Automated Extraction of Slum Built-up Areas from Multispectral Imageries

Author:

Dahiya SusheelaORCID,Garg P. K.,Jat Mahesh K.

Publisher

Springer Science and Business Media LLC

Subject

Earth and Planetary Sciences (miscellaneous),Geography, Planning and Development

Reference27 articles.

1. Aminipouri, M., & Sliuzas, R. (2009). Object-oriented analysis of very high resolution orthophotos for estimating the population of slum areas, case of Dar-Es-Salaam, Tanzania. In Proceedings of the ISPRS XXXVIII conference.

2. Attarzadeh, R., & Momeni, M. J. (2018). Object-based rule sets and its transferability for building extraction from high resolution satellite imagery. Journal of the Indian Society of Remote Sensing,46(2), 169–178.

3. Hofmann, P. (2001). Detecting informal settlements from Ikonos image data using methods of object oriented image analysis: An example from Cape Town (South Africa). In Proceedings of the remote sensing of urban areas/regensburger geographische Schriften, Regensburg, Germany (pp. 107–118).

4. Hofmann, P., Strobl, J., Blaschke, T., & Kux, H. (2008). Detecting informal settlements from QuickBird data in Rio de Janeiro using an object based approach. In T. Blaschke, S. Lang, & G. J. Hay (Eds.), Object-based image analysis. Lecture notes in geoinformation and cartography. Berlin, Heidelberg: Springer.

5. Huang, Y., Zhuo, L., Tao, H., Shi, Q., & Liu, K. (2017). A novel building type classification scheme based on integrated LiDAR and high-resolution images. Remote Sensing,9(7), 679.

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