Proceedings of the 2013 the International Conference on Remote Sensing, Environment and Transportation Engineering (RSETE 2013)

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Estimating impervious surfaces by linear spectral mixture analysis under semi-constrained condition

Authors
Zhu Honglei, Li Ying, Fu Bolin
Corresponding Author
Zhu Honglei
Available Online August 2013.
DOI
10.2991/rsete.2013.87How to use a DOI?
Keywords
inpervious surface; LSMA; semi-constrained condition
Abstract

Impervious surface played an important role in monitoring urban sprawl and understanding human activities. Linear spectral mixture analysis (LSMA) is commonly used to estimate impervious surface due to its simple structure and clear physical meaning. But previous researches found that LSMA seems to overestimate slightly impervious surface fraction in less developed areas (0–20%), while underestimating it in the central business district (CBD) (over 80%). This paper using LSMA model, under fully constrained and semi-constrained condition, developed impervious surface of Fujin town, Heilongjiang Province from the Landsat Thematic Mapper (TM) image. Accuracy evaluation was estimated between town and rural areas under the two different constraints. The results indicated that impervious surface developed by four endmembers(high albedo, low albedo, soil, and vegetation) under fully constrained and semi-constrained conditions overestimated slightly in less developed areas. Impervious surface developed by three endmembers (high albedo, soil, and vegetation) under semi-constrained condition provided a fine performance with a RMS reduced from 19.79% to 17.73%.

Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2013 the International Conference on Remote Sensing, Environment and Transportation Engineering (RSETE 2013)
Series
Advances in Intelligent Systems Research
Publication Date
August 2013
ISBN
10.2991/rsete.2013.87
ISSN
1951-6851
DOI
10.2991/rsete.2013.87How to use a DOI?
Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - CONF
AU  - Zhu Honglei
AU  - Li Ying
AU  - Fu Bolin
PY  - 2013/08
DA  - 2013/08
TI  - Estimating impervious surfaces by linear spectral mixture analysis under semi-constrained condition
BT  - Proceedings of the 2013 the International Conference on Remote Sensing, Environment and Transportation Engineering (RSETE 2013)
PB  - Atlantis Press
SP  - 355
EP  - 358
SN  - 1951-6851
UR  - https://doi.org/10.2991/rsete.2013.87
DO  - 10.2991/rsete.2013.87
ID  - Honglei2013/08
ER  -