Comparing Urban Impervious Surface Identification Using Landsat and High Resolution Aerial Photography

This paper evaluates accuracies of selected image classification strategies, as applied to Landsat imagery to assess urban impervious surfaces by comparing them to reference data manually delineated from high-resolution aerial photos. Our goal is to identify the most effective methods for delineatin...

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Main Authors: James B. Campbell, Tammy E. Parece
Format: Article
Language:English
Published: MDPI AG 2013-10-01
Series:Remote Sensing
Subjects:
Online Access:http://www.mdpi.com/2072-4292/5/10/4942
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spelling doaj-760d2a5ff20e4856a814c232cb27394c2020-11-24T22:09:17ZengMDPI AGRemote Sensing2072-42922013-10-015104942496010.3390/rs5104942Comparing Urban Impervious Surface Identification Using Landsat and High Resolution Aerial PhotographyJames B. CampbellTammy E. PareceThis paper evaluates accuracies of selected image classification strategies, as applied to Landsat imagery to assess urban impervious surfaces by comparing them to reference data manually delineated from high-resolution aerial photos. Our goal is to identify the most effective methods for delineating urban impervious surfaces using Landsat imagery, thereby guiding applications for selecting cost-effective delineation techniques. A high-resolution aerial photo was used to delineate impervious surfaces for selected census tracts for the City of Roanoke, Virginia. National Land Cover Database Impervious Surface data provided an overall accuracy benchmark at the city scale which was used to assess the Landsat classifications. Three different classification methods using three different band combinations provided overall accuracies in excess of 70% for the entire city. However, there were substantial variations in accuracy when the results were subdivided by census tract. No single classification method was found most effective across all census tracts; the best method for a specific tract depended on method, band combination, and physical characteristics of the area. These results highlight impacts of inherent local variability upon attempts to characterize physical structures of urban regions using a single metric, and the value of analysis at finer spatial scales.http://www.mdpi.com/2072-4292/5/10/4942impervious surfacesurbanLandsathigh-resolution imagerylanduse classificationRoanokeVirginia
collection DOAJ
language English
format Article
sources DOAJ
author James B. Campbell
Tammy E. Parece
spellingShingle James B. Campbell
Tammy E. Parece
Comparing Urban Impervious Surface Identification Using Landsat and High Resolution Aerial Photography
Remote Sensing
impervious surfaces
urban
Landsat
high-resolution imagery
landuse classification
Roanoke
Virginia
author_facet James B. Campbell
Tammy E. Parece
author_sort James B. Campbell
title Comparing Urban Impervious Surface Identification Using Landsat and High Resolution Aerial Photography
title_short Comparing Urban Impervious Surface Identification Using Landsat and High Resolution Aerial Photography
title_full Comparing Urban Impervious Surface Identification Using Landsat and High Resolution Aerial Photography
title_fullStr Comparing Urban Impervious Surface Identification Using Landsat and High Resolution Aerial Photography
title_full_unstemmed Comparing Urban Impervious Surface Identification Using Landsat and High Resolution Aerial Photography
title_sort comparing urban impervious surface identification using landsat and high resolution aerial photography
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2013-10-01
description This paper evaluates accuracies of selected image classification strategies, as applied to Landsat imagery to assess urban impervious surfaces by comparing them to reference data manually delineated from high-resolution aerial photos. Our goal is to identify the most effective methods for delineating urban impervious surfaces using Landsat imagery, thereby guiding applications for selecting cost-effective delineation techniques. A high-resolution aerial photo was used to delineate impervious surfaces for selected census tracts for the City of Roanoke, Virginia. National Land Cover Database Impervious Surface data provided an overall accuracy benchmark at the city scale which was used to assess the Landsat classifications. Three different classification methods using three different band combinations provided overall accuracies in excess of 70% for the entire city. However, there were substantial variations in accuracy when the results were subdivided by census tract. No single classification method was found most effective across all census tracts; the best method for a specific tract depended on method, band combination, and physical characteristics of the area. These results highlight impacts of inherent local variability upon attempts to characterize physical structures of urban regions using a single metric, and the value of analysis at finer spatial scales.
topic impervious surfaces
urban
Landsat
high-resolution imagery
landuse classification
Roanoke
Virginia
url http://www.mdpi.com/2072-4292/5/10/4942
work_keys_str_mv AT jamesbcampbell comparingurbanimpervioussurfaceidentificationusinglandsatandhighresolutionaerialphotography
AT tammyeparece comparingurbanimpervioussurfaceidentificationusinglandsatandhighresolutionaerialphotography
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