Evaluation of Impervious Surface Estimates in a Rapidly Urbanizing Watershed

Dougherty, Mark; Dymond, Randel L.; Goetz, Scott J.; Jantz, Claire A.; Goulet, Normand

doi:10.14358/pers.70.11.1275

Cited by 88 publications

(46 citation statements)

References 3 publications

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“…The Cappiella and Brown (2000) projections of imperviousness for various land use categories were generally consistent with estimates from satellite imagery published later by Dougherty et al (2004). The estimated imperviousness for all fish data study site drainage areas ranged from 0.1% to 40%, with a mean of 10.8% (Table 2).…”

Section: Hydrologic Analysissupporting

confidence: 75%

Hydrologic disturbance reduces biological integrity in urban streams

Coleman¹,

Miller

Mink³

2010

Environ Monit Assess

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The impact of urbanization on stream ecosystems is linked by land cover changes to the alteration of the natural hydrology and subsequent physical disruption of stream biota and habitat. Seasonal floods are part of the natural disturbance regime of many streams, but urbanization increases their frequency and magnitude. This study evaluated the impact of hydrologic disturbance on fish and aquatic macroinvertebrates in 81 (56 urban/25 reference) Ohio streams. Hydrologic variables included annual and monthly 24-h rainfall maxima and computed annual peak discharge, with computation supported by GIS-based drainage area delineation and land cover characterization. Ohio biological criteria for fish and macroinvertebrates measured during the late spring and summer were negatively impacted by annual peak discharge in urban streams as compared to reference streams. Results support the application of stormwater best management practices as part of stream restoration efforts to mitigate urbanization impacts to fish and macroinvertebrates.

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Section: Hydrologic Analysissupporting

confidence: 75%

Hydrologic disturbance reduces biological integrity in urban streams

Coleman¹,

Miller

Mink³

2010

Environ Monit Assess

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“…Civco and Hurd 1997;Prisloe et al 2000), aerial photography and satellite imaging (Ravagnani et al 2009;Dougherty et al 2004). Estimates of runoff can be made as a function of the area of cover (Arnold and Gibbons 1996), and landscape metrics such as patch shape and nearest neighbor (Leitao and Ahern 2002).…”

Section: Background and Literature Reviewmentioning

confidence: 99%

A Smart Market for Impervious Cover

Raffensperger

Cochrane

2010

Water Resour Manage

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When farmland or undeveloped ground is covered over, runoff can cause environmental damage and flood risk. Policymakers want to compare the economic improvement of new development to the costs produced by the associated environmental impacts. In this paper, we propose a smart market in impervious cover. A smart market is a periodic auction which is cleared by an optimization model, a linear program (LP) in this case. The LP constraint coefficients come from a hydrological model. The LP objective coefficients come from users' bids. To operate the auction, local government would appoint an auction manager, who would be responsible for maintaining the hydrological model and the LP, for operating the auction, and for maintaining the desired environmental standards. At regular intervals, the auction manager would accept bids over the internet, solve the corresponding LP, and announce the results. By LP duality, the smart market prices impervious cover at the opportunity cost to society, adjusted for location, the sensitivity of environmental features, and the incremental value of the development as indicated by bids. This design uses relevant hydrological information, and accepts community input on the desired environmental standards (avoiding the tragedy of the commons). The auction creates incentives to remove impervious cover, especially near environmentally sensitive areas. The proposed system nearly eliminates transaction costs associated with trading development rights.

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“…Many applications do not only require information about the amount of sealed surfaces and statistical tables, but also detailed maps. Accurate measurement of the distribution of impervious surface areas can provide an essential indicator for environmental quality analysis (Arnold Jr &Gibbons 1996, Dougherty et al 2004). Percent of impervious surface area has emerged as a key factor to explain and generally predict the degree of the corresponding decrease infiltration to streams and watersheds.…”

Section: Introductionmentioning

confidence: 99%

Estimating Impervious Surface Distribution: A Comparison of Object Based Analysis and Spectral Mixture Analysis

Wei¹,

Blaschke

2015

GI_Forum 2014 – Geospatial Innovation for Society

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Knowledge about the distribution of impervious surface is important to the understanding of urbanization processes and environmental consequences. This paper compares two methods for classifying the degree of imperviousness for the large metropolitan region of the fast growing city of Guangzhou in southern China: spectral mixture analysis (SMA) and object based image analysis (OBIA). Both methods were applied to data from the Chinese Satellite Huan Jing 1-B (HJ-1B). Samples were classified using a Support Vector Machine (SVM), ultimately yielding the percentages of Impervious Surface Areas (ISA). The estimation accuracy for ISA was assessed using the land surface temperature retrieval result based on HJ-1B satellite data. In general, OBIA achieved slightly better results, while both methods achieved low accuracies in the highly vegetated northern and eastern parts of the study area. Our results show that OBIA combined with SVM classification of the HJ-1B data provides a means to map and quantify the degree of impervious surface distribution.

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Evaluation of Impervious Surface Estimates in a Rapidly Urbanizing Watershed

Cited by 88 publications

References 3 publications

Hydrologic disturbance reduces biological integrity in urban streams

Hydrologic disturbance reduces biological integrity in urban streams

A Smart Market for Impervious Cover

Estimating Impervious Surface Distribution: A Comparison of Object Based Analysis and Spectral Mixture Analysis

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