碩士 / 國立臺灣大學 / 生態學與演化生物學研究所 / 100 / This study is to understand the capability of Quickbird satellite image for mapping the spatial distribution of seagrasses around the Dongsha Island, where the seagrass meadow there is composed of at least six species and occupies an area of 12 km2. Through two methods of image classification, both seagrass coverage and communities with different coexisted assemblages of seagrass species can be mapped, and the thematic maps produced can provide high-resolution and continuous distribution message.
The results showed that using the unsupervised classification to map the seagrass coverage, the thematic map had an overall accuracy of 76%, as well as the producer’s accuracy of 97% and the user’s accuracy of 76% for the seagrass class. When the seagrass meadow was divided into three types of seagrass communities by the unsupervised classification, the overall accuracy was 59%. By using supervised classification, the thematic map had a lower overall accuracy on the seagrass coverage and communities (59% and 46%, respectively), while the producer’s and user’s accuracy of the seagrass classes combined were 63% and 84%. The accuracy of the unsupervised classification was significantly higher than that of the supervised classification in mapping the seagrass coverage. No matter which classification was used, the input of the depth data didn’t improve the accuracy of the image classification, which might be owing to the shallowness of the water and the gentleness of the terrain around the Dongsha Island.
Moreover, this study found that some compositions of seagrass species had similar spectral features with some other habitats, which may cause misclassification. For example, the spectral separability between corals and the seagrass communities with Cymodocea serrulata (or Syringodium isoetifolium) was poor. As the frequent mixture of seagrass species also led to the difficulty of spectral discrimination between some species pairs, like Cymodocea rotundata and Thalassia hemprichii.
Although remote sensing techniques have some limitations in complex environments, such as image classification in the Dongsha Island, it is still an cost-effective way to monitor seagrass meadows located in faraway places, and is quite helpful to seagrass conservation and management.
| Identifer | oai:union.ndltd.org:TW/100NTU05110023 |
| Date | January 2012 |
| Creators | Hsiao-Yun Sun, 孫筱雲 |
| Contributors | Pei-Fen Lee, 李培芬 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 104 |
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