Mangrove area detection by using high resolution satellite imagery
| Autor: | Noorzalianee Ghazali, Fazlina Ahmat Ruslan, Nor Shafikah Iliyas, Abd Manan Samad, Noorita Sahriman, Nurul Ain Mohd Zaki, Mohd Zainee Zainal, Khairulazhar Zainuddin |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
010504 meteorology & atmospheric sciences
Flood myth Outfall Mangrove area 0211 other engineering and technologies 02 engineering and technology 01 natural sciences Training (civil) Environmental science Ecosystem Marine ecosystem Satellite imagery Mangrove 021101 geological & geomatics engineering 0105 earth and related environmental sciences Remote sensing |
| Zdroj: | 2017 IEEE 13th International Colloquium on Signal Processing & its Applications (CSPA). |
| DOI: | 10.1109/cspa.2017.8064968 |
| Popis: | Mangrove usually found on the outfall or along the beach and commonly the area is a mudflats area. Mangroves have many important roles to the environment and to the marine ecosystem and also protect land from the erosion, flood and even tsunami. Mangrove can be a shelter when there is tempest that come from the sea and can reduce the erosion to the land that cause from the wave. Mangrove have main important role for ecosystem, mapping of the mangrove should be done. But to get the information to map the mangrove area might be difficult since the area of the mangrove is a mudflats area and might have constraint to get the information to map the mangrove area. In this study using remote sensing technology, mapping for mangrove area are easier since it is use satellite image and no need to go to the field which might have difficult and probably have to take longer time to get the data. This study is about to detect mangrove area by using high resolution satellite imagery. Since this study is to detect mangrove area by using high resolution satellite imagery and there are many types of satellite imagery are available, Quickbird images have been used to detect mangrove area. Visual interpretation technique being used to choose the training area and supervised and unsupervised classification will be performed. |
| Databáze: | OpenAIRE |
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