from the National Agriculture Imagery Program (NAIP). We defined grassland as any land occupied by native or exotic grasses, including hayfields and rangeland but excluding row crops. For our extraction protocol, we used all three available spectral bands, a resample factor of two, a Manhattan 7 input representation, a minimum object size of 25 pixels, and included instances of rotated features.

We assessed the accuracy of our grassland extractions by placing 100 random points on each of four airport classification maps, split evenly between grassland and non-grassland cover types, and then determined whether points were classified correctly. Overall accuracy was 85% (339 of 400 points were classified correctly). The kappa coefficient, a measure of agreement between the extraction classification and the reference data, was 0.7, indicating substantial agreement (Landis and Koch 1977). The producer’s accuracy (probability of a reference point being correctly classified) was 90 and 81% for grassland and non-grassland cover types, respectively; the user’s accuracy (probability that a point classified in the extraction represents the correct landcover type) was 78 and 92% for grassland and non-grassland cover types, respectively. Finally, we processed 2003 true-color digital orthoimagery (spatial resolution of 1 m; also from NAIP) for 10 small airports (nine GA and one small certificated airport) in Indiana, U.S. using our extraction protocol, and compared our results with landcover classifications made by manual digitization and on-site ground truthing (DeVault and others 2009). A Wilcoxon signed rank test (Statistix 2008) indicated no difference (P = 0.103) between the two landcover classification methods for grasslands, suggesting our extraction protocol was accurate. GIS analyses were conducted using ArcMap ver. 9.3 (Environmental Systems Research Institute, Redlands, California, U.S.), Feature Analyst for ArcGIS ver. 4.2, and Hawth’s Analysis Tools ver. 3.27.

Across our sample of certificated airports, we calculated a mean of 39 ± 16% (SD) grassland cover within each airport property (Table 1), and a mean of 16 ± 9% within 3 km of the AOA. Totaled across all certificated airports in the contiguous U.S., we estimated about 1,546 km² of grassland within airport properties, and an additional 4,460 km² within 3 km of the AOA.

To estimate the amount of grassland area at GA airports, we examined GIS landcover classifications conducted by DeVault and others (2009) for small airports in Indiana, U.S. DeVault and others (2009) reported that about 56% of the land cover within airport properties was composed of grassland. Using a conservative estimate of 50% grassland area, we estimated approximately 1,760 km² of grassland on GA airport properties in the contiguous U.S. (Table 1). In total, we estimated there are approximately 3,306 km² of grassland within airport properties in the contiguous U.S. Considering that there are about 12,000 small airports in the U.S. not included in NPIAS and thus not included in our calculations, plus military airfields, our estimate of grassland area is likely very conservative.

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DeVault, T.L., Belant, J.L., Blackwell, B.F. et al. Airports Offer Unrealized Potential for Alternative Energy Production. Environmental Management 49, 517–522 (2012). https://doi.org/10.1007/s00267-011-9803-4

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• Received: 30 March 2011

• Accepted: 09 December 2011

• Published: 14 January 2012

• Issue Date: March 2012

• DOI: https://doi.org/10.1007/s00267-011-9803-4

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