Herwindiati, Dyah E. and Hendryli, Janson and Mulyono, Sidik Robust Kurtosis Projection Approach for Mangrove Classification. Robust Kurtosis Projection Approach for Mangrove Classification.
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Abstract
Mangroves are coastal vegetations that grow at the interface between
land and sea. It can be found in tropical and subtropical tidal areas. Mangrove
ecosystems have many ecological roles spans from forestry, fisheries, environmental
conservation. The Indonesian archipelago is home to a large mangrove
population which has enormous ecological value. This paper discusses mangrove
land detection in the North Jakarta from Landsat 8 satellite imagery. One
of the special characteristics of mangroves that are distinguishing them from
another vegetation is their growing location. This characteristic makes mangrove
classification using satellite imagery non trivial task. We need an advanced
method that can confidently detect the mangrove ecosystem from the satellite
images. The objective of this paper is to propose the robust algorithm using
projection kurtosis and minimizing vector variance for mangrove land classification.
The evaluation classification provides that the proposed algorithm has a
good performance.
| Item Type: | Article |
|---|---|
| Subjects: | Penelitian > Fakultas Teknologi Informasi |
| Divisions: | Fakultas Teknologi Informasi > Teknik Informatika |
| Depositing User: | Puskom untar untar |
| Date Deposited: | 08 Dec 2020 08:34 |
| Last Modified: | 08 Dec 2020 08:34 |
| URI: | https://repotest.untar.ac.id/id/eprint/13333 |
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