Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/4622
Title: Application of remote sensing data to monitor mangroves and other coastal vegetation of India
Authors: Nayak, Shailesh
Bahuguna, Anjali
Issue Date: Dec-2001
Publisher: CSIR
Abstract: Remote sensing data, because of its repetitive, synoptic and multi-spectral nature, has proved to be of an immense value in monitoring of coastal vegetation. Indian Remote Sensing Satellite (IRS) data have been extensively used to map mangroves and other coastal vegetation for the entire country’s coastline. Large database on spatial extent of mangroves and their condition has been created on 1:250,000, 1:50,000 and 1:25,000 scale using IRS data (the database provides information for the first time on the mangrove areas of the entire Indian coast). Based on this study, it was observed that the Kori creek, Gujarat, has large area under mangroves. The repetitive nature of the data has helped in monitoring vital and critical areas, periodically. In one such study, on the Marine National Park, in the Gulf of Kachchh, mangrove areas were monitored for the last 25 years. The degradation of mangroves continued up to 1985 and the condition significantly improved due to the adoption of conservation measures. This has helped in planning various management actions to conserve this vital ecosystem. IRS data have been used in identifying dominant plant communities in many mangrove areas such as Bhitarkanika, Coringa, Mandovi estuary in Goa and the Gulf of Kachchh, etc. This is a unique approach for providing spatial information at plant community level and can be seen as a first step towards bio-diversity assessment. Along with the mangroves, seaweed, seagrass beds and dune vegetation have also been mapped with reasonable accuracy. With the better sensors planned for future, remote sensing-based information is going to be one of the major inputs in the preparation of management action plans.
Description: 195-213
URI: http://hdl.handle.net/123456789/4622
ISSN: 0975-1033 (Online); 0379-5136 (Print)
Appears in Collections:IJMS Vol.30(4) [December 2001]

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