Abstract
Estimation of infrastructural growth is the key issue for planning and resource management. In this regard it is highly required to have a proper database and documentation. Remotely sensed data and its processing techniques are most important parameter to achieve this goal. In developing countries, the planning and resource management is still dependent on traditional methods, but integration of satellite data of high resolution and of multiple spectral bands with appropriate processing techniques, makes it possible to get optimal result in limited fiscal resources. The merging of multi resolution sensor data can be the best option instead of using costly data for low budget planning and development. This study aims to analyze the potentials of image fusion of multispectral and panchromatic satellite data with high ground resolution images and evaluating their significance in infrastructural classification. While the accuracy assessment tests of classification result, suggest the appropriate classification techniques. The Relevance of image fusion in auto vectorization has also been discussed in this paper.
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References
Congalton. (1991). A Review of Assessing the Accuracy of Classifications of Remotely Sensed Data. Remote Sensing of Environment, 37, 35–46.
Erdas field guide, 2005, :Leica Geosystems
Firooz Sadjadi, (2005). Comparative Image Fusion Analysis. Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05) - Workshops, pp. 8, June 20-26, 2005.
Jong-Hyun Park, Ryutaro Tateishi, Ketut Wikantika, and Jong-Geol PARK (1999). The Potential of High Resolution Remotely Sensed Data for Urban Infrastructure Monitoring - 0-7803-5207-6/99/$10.00 c 1999 IEEE. Pg 1137–39
Li, S. T., Kowk, J. T., & Wang, Y. N. (2002). Using the discrete wavelet frame transform to merge Landsat TM and SPOT panchromatic images. Information Fusion, 3, 17–23.
Parcharidis, I., Kazi-Tani, L.M., (2000). Landsat TM and ERS data fusion: a statistical approach evaluation for four different methods. Geosciences and Remote Sensing Symposium, 2000. Proceedings IGARSS, IEEE 2000 International, 24–28 July 2000, 2120 –22.
Rahman Atiqure, (2006). “Application of Remote Sensing and GIS Technique for UrbanEnvironment Management and Development of Delhi, India”. Applied Remote Sensing for Urban Planning Governance and Sustainability, http://www.springerlink.com/index/x5w74277j3I13959pdf
Rüdenauer, H., Schmitz, M., (2010). Use of landsat 7 ETM + data as basic information for infrastructure planning. Proceedings of the ISPRS Joint Symposium URBAN05 and URS 2005, Tempe, AZ, USA.
Shamshad, A., Wan Hussain, W.M.A., Mohd Sansui, S.A., (2004). Comparison of different data fusion approaches for surface features extraction using quick bird images. Proceeding GIS-IDEAS 2004, Hanoi, Vietnam.
Verma Ravindra Kumar, Kumari Sangeeta and Tiwari R.K., (2009). Application of Remote Sensing and GIS technique for efficient urban planning in India, http://www.csre.iitb.ac.in/~csre/conf/wp-content/uploads/…/OS4_13.pdf
Yao Jing, Wu Wenbo, Kang Tingjun., (2008). Study of Remote Sensing Image Fusion and Its Application in Image Classification. Proceedings of Commission VII, ISPRS Congress Beijing 2008.
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Sarup, J., Singhai, A. Study of Various Image Fusion Approaches for Extraction and Classification of Infrastructural Growth. J Indian Soc Remote Sens 41, 191–197 (2013). https://doi.org/10.1007/s12524-012-0206-7
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DOI: https://doi.org/10.1007/s12524-012-0206-7