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h. Result Analysis Using Map and Histogram
The results of each classification methods in this research are shown in map and histogram. The focus of analysis are the number of mangrove classses that
can be derived from each algorithm and the capability to mapping mangrove into certain level of class it self zone, density, or species. One algorithms will not
compared each other, but explored the capability for mangrove classification using ASTER VNIR data were explored.
i. Data Validation
For validation, need to build new training areas of each class of mangrove were used to validate each map where produced. These training areas are different
with Region of Interest ROI for maximum likelihood supervised classification and neural network. The validation of map as a result of each algorithm apllied,
checked with confusion matrix. Based on this matrix can predict the accuracy of each class.
IV. RESULT AND DISCUSSION
4.1 Synchronized ISODATA Unsupervised Classification with Field Data
The number of peak from ASTER VNIR bands express the capability of this image to detect class of object on the field. Based on histogram of each band on Chapter
III, band 2 have more peaks than the other. It is quite different with the normal condition of reflectance vegetation, because amount of water in the atmosphere and leaf is high.
When, observation was done on middle of June 2008 the same date with ASTER image captured the frequency of rain at Berau delta is often, almost every day, even more than
a times in one day. So, leaf water content becomes increase. The reflectance of NIR was low, while, Red was higher than normal. Because the NIR wavelength absorbed by water.
The impact, when ASTER VNIR image was analyzed, there were only few pixels which have high value of Band 3, because not all of mangrove vegetation have same
capability to keep high amount of water in their leaf. The value of Band 3 will high, if the mangrove leaf fast in past the water. In reality, the type of leaf and canopy gives high
influenced. Nypa with long leaf and almost vertically, will past the water faster than Avicenia and Rhizophora. This means that the pixels which still have high value in Band
3 are pixels of class Nypa. While, the condition of band 2 which more sensitive, it is easy to know because
the frequency of pixels are more various. This means that, these pixels not only express class of Nypa, but also other kind of mangrove conditions. Based on this, band 2 was
used to derived classes in ISODATA unsupervised. There are totally 13 classes, and 5
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