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Findlay, HS, Kurekin, A and Selmes, N 2022 Assessment of the environmental, ecosystem, and human activities in coastal Vietnam and Cambodia gathered from satelitte remote sensing. PML Publishing. 1-35. https://doi.org/10.17031/p1rp-f869
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Abstract/Summary
Within the ACCORD (Addressing Challenges of Coastal Communities through Ocean Research for Developing Economies) project, satellite Earth Observations are used for two purposes: 1. To describe basic environmental dynamics around two focus regions, Da Nang Bay in Vietnam and Kep Province in Cambodia. Two aspects of satellite data are examined for this purpose: first, sea surface temperature (SST),); second, water quality data, focussing on chlorophyll a and turbidity. 2. To assess the potential for mapping locations of aquaculture sites around Da Nang Bay, Vietnam, through exploitation of EO data. This second purpose utilises the sea surface radar backscattering coefficient. NOAA’s Pathfinder SST dataset derived from measurements made by AVHRR sensors was used here at 4 km resolution. This dataset offers a long time series, which has gone through rigorous quality control and calibration, and as such is considered a climate-quality dataset. The seasonal cycle as well as the long term dynamics for SST can be observed, showing the monsoon dynamics of the region. No trend in warming over the past two decades is observable from these data. Water quality measurements were investigated using a number of EO-derived products. These products cover different spatial and temporal scales. The first is the ESA Ocean Colour Climate Change Initiative (OC-CCI) – Chlorophyll a dataset. This has a 1 km resolution and is mainly optimised for the open ocean through to moderately turbid coastal waters; the most turbid coastal waters around Da Nang and Kep are frequently masked in this dataset. Larger scale regional seasonality and long term changes in chlorophyll levels are assessed. There is no clear trend through time over the wider regions, however clear spatial dynamics can be observed. The relationship between chlorophyll a and SST over the past two decades was also investigated. Higher levels of chlorophyll a occurred near the coasts at certain times of year, predominantly corresponding to seasonal changes in temperature and increases in river flow during monsoon periods. The coastal and nearshore water quality around Da Nang and Kep was assessed using datasets processed with PML’s Calimnos processor, which includes a blend of algorithms designed for very turbid water and prioritises higher spatial resolution over having the longest time series. The 300 m dataset were derived from Envisat MERIS and Sentinel 3 OLCI, which provide a medium-term time series, although there is a four year gap between the missions so a continuous dataset is not available. These data offer the best balance of resolution and algorithm performance for coastal remote sensing at present. The 60 m water quality dataset was derived from Sentinel 2 MSI, which has been operating since 2015 and hence is a shorter time series. However, the 60 m dataset is especially useful for resolving smaller features, as is demonstrated by highlighting small eddy features and river outflows around both Da Nang bay and Kep. The method for detecting and mapping aquaculture structures, such as finfish cages, shellfish farms and floating houses using freely available Sentinel-1A SAR sensor data was successfully applied to Da Nang bay and nearby rivers. 11 aquaculture sites were identified in the bay and in the rivers, confirmed by comparing with high resolution Google Map satellite images. Comparing static maps across different years shows that this method can be used to monitor temporal changes in detected aquaculture sites.
| Item Type: | Publication - Article |
|---|---|
| Divisions: | Plymouth Marine Laboratory > National Capability categories > NC-ODA Plymouth Marine Laboratory > Science Areas > Earth Observation Science and Applications Plymouth Marine Laboratory > Science Areas > Marine Ecology and Biodiversity |
| Depositing User: | S Hawkins |
| Date made live: | 09 Jan 2023 11:37 |
| Last Modified: | 17 Jan 2023 16:54 |
| URI: | https://plymsea.ac.uk/id/eprint/9835 |
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