Synergistic object-based multi-class feature extraction in urban landscape using airborne LiDAR data-Reference-Cited by-同舟云学术

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Synergistic object-based multi-class feature extraction in urban landscape using airborne LiDAR data

Published:2018-04-25 Issue:5 Volume:26 Page:483-496
ISSN:2366-3286
Container-title:Spatial Information Research
language:en
Short-container-title:Spat. Inf. Res.

Author:

Jawak Shridhar D.,Panditrao Satej N.,Luis Alvarinho J.

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computers in Earth Sciences,Computer Science Applications,Geography, Planning and Development

Link

http://link.springer.com/article/10.1007/s41324-018-0191-1/fulltext.html

Reference41 articles.

1. Bhaskaran, S., Eric, N., Jimenez, K., & Bhatia, S. K. (2013). Rule-based classification of high-resolution imagery over urban areas in New York City. Geocarto International, 28(6), 527–545. https://doi.org/10.1080/01431161.2013.879350 .

2. Hamedianfar, A., & Shafri, H. Z. M. (2013). Development of fuzzy rule-based parameters for urban object-oriented classification using very high resolution imagery. Geocarto International, 29(3), 268–292. https://doi.org/10.1080/10106049.2012.760006 .

3. Blaschke, T., & Strobl, J. (2001). What’s wrong with pixels? Some recent developments interfacing remote sensing and GIS. GIS—ZeitschriftfürGeoinformationssysteme, 14(6), 12–17. https://doi.org/10.1080/13658816.2011.566569 .

4. Hu, X., & Weng, Q. (2010). Impervious surface area extraction from IKONOS imagery using an object-based fuzzy method. Geocarto International, 26(1), 3–20. https://doi.org/10.1080/10106049.2010.535616 .

5. Li, X., Myint, S. W., Zhang, Y., Galletti, C., Zhang, X., & Turner, B. L. (2014). Object-based land- cover classification for metropolitan Phoenix, Arizona, using aerial photography. International Journal of Applied Earth Observation and Geoinformation, 33, 321–330. https://doi.org/10.1016/j.jag.2014.04.018 .

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