Analysis of Change Detection Techniques using Remotely Sensed Data
Sadhana Tripathi,  Prof. Ameya Naik,  Mrs. Swapna Patil
Accurate information about nature and extent of land cover changes especially in rapidly growing areas is essential. Change detection plays very important role in different applications such as video surveillance, medical imaging and remote sensing. It plays a very important role in landuse and cover analysis, forest and vegetation inspection and flood monitoring. Semarang City, located on the north coast of island of Java, Indonesia that is very much prone to tidal floods. The objective of this research is to assess, evaluate and monitor the nature and extent of land cover changes in Semarang city through the period from 2012 to 2014 using remotely sensed Landsat multispectral images. Four change detection techniques namely; post-classification, image differencing, image regression and principal component analysis were applied. The objective is extended to examine the effectiveness of each change detection technique regarding the ability to differentiate changed from unchanged areas based on the pixel-by-pixel analysis and calculating the overall number of changed pixels. The results indicated that the post classification change detection technique provided the highest accuracy while the principal component analysis technique gave the least accuracy.
Keywords- Change detection, Post classification, Image differencing, Image regression, Principal component Analysis
Cite this Article
Sadhana Tripathi,  Prof. Ameya Naik,  Mrs. Swapna Patil,   "Analysis of Change Detection Techniques using Remotely Sensed Data"
, International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.3, Issue 3, pp., July 2015, Available at :http://www.ijedr.org/papers/IJEDR1503038.pdf