Afify HA (2011) Evaluation of change detection techniques for monitoring land-cover changes: a
case study in new Burg El-Arab area. Alex Eng J 50(2):187–195
Alphan H (2011) Comparing the utility of image algebra operations for characterizing landscape
changes: the case of the Mediterranean coast. J Environ Manage 92(11):2961–2971
Alumutairi A, Warner TA (2010) Change detection accuracy and image properties: a study using
simulated data. Remote Sens 2:1508–1529
Anderson JR, Hardy EE, Roach JT, Witmer RE (1976) A land use and land cover classification
system for use with remote sensor data. United States Government Printing Office, Washington
Benediktsson JA, Chanussot J, Fauvel M (2007) Multiple classifier systems in remote sensing:
from basics to recent developments. MCS 2007. LNCS 4472:501–512
Bhatta B (2010) Analysis of urban growth and sprawl from remote sensing data, Elsevier
Byrne GF, Crapper PF, Mayo KK (1980) Monitoring land-cover change by principal component
analysis of multitemporallandsat data. Remote Sens Environ 10(3):175–184
Congalton R (1991) A review of assessing the accuracy of classifications of remotely sensed data.
Remote Sens Environ 46:35–46
Congalton RG, Green K (1999) Assessing the accuracy of remotely sensed data: principles and
practices. CRC Press, New York. ISBN 0-87371-986-7
Coppin P, Jonckheere I, Nackaerts K, Muys B, Lambin E (2004) Digital change detection methods
in ecosystem monitoring: a review. Int J Remote Sens 25(9):1565–1596
Dawelbait M, Morari F (2012) Monitoring desertification in a Savannah region in Sudan using
Landsat images and spectral mixture analysis. J Arid Environ 80:45–55
Deng JS, Wang K, Li J, Deng YH (2009) Urban land use change detection using multisensor
satellite images. Pedosphere 19(1):96–103
Frohn R, Arellano-Neri O (2005) Improving artificial neural networks using texture analysis and
decision trees for the classification of land cover. GISci Remote Sens 42(1):44–65
Gislason PO, Benediktsson JA, Sveinsson JR (2006) Random forests for land cover classification.
Pattern Recogn Lett 27(4):294–300
Hansen MC, Loveland TR (2012) A review of large area monitoring of land cover change using
Landsat data. Remote Sens Environ 122:66–74
Hayes DJ, Sader SA (2001) Comparison of change detection techniques for monitoring tropical
forest clearing and vegetation regrowth in a time series. Photogramm Eng Remote Sens
67(9):1067–1075
Huang C, Davis LS, Townshend JRG (2002) An assessment of support vector machines for land
cover classification. Int J Remote Sens 23(4):725–749
Huang Y, Fipps G, Lacey RE, Thomson SJ (2011) Landsat satellite multi-spectral image classification of land cover and land use changes for GIS-based urbanization analysis in irrigation
districts of Lower Rio Grande Valley of Texas. Appl Remote Sens J 2(1):27–36
IRS (2013) ITC’s database of satellites and sensors, Faculty of geo-information science and earth
observation (ITC). University of Twente. Retrieved from: http://www.itc.nl/research/products/
sensordb/AllSatellites.aspx
Jensen JR (2005) Introductory of digital image processing: a remote sensing perspective, 3rd edn.
Pearson Education, Hardcover, USA, ISBN 0-13-145361-0
Jensen JR (2006) Remote sensing of the environment: an earth resource perspective, 2nd edn.
Pearson Education, Hardcover, USA, ISBN 0-13-188950-8
Jha CS, Unni NVM (1994) Digital change detection of forest conversion of a dry tropical Indian
forest region. Int J Remote Sens 15(13):2543–2552
Kaufmann RK, Seto KC (2001) Change detection, accuracy, and bias in a sequential analysis of
Landsat imagery in the Pearl River Delta, China: econometric techniques. Agr Ecosyst Environ
85(1–3):95–105
Kleynhans W, Olivier JC, Wessels KJ, Salmon BP, van den Bergh F, Steenkamp K (2011)
Detecting land cover change using an extended Kalman filter on MODIS NDVI time-series
data. IEEE Geosci Remote Sens Lett 8(3):507–511
84
A. Fu et al.
case study in new Burg El-Arab area. Alex Eng J 50(2):187–195
Alphan H (2011) Comparing the utility of image algebra operations for characterizing landscape
changes: the case of the Mediterranean coast. J Environ Manage 92(11):2961–2971
Alumutairi A, Warner TA (2010) Change detection accuracy and image properties: a study using
simulated data. Remote Sens 2:1508–1529
Anderson JR, Hardy EE, Roach JT, Witmer RE (1976) A land use and land cover classification
system for use with remote sensor data. United States Government Printing Office, Washington
Benediktsson JA, Chanussot J, Fauvel M (2007) Multiple classifier systems in remote sensing:
from basics to recent developments. MCS 2007. LNCS 4472:501–512
Bhatta B (2010) Analysis of urban growth and sprawl from remote sensing data, Elsevier
Byrne GF, Crapper PF, Mayo KK (1980) Monitoring land-cover change by principal component
analysis of multitemporallandsat data. Remote Sens Environ 10(3):175–184
Congalton R (1991) A review of assessing the accuracy of classifications of remotely sensed data.
Remote Sens Environ 46:35–46
Congalton RG, Green K (1999) Assessing the accuracy of remotely sensed data: principles and
practices. CRC Press, New York. ISBN 0-87371-986-7
Coppin P, Jonckheere I, Nackaerts K, Muys B, Lambin E (2004) Digital change detection methods
in ecosystem monitoring: a review. Int J Remote Sens 25(9):1565–1596
Dawelbait M, Morari F (2012) Monitoring desertification in a Savannah region in Sudan using
Landsat images and spectral mixture analysis. J Arid Environ 80:45–55
Deng JS, Wang K, Li J, Deng YH (2009) Urban land use change detection using multisensor
satellite images. Pedosphere 19(1):96–103
Frohn R, Arellano-Neri O (2005) Improving artificial neural networks using texture analysis and
decision trees for the classification of land cover. GISci Remote Sens 42(1):44–65
Gislason PO, Benediktsson JA, Sveinsson JR (2006) Random forests for land cover classification.
Pattern Recogn Lett 27(4):294–300
Hansen MC, Loveland TR (2012) A review of large area monitoring of land cover change using
Landsat data. Remote Sens Environ 122:66–74
Hayes DJ, Sader SA (2001) Comparison of change detection techniques for monitoring tropical
forest clearing and vegetation regrowth in a time series. Photogramm Eng Remote Sens
67(9):1067–1075
Huang C, Davis LS, Townshend JRG (2002) An assessment of support vector machines for land
cover classification. Int J Remote Sens 23(4):725–749
Huang Y, Fipps G, Lacey RE, Thomson SJ (2011) Landsat satellite multi-spectral image classification of land cover and land use changes for GIS-based urbanization analysis in irrigation
districts of Lower Rio Grande Valley of Texas. Appl Remote Sens J 2(1):27–36
IRS (2013) ITC’s database of satellites and sensors, Faculty of geo-information science and earth
observation (ITC). University of Twente. Retrieved from: http://www.itc.nl/research/products/
sensordb/AllSatellites.aspx
Jensen JR (2005) Introductory of digital image processing: a remote sensing perspective, 3rd edn.
Pearson Education, Hardcover, USA, ISBN 0-13-145361-0
Jensen JR (2006) Remote sensing of the environment: an earth resource perspective, 2nd edn.
Pearson Education, Hardcover, USA, ISBN 0-13-188950-8
Jha CS, Unni NVM (1994) Digital change detection of forest conversion of a dry tropical Indian
forest region. Int J Remote Sens 15(13):2543–2552
Kaufmann RK, Seto KC (2001) Change detection, accuracy, and bias in a sequential analysis of
Landsat imagery in the Pearl River Delta, China: econometric techniques. Agr Ecosyst Environ
85(1–3):95–105
Kleynhans W, Olivier JC, Wessels KJ, Salmon BP, van den Bergh F, Steenkamp K (2011)
Detecting land cover change using an extended Kalman filter on MODIS NDVI time-series
data. IEEE Geosci Remote Sens Lett 8(3):507–511
84
A. Fu et al.