Agriculture Reference
In-Depth Information
Fig. 2.8
Flow chart of remote sensing-based methodology for mapping of mangroves
radiometric corrections were carried out. Ibrahim et al. (
2010
) demonstrated that
the SWIR is very sensitive to liquid water contents and therefore has the potential
as the best index to recognize the mangrove classes. Panigrahy et al. (
2009
) has also
shown the utility of IRS-P6 AWiFS SWIR for crop discrimination and classifica-
tion. Satellite data was then processed using digital image-processing software and
mangroves were classified using unsupervised classification. This was followed
by area calculation in delineated mangrove areas. The area figures of the two as-
sessment periods (pre- and post-tsunami) were compared and changes assessed.
This was followed by identification and delineation of areas where changes have
taken place. The resultant classified data was used for ground verification. The field
visits for ground truth verification were made in January-February 2009. For the
satellite data of 2004-2005 and 2007, ground verification records of the FSI were
consulted. Post-classification, corrections were made after ground truth verifica-
tion. Figure
2.8
presents the flow chart of the methodology used for the interpreta-
tion and the classification of satellite data.
