Detecting slums from quick bird data in pune using an object oriented approach

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

Volumn 39, Issue , 2012, Pages 519-524

  Shekhar, Sulochana ^a  

^a CENTRAL UNIVERSITY OF KARNATAKA   (India)

Author keywords

ECognition; Object oriented Analysis; Pune; Quick bird data; Slums

Indexed keywords

BIRDS; HOUSING; IMAGE SEGMENTATION; MEMBERSHIP FUNCTIONS; PHOTOGRAMMETRY; REMOTE SENSING; RURAL AREAS;

ECOGNITION; OBJECT-ORIENTED ANALYSIS; PUNE; QUICK BIRD; SLUMS;

OBJECT ORIENTED PROGRAMMING;

EID: 84880676968     PISSN: 16821750     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (33)

1. Angeles, G., Lance, P., Barden-O'Fallon, J., Islam, N., Mahbub, A. Q. M., & Nazem, N. I. (2009). The 2005 census and mapping of slums in Bangladesh: design, select results and application. [Article]. International Journal of Health Geographics, 8, 19.
2. Baud, I., Kuffer, M., Pfeffer, K., Sliuzas, R., & Karuppannan, S. (2010). Understanding heterogeneity in metropolitan India: The added value of remote sensing data for analyzing substandard residential areas. International Journal of Applied Earth Observation and Geoinformation, 12(5), 359-374.
3. Baud, I., Pfeffer, K., Sridharan, N., & Nainan, N. (2009). Matching deprivation mapping to urban governance in three Indian mega-cities. Habitat International, 33(4), 365-377.
4. Baud, I., Sridharan, N., & Pfeffer, K. (2008). Mapping urban poverty for local governance in an Indian mega-city: The case of Delhi. Urban Studies, 45(7), 1385-1412.
5. Baatz, M. and schä pe, A., (2000). Multiresolution segmentation-an optimization approach for high quality multi-scale image segmentation. J. Strobl, T. Blaschke and G. Griesebner (Eds) (Heidelberg, Germany: Wichmann Verlag)
6. Blaschke, T. (2010). Object based image analysis for remote sensing. ISPRS Journal of Photogrammetry and Remote Sensing, 65, 2-16.
7. Cleve, C, Kelly, M., Kearns, F. R., & Moritz, M. (2008). Classification of the wildland-urban interface: A comparison of pixel-and object-based classifications using high-resolution aerial photography. Computers, Environment and Urban Systems, 32(4), 317-326.
8. Census of India (2011), Government of India.
9. Definiens. (2009). Definiens eCognition Developer 8 User Guide.
10. Drəguţ, L., Tiede, D., & Levick, S. R. (2010). ESP: a tool to estimate scale parameter for multiresolution image segmentation of remotely sensed data. International Journal of Geographical Information Science, 24(6), 859-871.
11. EGM., (2008), Expert group Meeting, 2008, organized by UN-HABITAT, 21-23 May 2008 at ITC, Enschede, The Netherlands
12. Hofmann, P. (2001). Detecting Informal Settlements from Ikonos Image Data Using Methods of Object Oriented Image Analysis-An Example from Cape Town (South Africia) Paper presented at the Remote Sensing of Urban Areas.
13. Hofmann, P., Strobl, J., Blaschke, T., & Kux, H. (2008). Detecting informal settlements from Quickbird data in Rio De Janeiro using an object based approach. Object-based Image Analysis, 531-553.
14. Jain, S. (2007). Use of IKONOS satellite data to identify informal settlements in Dehradun, India. International Journal of Remote Sensing, 28(15), 3227-3233.
15. Jain, S., Sokhi, B. S., & Sur, U. (2005). Slum identification using high-resolution satellite data. GIM International, 19(9).
16. Joshi, P., Sen, S., & Hobson, J. (2002). Experiences with surveying and mapping Pune and Sangli slums on a geographical information system (GIS). Environment and Urbanization, 14(2), 225-240.
17. Kohli, D., et al. An ontology of slums for image-based classification. Computers, Environment and Urban Systems (2011).
18. Mason, S. O., & Fraser, C. S. (1998). Image sources for informal settlement management. The Photogrammetric Record, 16(92), 313-330.
19. Naga Jyothi. B, Babu. G.R and Murali Krishna. I.V (2008) Object Oriented and Multi-Scale Image Analysis: Strengths, Weaknesses, Opportunities and Threats-A Review, Journal of Computer Science 4 (9): 706-712, 2008.
20. Nussbauma S., Niemeyerb I., Cantya M.J. (2008) Seath-a new tool for automated feature extraction in the context of object-based image analysis.
21. PMC, (2010) Pune Municipal Corporation Environmental Status Report-2010.
22. Sen, S., Hobson, J., & Joshi, P. (2003). The Pune Slum Census: creating a socio-economic and spatial information base on a GIS for integrated and inclusive city development. [Proceedings Paper]. Habitat International, 27(4), 595-611.
23. Shekhar, S. (2004). Urban sprawl assessment-entropy approach. 8(5), 43-48
24. Shekhar, S. (2006). Modelling Urban Development with Fuzzy Logic and cellular automata. Asian Journal of Geoinformatics, Vol 6 No 1 2006. Page 3-10.
25. Sliuzas, R.V., 2004. Managing informal settlements: a study using geo-information in Dar es Salaam, Tanzania. Utrecht University, ITC Publication Series No. 112
26. Sliuzas, R.V., 2008. Improving the performance of urban planning and management with remote sensing systems. In: C. Jurgens (Editor), Remote sensing: new challenges of high resolution-EARSeL workshop, Bochum, Germany.
27. Sliuzas, R. V., Kerle, N., & Kuffer, M. (2008). Object-oriented mapping of urban poverty and deprivation. Paper presented at the EARSeL worshop on Remote Sensing for Developing Countries in Conjunction with GISDECO 8.
28. Sliuzas, R. V., & Kuffer, M. (2008). Analysing the spatial heterogeneity of poverty using remote sensing: Typology of poverty areas using selected RS based indicators. Paper presented at the EARSeL Workshop on Remote Sensing.
29. Teo, T. A., & Chen, L. C. (2004). Object-Based Building Detection from LIDAR Data and High Resolution Satellite Imagery Paper presented at the 25th Asia Conference on Remote Sensing.
30. Turkstra, J., 2008, Visible and non-visible slum, Libya and Somalia, Paper presented at the Expert Group Meeting on Slum Mapping at ITC in Enschede Netherlands, 21-23May2008. Available online at http://www.ciesin.columbia.edu/confluence/
31. Ujjwal Sur, Sadhana Jain, B. S. Sokhi., 2004, Identification/Mapping of Slum Environment using IKONOS Satellite Data: A Case Study of Dehradun, India, http://www.gisdevelopment.net/application/environment/pp/mi 04011.htm
32. UN-HABITAT. (2010). State of World's Cities 2010/2011: United Nations Human Settlements Programme (UN-HABITAT).
33. Weeks, J., Hill, A., Stow, D., Getis, A., & Fugate, D. (2007). Can we spot a neighborhood from the air? Defining neighborhood structure in Accra, Ghana. GeoJournal, 69(1), 9-22.