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Mapping plant communities in the Intertidal Zones of the Yellow River Delta using Sentinel-2 Optical and Sentinel-1 SAR Time series data

Luo, Yansha (2018) Mapping plant communities in the Intertidal Zones of the Yellow River Delta using Sentinel-2 Optical and Sentinel-1 SAR Time series data.

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Abstract:Classification and mapping of the intertidal vegetation play a critical role in wetland conservation planning and policy. Serving as the early indicator of wetland degradation, plant communities in the intertidal zone re the most critical ecological variable in wetland assessment. Traditional survey methods are expensive nd time-consuming. With the development of remote sensing techniques, optical satellite images become more popular and efficient compared with field survey. However, the quality of optical images would be nfluenced by clouds and weather. Thus weather-independent SAR data is considered to provide omplementary information for mapping intertidal plant communities. Vegetation indices derived from ptical time series data play a crucial role in characterising vegetation phenology. In this study, the ntertidal plant communities of the Yellow River Delta were classified using random forest algorithm ased on Sentinel-1 and Sentinel-2 time series images as well as the NDVI statistic parameters derived rom Sentinel-2 time series. The variable importance of different input data from various classification cenarios was also evaluated. It was found that a high mapping accuracy for the intertidal plant ommunities was achieved with an overall mapping accuracy of 75.7% and the Kappa coefficient of 0.73 when integrating the Sentinel-2 time series images with its associated NDVI statistic parameters, which is ignificantly higher than the mapping accuracies derived from either the single-date Sentinel-2 images, entinel-1 SAR time series images or the NDVI statistic parameters alone. Besides, when combining entinel-1 time series, Sentinel-2 time series and NDVI statistic parameters, a further improved mapping ccuracy was achieved with an overall mapping accuracy of 77.7% and the Kappa coefficient of 0.75. The esearch also showed that autumn image and the red edge bands are the most critical variables for mapping intertidal plant communities. The study suggests that combining the Sentinel-2 optical images with the Sentinel-1 SAR images makes it possible to map intertidal plant communities in a dynamic cosystem successfully, and with higher accuracy than when using either the Sentinel-2 time series or the entinel-1 time series.
Item Type:Essay (Master)
Faculty:ITC: Faculty of Geo-information Science and Earth Observation
Programme:Geoinformation Science and Earth Observation MSc (75014)
Link to this item:https://purl.utwente.nl/essays/83705
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