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machine classifiers for land cover classification in Northern China using a SPOT-5 HRG
image. Int J Remote Sens 33(10):3301–3320
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statcan.gc.ca/census-recensement/2011/as-sa/fogs-spg/Facts-pr-eng.cfm?Lang¼Eng&
GK¼PR&GC¼35
Sundarakumar K, Harika M, Begum SKA, Yamini S, Balakrishna K (2012) Land use and land
cover change detection and urban sprawl analysis of Vijayamada city using multitemporal
Landsat data. Int J Eng Sci Technol 4(01):170–178
Tan KC, Lim HS, MatJafri MZ, Abdullah K (2009) Landsat data to evaluate urban expansion and
determine land use/land cover changes in Penang Island, Malaysia. Environ Earth Sci
60(7):1509–1521
Tang J, Wang L, Yao Z (2008) Analyses of urban landscape dynamics using multi-temporal
satellite images: a comparison of two petroleum-oriented cities. Landsc Urban Plan
87(4):269–278
Thapa RB, Murayama Y (2009) Urban mapping, accuracy, & image classification: a comparison
of multiple approaches in Tsukuba City, Japan. Appl Geogr 29(1):135–144
Thompson SK (1992) Sampling. Wiley, New York. ISBN 0-471-54045-5
Tian G, Jiang J, Yang Z, Zhang Y (2011) The urban growth, size distribution and spatio-temporal
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tion/fs20133060
USGS (2013b) Landsat-A global land-imaging mission. Fact sheet 2012-3072. Retrieved from:
http://pubs.usgs.gov/fs/2012/3072/fs2012-3072.pdf
USGS (2013c) Landsat 8. Retrieved from: http://landsat.usgs.gov/landsat8.php
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USGS (2013e) Landsat project description. Retrieved from: http://landsat.usgs.gov/about_pro
ject_descriptions.php
USGS (2013f) Landsat processing details. Retrieved from: http://landsat.usgs.gov/Landsat_
Processing_Details.php
Wulder MA, White JC, Masek JG, Dwyer J, Roy DP (2011) Continuity of Landsat observations:
short term considerations. Remote Sens Environ 115:747–751
Yang X (2002) Satellite monitoring of urban spatial growth in the Atlanta Metropolitan area.
Photogramm Eng Remote Sens 68(7):725–734
Yang L, Xian G, Klaver JM, Deal B (2003) Urban land-cover change detection through sub-pixel
imperviousness mapping using remotely sensed data. Photogramm Eng Remote Sens
69(9):1003–1010
Yin J, Yin Z, Zhong H, Xu S, Hu X, Wang J, Wu J (2011) Monitoring urban expansion and land
use/land cover changes of Shanghai metropolitan area during the transitional economy
(1979─2009) in China. Environ Monit Assess 177(1–4):609–621
Yuan F, Sawaya KE, Loeffelholz BC, Bauer ME (2005) Land cover classification and change
analysis of the Twin Cities (Minnesota) Metropolitan area by multitemporal Landsat remote
sensing. Remote Sens Environ 98(2–3):317–328
Zha Y, Gao J, Ni S (2003) Use of normalized difference built-up index in automatically mapping
urban areas from TM imagery. Int J Remote Sens 24(3):583–594
Zhao H, Chen X, Area AS (2005) Use of normalized difference bareness index in quickly mapping
bare areas from TM/ETM+. IEEE Trans Geosci Remote Sens 4(5):1666–1668
86
A. Fu et al.
machine classifiers for land cover classification in Northern China using a SPOT-5 HRG
image. Int J Remote Sens 33(10):3301–3320
Statistics Canada (2011) Focus on geography series, 2011 census. Retrieved from: http://www12.
statcan.gc.ca/census-recensement/2011/as-sa/fogs-spg/Facts-pr-eng.cfm?Lang¼Eng&
GK¼PR&GC¼35
Sundarakumar K, Harika M, Begum SKA, Yamini S, Balakrishna K (2012) Land use and land
cover change detection and urban sprawl analysis of Vijayamada city using multitemporal
Landsat data. Int J Eng Sci Technol 4(01):170–178
Tan KC, Lim HS, MatJafri MZ, Abdullah K (2009) Landsat data to evaluate urban expansion and
determine land use/land cover changes in Penang Island, Malaysia. Environ Earth Sci
60(7):1509–1521
Tang J, Wang L, Yao Z (2008) Analyses of urban landscape dynamics using multi-temporal
satellite images: a comparison of two petroleum-oriented cities. Landsc Urban Plan
87(4):269–278
Thapa RB, Murayama Y (2009) Urban mapping, accuracy, & image classification: a comparison
of multiple approaches in Tsukuba City, Japan. Appl Geogr 29(1):135–144
Thompson SK (1992) Sampling. Wiley, New York. ISBN 0-471-54045-5
Tian G, Jiang J, Yang Z, Zhang Y (2011) The urban growth, size distribution and spatio-temporal
dynamic pattern of the Yangtze River Delta megalopolitan region, China. Ecol Model
222(3):865–878
USGS (2013a) Landsat 8. Fact sheet 2013–3060. Retrieved from: http://pubs.er.usgs.gov/publica
tion/fs20133060
USGS (2013b) Landsat-A global land-imaging mission. Fact sheet 2012-3072. Retrieved from:
http://pubs.usgs.gov/fs/2012/3072/fs2012-3072.pdf
USGS (2013c) Landsat 8. Retrieved from: http://landsat.usgs.gov/landsat8.php
USGS (2013d) Landsat project statistics. Retrieved from: http://landsat.usgs.gov/Landsat_Pro
ject_Statistics.php
USGS (2013e) Landsat project description. Retrieved from: http://landsat.usgs.gov/about_pro
ject_descriptions.php
USGS (2013f) Landsat processing details. Retrieved from: http://landsat.usgs.gov/Landsat_
Processing_Details.php
Wulder MA, White JC, Masek JG, Dwyer J, Roy DP (2011) Continuity of Landsat observations:
short term considerations. Remote Sens Environ 115:747–751
Yang X (2002) Satellite monitoring of urban spatial growth in the Atlanta Metropolitan area.
Photogramm Eng Remote Sens 68(7):725–734
Yang L, Xian G, Klaver JM, Deal B (2003) Urban land-cover change detection through sub-pixel
imperviousness mapping using remotely sensed data. Photogramm Eng Remote Sens
69(9):1003–1010
Yin J, Yin Z, Zhong H, Xu S, Hu X, Wang J, Wu J (2011) Monitoring urban expansion and land
use/land cover changes of Shanghai metropolitan area during the transitional economy
(1979─2009) in China. Environ Monit Assess 177(1–4):609–621
Yuan F, Sawaya KE, Loeffelholz BC, Bauer ME (2005) Land cover classification and change
analysis of the Twin Cities (Minnesota) Metropolitan area by multitemporal Landsat remote
sensing. Remote Sens Environ 98(2–3):317–328
Zha Y, Gao J, Ni S (2003) Use of normalized difference built-up index in automatically mapping
urban areas from TM imagery. Int J Remote Sens 24(3):583–594
Zhao H, Chen X, Area AS (2005) Use of normalized difference bareness index in quickly mapping
bare areas from TM/ETM+. IEEE Trans Geosci Remote Sens 4(5):1666–1668
86
A. Fu et al.