MATEC Web Conf.
Volume 120, 2017International Conference on Advances in Sustainable Construction Materials & Civil Engineering Systems (ASCMCES-17)
|Number of page(s)||12|
|Section||Geographic Information Systems & Remote Sensing|
|Published online||09 August 2017|
- A. K. Nassar, G. Alan Blackburn, and J. Duncan Whyatt, “Developing the desert: The pace and process of urban growth in Dubai,” Computers, Environment and Urban Systems, vol. 45, pp. 50–62, (2014). [CrossRef] [Google Scholar]
- H. S. Sudhira, T. V. Ramachandra, and K. S. Jagadish, “Urban sprawl: Metrics, dynamics and modelling using GIS,” International Journal of Applied Earth Observation and Geoinformation, vol. 5, no. 1, pp. 29–39, (2004). [CrossRef] [Google Scholar]
- W. Ji, Y. Wang, D. Zhuang, D. Song, X. Shen, W. Wang, and G. Li, “Spatial and temporal distribution of expressway and its relationships to land cover and population: A case study of Beijing, China,” Transportation Research Part D: Transport and Environment, vol. 32, pp. 86–96, (2014). [CrossRef] [Google Scholar]
- [M. K. Jat, P. K. Garg, and D. Khare, “Monitoring and modelling of urban sprawl using remote sensing and GIS techniques,” International Journal of Applied Earth Observation and Geoinformation, vol. 10, no. 1, pp. 26–43, (2008). [CrossRef] [Google Scholar]
- A. a a Al-sharif, B. Pradhan, H. Zulhaidi, M. Shafri, and S. Mansor, “Spatio-temporal Analysis of Urban and Population Growths in Tripoli using Remotely Sensed Data and GIS,” Indian Journal of Science and technology, vol. 6, no. 8, pp. 5134–5142, (2013). [Google Scholar]
- A. Singh, “Review article digital change detection techniques using remotely-sensed data,” International journal of remote sensing, vol. 10, no. 6, pp. 989–1003,( 1989). [CrossRef] [Google Scholar]
- I. Dowman, “Automated procedures for integration of satellite images and map data for change detection: the archangel project,” International Archives of Photogrammetry and Remote Sensing, vol. 32, pp. 162–169, (1998). [Google Scholar]
- R. I. Al-Ruzouq and A. F. Habib, “Linear features for automatic registration and reliable change detection of multi-source imagery,” Journal of Spatial Science, vol. 57, no. 1, pp. 51–64,( 2012). [CrossRef] [Google Scholar]
- L. Bruzzone and D. F. Prieto, “Automatic analysis of the difference image for unsupervised change detection,” IEEE Transactions on Geoscience and Remote Sensing, vol. 38, no. 3, pp. 1171–1182, (2000). [CrossRef] [Google Scholar]
- MathWorks, “Edge Detection.” [Online]. Available: http://www.mathworks.com/discovery/edge-detection.html. [Accessed: 03-Aug-2016]. [Google Scholar]
- X. J. Yu and C. N. Ng, “Spatial and temporal dynamics of urban sprawl along two urban-rural transects: A case study of Guangzhou, China,” Landscape and Urban Planning, vol. 79, no. 1, pp. 96–109, (2007). [CrossRef] [Google Scholar]
- M. Aljoufie, M. Zuidgeest, M. Brussel, and M. van Maarseveen, “Spatial-temporal analysis of urban growth and transportation in Jeddah City, Saudi Arabia,” Cities, vol. 31, pp. 57–68, (2013). [CrossRef] [Google Scholar]
- T. Blaschke, “Object based image analysis for remote sensing,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 65, no. 1, pp. 2–16, (2010). [CrossRef] [Google Scholar]
- R. C. Weih and N. D. Riggan, “Object-based classification vs. pixel-based classification: Comparitive importance of multi-resolution imagery,” The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XXXVIII, pp. 1–6, (2010). [Google Scholar]
- J. Norton, D. Gallant, and N. Scotia, “Supervised Image Classification,” no. March, (2014). [Google Scholar]
- G. M. Foody and A. Mathur, “Toward intelligent training of supervised image classifications: Directing training data acquisition for SVM classification,” Remote Sensing of Environment, vol. 93, no. 1–2, pp. 107–117, (2004). [CrossRef] [Google Scholar]
- T. W. Lee and M. S. Lewicki, “Unsupervised image classification, segmentation, and enhancement using ICA mixture models,” IEEE Transactions on Image Processing, vol. 11, no. 3, pp. 270–279, (2002). [CrossRef] [Google Scholar]
- A. E. M. Omran A. Salman, “Differential evolution methods for unsupervised image classification,” Proc. of the IEEE Congress on Evolutionary Computation, vol. 2, pp. 966–973, (2005). [Google Scholar]
- Dubai Statistical Center, “Population-Clock @ www.dsc.gov.ae.” [Online]. Available: https://www.dsc.gov.ae/en-us/EServices/Pages/Population-Clock.aspx. [Google Scholar]
- Archived from Tedad.ae, “background @ web.archive.org.” [Online]. Available: https://web.archive.org/web/20100516221856/http://www.tedad.ae/english/about_census/background.html. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.