Full text: Technical Commission VIII (B8)

  
    
    
     
   
    
    
    
  
     
   
     
    
     
    
    
    
   
    
  
    
  
    
  
   
  
  
   
  
    
    
   
     
  
  
   
     
      
    
   
   
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. 
Baatz, M. and scha” pe, 4A.,(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) 
Blaschke, T. (2010). Object based image analysis for remote 
sensing. ISPRS Journal of Photogrammetry and Remote 
Sensing, 65, 2-16. 
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. 
Census of India(201 1),Government of India. 
Definiens. (2009). Definiens eCognition Developer 8 User 
Guide. 
Drágut, 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. 
EGM.,(2008), Expert group Meeting,2008, organized by UN- 
HABITAT , 21-23 May 2008 at ITC, Enschede, The 
Netherlands 
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. 
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. 
Jain, S. (2007). Use of IKONOS satellite data to identify 
informal settlements in Dehradun, India. International Journal 
of Remote Sensing, 28(15), 3227 - 3233. 
Jain, S., Sokhi, B. S., & Sur, U. (2005). Slum identification 
using high-resolution satellite data. GIM International, 19(9). 
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. 
Kohli, D., et al. An ontology of slums for image-based 
classification. Computers, Environment and Urban Systems 
(2011). 
Mason, S. O., & Fraser, C. S. (1998). Image sources for 
informal settlement management. The Photogrammetric 
Record, 16(92), 313-330. 
Naga Jyothi. B, Babu. G.R and Murali Krishna. LV (2008) 
Object Oriented and Multi-Scale Image Analysis: Strengths, 
Weaknesses, Opportunities and Threats-A Review, Journal of 
Computer Science 4 (9): 706-712, 2008. 
Nussbauma.S , Niemeyerb.I , . Cantya M.J (2008) Seath - a 
new tool for automated feature extraction in the context of 
object-based image analysis. 
PMC ,(2010) Pune Municipal Corporation Environmental 
Status Report -2010. 
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. 
Shekhar, S. (2004). Urban sprawl assessment - entropy 
approach. 8(5), 43-48 
Shekhar, S. (2006). Modelling Urban Development with Fuzzy 
Logic and cellular automata. Asian Journal of Geoinformatics, 
Vol 6 No 1 2006. Page 3-10. 
Sliuzas, R.V., 2004. Managing informal settlements: a 
study using geo-information in Dar es Salaam, 
Tanzania. Utrecht University, ITC Publication Series No. 112 
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. 
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. 
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. 
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. 
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/ 
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 
UN-HABITAT. (2010). State of World's Cities 2010/2011: 
United Nations Human Settlements Programme (UN- 
HABITAT). 
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. 
     
KEY ' 
ABST 
The ol 
MODI 
provid 
domai 
classif 
applyi 
NBAR 
classif 
Land 
inform 
resear( 
global 
DISCc 
MODI 
distrib 
maps \ 
were ; 
Howe 
were c 
The o 
cover 
tempo 
kinds 
Nadir 
are co 
459-4 
2105-7 
atmos; 
correc 
correc! 
and NI 
The ta 
-10 ° 
respec 
projec 
NBAR 
produc 
transfc 
with 
proces
	        
Waiting...

Note to user

Dear user,

In response to current developments in the web technology used by the Goobi viewer, the software no longer supports your browser.

Please use one of the following browsers to display this page correctly.

Thank you.