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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2013-10-01
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Online Access: | http://www.mdpi.com/2072-4292/5/10/4942 |
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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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