Monitoring Annual Urban Changes in a Rapidly Growing Portion of Northwest Arkansas with a 20-Year Landsat Record
Northwest Arkansas has undergone a significant urban transformation in the past several decades and is considered to be one of the fastest growing regions in the United States. The urban area expansion and the associated demographic increases bring unprecedented pressure to the environment and natur...
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2017-01-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | http://www.mdpi.com/2072-4292/9/1/71 |
id |
doaj-2d00f24f327e4a6094cf3119d9bf5e4f |
---|---|
record_format |
Article |
spelling |
doaj-2d00f24f327e4a6094cf3119d9bf5e4f2020-11-25T00:14:25ZengMDPI AGRemote Sensing2072-42922017-01-01917110.3390/rs9010071rs9010071Monitoring Annual Urban Changes in a Rapidly Growing Portion of Northwest Arkansas with a 20-Year Landsat RecordRyan Reynolds0Lu Liang1XueCao Li2John Dennis3School of Forestry and Natural Resources, University of Arkansas at Monticello, Monticello, AR 71656, USASchool of Forestry and Natural Resources, University of Arkansas at Monticello, Monticello, AR 71656, USADepartment of Geological & Atmospheric Science, Iowa State University, Ames, IA 50014, USASchool of Forestry and Natural Resources, University of Arkansas at Monticello, Monticello, AR 71656, USANorthwest Arkansas has undergone a significant urban transformation in the past several decades and is considered to be one of the fastest growing regions in the United States. The urban area expansion and the associated demographic increases bring unprecedented pressure to the environment and natural resources. To better understand the consequences of urbanization, accurate and long-term depiction on urban dynamics is critical. Although urban mapping activities using remote sensing have been widely conducted, long-term urban growth mapping at an annual pace is rare and the low accuracy of change detection remains a challenge. In this study, a time series Landsat stack covering the period from 1995 to 2015 was employed to detect the urban dynamics in Northwest Arkansas via a two-stage classification approach. A set of spectral indices that have been proven to be useful in urban area extraction together with the original Landsat spectral bands were used in the maximum likelihood classifier and random forest classifier to distinguish urban from non-urban pixels for each year. A temporal trajectory polishing method, involving temporal filtering and heuristic reasoning, was then applied to the sequence of classified urban maps for further improvement. Based on a set of validation samples selected for five distinct years, the average overall accuracy of the final polished maps was 91%, which improved the preliminary classifications by over 10%. Moreover, results from this study also indicated that the temporal trajectory polishing method was most effective with initial low accuracy classifications. The resulting urban dynamic map is expected to provide unprecedented details about the area, spatial configuration, and growing trends of urban land-cover in Northwest Arkansas.http://www.mdpi.com/2072-4292/9/1/71time serieschange detectiontemporal filteringremote sensing |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ryan Reynolds Lu Liang XueCao Li John Dennis |
spellingShingle |
Ryan Reynolds Lu Liang XueCao Li John Dennis Monitoring Annual Urban Changes in a Rapidly Growing Portion of Northwest Arkansas with a 20-Year Landsat Record Remote Sensing time series change detection temporal filtering remote sensing |
author_facet |
Ryan Reynolds Lu Liang XueCao Li John Dennis |
author_sort |
Ryan Reynolds |
title |
Monitoring Annual Urban Changes in a Rapidly Growing Portion of Northwest Arkansas with a 20-Year Landsat Record |
title_short |
Monitoring Annual Urban Changes in a Rapidly Growing Portion of Northwest Arkansas with a 20-Year Landsat Record |
title_full |
Monitoring Annual Urban Changes in a Rapidly Growing Portion of Northwest Arkansas with a 20-Year Landsat Record |
title_fullStr |
Monitoring Annual Urban Changes in a Rapidly Growing Portion of Northwest Arkansas with a 20-Year Landsat Record |
title_full_unstemmed |
Monitoring Annual Urban Changes in a Rapidly Growing Portion of Northwest Arkansas with a 20-Year Landsat Record |
title_sort |
monitoring annual urban changes in a rapidly growing portion of northwest arkansas with a 20-year landsat record |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2017-01-01 |
description |
Northwest Arkansas has undergone a significant urban transformation in the past several decades and is considered to be one of the fastest growing regions in the United States. The urban area expansion and the associated demographic increases bring unprecedented pressure to the environment and natural resources. To better understand the consequences of urbanization, accurate and long-term depiction on urban dynamics is critical. Although urban mapping activities using remote sensing have been widely conducted, long-term urban growth mapping at an annual pace is rare and the low accuracy of change detection remains a challenge. In this study, a time series Landsat stack covering the period from 1995 to 2015 was employed to detect the urban dynamics in Northwest Arkansas via a two-stage classification approach. A set of spectral indices that have been proven to be useful in urban area extraction together with the original Landsat spectral bands were used in the maximum likelihood classifier and random forest classifier to distinguish urban from non-urban pixels for each year. A temporal trajectory polishing method, involving temporal filtering and heuristic reasoning, was then applied to the sequence of classified urban maps for further improvement. Based on a set of validation samples selected for five distinct years, the average overall accuracy of the final polished maps was 91%, which improved the preliminary classifications by over 10%. Moreover, results from this study also indicated that the temporal trajectory polishing method was most effective with initial low accuracy classifications. The resulting urban dynamic map is expected to provide unprecedented details about the area, spatial configuration, and growing trends of urban land-cover in Northwest Arkansas. |
topic |
time series change detection temporal filtering remote sensing |
url |
http://www.mdpi.com/2072-4292/9/1/71 |
work_keys_str_mv |
AT ryanreynolds monitoringannualurbanchangesinarapidlygrowingportionofnorthwestarkansaswitha20yearlandsatrecord AT luliang monitoringannualurbanchangesinarapidlygrowingportionofnorthwestarkansaswitha20yearlandsatrecord AT xuecaoli monitoringannualurbanchangesinarapidlygrowingportionofnorthwestarkansaswitha20yearlandsatrecord AT johndennis monitoringannualurbanchangesinarapidlygrowingportionofnorthwestarkansaswitha20yearlandsatrecord |
_version_ |
1725390626580594688 |