Determining the chloropyhll content [Chloropyhll A and Chloropyhll B] and mapping of rhizophora apiculata and rhizophora mucronata using landsat 8 imagery data at Selat Pulau Tuba, Langkawi / Muhammad Zulkarnain Royazid
Mangrove is a one of a kind woody plant network of intertidal drifts in tropical and subtropical throughout the world which experienced the losses due to the intense demand for mangrove trees which greatly benefits human activities. The aims of this study was conducted mainly to study the distributi...
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| Format: | Thesis |
| Language: | English |
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2020
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| Online Access: | https://ir.uitm.edu.my/id/eprint/32692/ |
| _version_ | 1848808089973686272 |
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| author | Royazid, Muhammad Zulkarnain |
| author_facet | Royazid, Muhammad Zulkarnain |
| author_sort | Royazid, Muhammad Zulkarnain |
| building | UiTM Institutional Repository |
| collection | Online Access |
| description | Mangrove is a one of a kind woody plant network of intertidal drifts in tropical and subtropical throughout the world which experienced the losses due to the intense demand for mangrove trees which greatly benefits human activities. The aims of this study was conducted mainly to study the distribution of Rhizophora apiculata and Rhizophora mucronata species at mangrove area of Selat Pulau Tuba, Langkawi and to measure the total chlorophyll content, chlorophyll-a and chlorophyll-b content in the leaves samples of Rhizophora apiculata and Rhizophora mucronata in laboratory and their relationship with Normalized Diffference Vegetation Index (NDVI) values extracted from Landsat 8 satellite imagery data. ERDAS Imagine 2014 and ArcGIS 10.2 were used to process the satellite imagery data of Landsat 8 which the overall data processes involves preprocessing of the satellite imagery data, layer stack, subset image, optimum index factor (OIF), Normalized Difference Vegetation Index (NDVI), unsupervised classification, supervised classification and accuracy assessment were done. While, the determination of chlorophyll content was determined in the laboratory. The OIF result shows the best three-band combination was 2,3,5 (Blue, Green, NIR). Meanwhile, NDVI Red recorded the wide range of NDVI value at -0.40 to 0.80 to help in distinguishing the vegetation and non-vegetation area compared to NDVI Green. The classification of three main classes of Rhizophora apiculata, Rhizophora mucronata and water bodies was recorded higher using SAM with the overall accuracy resulted at 54.72%. The result of correlation shows most of the analysis have weak positive correlation between chlorophyll a, chlorophyll b and total of chlorophyll with NDVI Green and NDVI Red. However, the regression analysis recorded lower for all since the value recorded in the range of 0.0007 to 0.17. In conclusion, Landsat 8 OLI satellite imagery shows capability in mapping the distribution of the Rhizophora apiculata and Rhizophora mucronata within the study area with the limited spatial resolution of 30 m. |
| first_indexed | 2025-11-14T22:53:11Z |
| format | Thesis |
| id | uitm-32692 |
| institution | Universiti Teknologi MARA |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T22:53:11Z |
| publishDate | 2020 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uitm-326922020-07-27T05:37:06Z https://ir.uitm.edu.my/id/eprint/32692/ Determining the chloropyhll content [Chloropyhll A and Chloropyhll B] and mapping of rhizophora apiculata and rhizophora mucronata using landsat 8 imagery data at Selat Pulau Tuba, Langkawi / Muhammad Zulkarnain Royazid Royazid, Muhammad Zulkarnain Nutrition. Plant food. Assimilation of nitrogen, etc. Mangrove forests Mangrove is a one of a kind woody plant network of intertidal drifts in tropical and subtropical throughout the world which experienced the losses due to the intense demand for mangrove trees which greatly benefits human activities. The aims of this study was conducted mainly to study the distribution of Rhizophora apiculata and Rhizophora mucronata species at mangrove area of Selat Pulau Tuba, Langkawi and to measure the total chlorophyll content, chlorophyll-a and chlorophyll-b content in the leaves samples of Rhizophora apiculata and Rhizophora mucronata in laboratory and their relationship with Normalized Diffference Vegetation Index (NDVI) values extracted from Landsat 8 satellite imagery data. ERDAS Imagine 2014 and ArcGIS 10.2 were used to process the satellite imagery data of Landsat 8 which the overall data processes involves preprocessing of the satellite imagery data, layer stack, subset image, optimum index factor (OIF), Normalized Difference Vegetation Index (NDVI), unsupervised classification, supervised classification and accuracy assessment were done. While, the determination of chlorophyll content was determined in the laboratory. The OIF result shows the best three-band combination was 2,3,5 (Blue, Green, NIR). Meanwhile, NDVI Red recorded the wide range of NDVI value at -0.40 to 0.80 to help in distinguishing the vegetation and non-vegetation area compared to NDVI Green. The classification of three main classes of Rhizophora apiculata, Rhizophora mucronata and water bodies was recorded higher using SAM with the overall accuracy resulted at 54.72%. The result of correlation shows most of the analysis have weak positive correlation between chlorophyll a, chlorophyll b and total of chlorophyll with NDVI Green and NDVI Red. However, the regression analysis recorded lower for all since the value recorded in the range of 0.0007 to 0.17. In conclusion, Landsat 8 OLI satellite imagery shows capability in mapping the distribution of the Rhizophora apiculata and Rhizophora mucronata within the study area with the limited spatial resolution of 30 m. 2020-07-20 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/32692/1/32692.pdf Royazid, Muhammad Zulkarnain (2020) Determining the chloropyhll content [Chloropyhll A and Chloropyhll B] and mapping of rhizophora apiculata and rhizophora mucronata using landsat 8 imagery data at Selat Pulau Tuba, Langkawi / Muhammad Zulkarnain Royazid. (2020) Degree thesis, thesis, Universiti Teknologi Mara Perlis. |
| spellingShingle | Nutrition. Plant food. Assimilation of nitrogen, etc. Mangrove forests Royazid, Muhammad Zulkarnain Determining the chloropyhll content [Chloropyhll A and Chloropyhll B] and mapping of rhizophora apiculata and rhizophora mucronata using landsat 8 imagery data at Selat Pulau Tuba, Langkawi / Muhammad Zulkarnain Royazid |
| title | Determining the chloropyhll content [Chloropyhll A and Chloropyhll B] and mapping of rhizophora apiculata and rhizophora mucronata using landsat 8 imagery data at Selat Pulau Tuba, Langkawi / Muhammad Zulkarnain Royazid |
| title_full | Determining the chloropyhll content [Chloropyhll A and Chloropyhll B] and mapping of rhizophora apiculata and rhizophora mucronata using landsat 8 imagery data at Selat Pulau Tuba, Langkawi / Muhammad Zulkarnain Royazid |
| title_fullStr | Determining the chloropyhll content [Chloropyhll A and Chloropyhll B] and mapping of rhizophora apiculata and rhizophora mucronata using landsat 8 imagery data at Selat Pulau Tuba, Langkawi / Muhammad Zulkarnain Royazid |
| title_full_unstemmed | Determining the chloropyhll content [Chloropyhll A and Chloropyhll B] and mapping of rhizophora apiculata and rhizophora mucronata using landsat 8 imagery data at Selat Pulau Tuba, Langkawi / Muhammad Zulkarnain Royazid |
| title_short | Determining the chloropyhll content [Chloropyhll A and Chloropyhll B] and mapping of rhizophora apiculata and rhizophora mucronata using landsat 8 imagery data at Selat Pulau Tuba, Langkawi / Muhammad Zulkarnain Royazid |
| title_sort | determining the chloropyhll content [chloropyhll a and chloropyhll b] and mapping of rhizophora apiculata and rhizophora mucronata using landsat 8 imagery data at selat pulau tuba, langkawi / muhammad zulkarnain royazid |
| topic | Nutrition. Plant food. Assimilation of nitrogen, etc. Mangrove forests |
| url | https://ir.uitm.edu.my/id/eprint/32692/ |