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Journal of Zhejiang University SCIENCE A 2012 Vol.13 No.2 P.146-158


Monitoring rapid urban expansion using a multi-temporal RGB-impervious surface model

Author(s):  Amirreza Shahtahmassebi, Zhou-lu Yu, Ke Wang, Hong-wei Xu, Jin-song Deng, Jia-dan Li, Rui-sen Luo, Jing Wu, Nathan Moore

Affiliation(s):  Institute of Agriculture Remote Sensing and Information Technology, Zhejiang University, Hangzhou 310029, China; more

Corresponding email(s):   amir511@zju.edu.cn, kwang@zju.edu.cn

Key Words:  Red-green-blue impervious surface model (RGB-IS), Multi-temporal, Impervious surface, Landsat

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Amirreza Shahtahmassebi, Zhou-lu Yu, Ke Wang, Hong-wei Xu, Jin-song Deng, Jia-dan Li, Rui-sen Luo, Jing Wu, Nathan Moore. Monitoring rapid urban expansion using a multi-temporal RGB-impervious surface model[J]. Journal of Zhejiang University Science A, 2012, 13(2): 146-158.

@article{title="Monitoring rapid urban expansion using a multi-temporal RGB-impervious surface model",
author="Amirreza Shahtahmassebi, Zhou-lu Yu, Ke Wang, Hong-wei Xu, Jin-song Deng, Jia-dan Li, Rui-sen Luo, Jing Wu, Nathan Moore",
journal="Journal of Zhejiang University Science A",
publisher="Zhejiang University Press & Springer",

%0 Journal Article
%T Monitoring rapid urban expansion using a multi-temporal RGB-impervious surface model
%A Amirreza Shahtahmassebi
%A Zhou-lu Yu
%A Ke Wang
%A Hong-wei Xu
%A Jin-song Deng
%A Jia-dan Li
%A Rui-sen Luo
%A Jing Wu
%A Nathan Moore
%J Journal of Zhejiang University SCIENCE A
%V 13
%N 2
%P 146-158
%@ 1673-565X
%D 2012
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A1100034

T1 - Monitoring rapid urban expansion using a multi-temporal RGB-impervious surface model
A1 - Amirreza Shahtahmassebi
A1 - Zhou-lu Yu
A1 - Ke Wang
A1 - Hong-wei Xu
A1 - Jin-song Deng
A1 - Jia-dan Li
A1 - Rui-sen Luo
A1 - Jing Wu
A1 - Nathan Moore
J0 - Journal of Zhejiang University Science A
VL - 13
IS - 2
SP - 146
EP - 158
%@ 1673-565X
Y1 - 2012
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A1100034

In this paper, we developed a novel method of combining remote sensing tools at the sub-pixel level for accurate identification of impervious surface time series changes. We examined the use of the impervious surface model (RGB-IS)%29&ck%5B%5D=abstract&ck%5B%5D=keyword'>red-green-blue impervious surface model (RGB-IS) in detecting time series internal modification of urban regions by integrating landsat data collected over four different periods between 1987 and 2009 (i.e., 1987, 2000, 2002, and 2009). The performance of this approach was compared with two conventional methods, namely standard RGB-normalized difference vegetation index (NDVI) and post-classification technique. In contrast to conventional techniques, RGB-IS could monitor between-class changes, within-class changes, and location of these modifications. The proposed method was independent of seasonal changes and was also able to serve as a useful alternative for quick mapping growth hotspots and updating transportation corridor map. The results also showed that Cixi County, Zhejiang Province, China experienced tremendous impervious surface changes, especially along the corridors of newly constructed highways and around urban areas over the past 22 years.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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