In this research, an attempted has been made to map paddy rice of the southern coastal areas of Caspian Sea using multi-temporal Radarsat and Landsat TM optical images acquired in different seasons of the year 1998. Two major tasks including land use map preparation and Change detection studies were implemented. Due to the presence of clouds, some parts of the TM based land use map were not completed. So, land use maps prepared with the use of Radarsat and TM fused images derived based on multiplicative, Brovey and principal component algorithms. For change detection studies, image differencing algorithm used to derive the changed areas. Most of the changed areas were observed to be within agricultural lands (Paddy fields). Results of this study show that fused image based on Brovey algorithm has not only eliminated the cloudy areas of TM data but also has more information on land use land cover in comparison with Radarsat and TM images alone. Comparison between land use change map and image derived from change detection studies showed a high correlation between agricultural lands (Paddy fields) and changed areas within the change image. The results of this study could be useful to agricultural and land use land cover planners.
In this research work, an attempt has been made to study the ability of remote sensing data and some of the image processing techniques to map and monitor changes happened over a period of one year in an urban area. IRS 1B LISS II data pertaining to coastal city of Madras, India acquired in the month of April 93 and 94 were registered on each other using EASI/PACE image processing software. Band subtraction, PCA and fuzzy logic were then applied to create a new image showing changed and unchanged areas. MLC algorithm used to classify the images of 93 and this new image. To create change map, a simple procedural program was developed with modeling language of EASI/PACE image processing software. Based on the ground truth information the overall accuracy of classification was observed to be about 70 per cent. Results showed that in this urban area, major changes were observed to be from green areas to built-up area.
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